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Data ratcheting and data-driven organisational change in transport:

Data ratcheting and data-driven organisational change in transport: This article explores the process by which intelligent transport system technologies have further advanced a data- driven culture in public transport and traffic control. Based on 12 interviews with transport engineers and field- work visits to three control rooms, it follows the implementation of Real-Time Passenger Information in Dublin and the various technologies on which it is dependent. It uses the concept of ‘data ratcheting’ to describe how a new data- driven rational order supplants a gradualist, conservative ethos, creating technological dependencies that pressure organisations to take control of their own data and curate accessibility to outside organisations. It is argued that the implementation of Real-Time Passenger Information forms part of a changing landscape of urban technologies as cities move from a phase of opening data silos and expanded communication across departments and with citizens towards one in which new streams of digital data are recognised for their value in stabilising novel forms of city administration. Keywords Intelligent transport systems, real-time information, smart city, Big Data, organisational change ITS forms the basis for a longitudinal study on how Introduction data-driven organisational control is being enacted in There is a quiet ‘revolution’ underway in the transport our cities, drawing attention to the concept of ‘data- sector as intelligent transport systems (ITS) technolo- ratcheting’ to show how these data-driven changes are gies are used to increase efficiencies and integrate urban iterative and leveraged off previous innovations. The functions, through an alliance of well-established trans- evolution of ITS is dependent on long-standing com- port technology companies in partnership with city mitments to shared infrastructure, and indicative of a engineers and technologists. ITS originates in the con- shift to increasing autonomous management of public text of managing and coordinating road use, but inter- transport and traffic while overseen by human oper- faces with air, rail and water systems (Williams, 2008: ators. The article seeks to contribute to the theoretical 3). While discursively enveloped in the promise of the literature on standards and Big Data by building an smart city in recent marketing programmes such as that explanatory account of data-driven organisational of Dublin (Coletta et al., 2018a; Kitchin et al., 2018), change based on a case study on the deployment of the history of ITS extends back further over several Real-Time Passenger Information (henceforth RTPI) decades with the development of CCTV-supplied traffic in Dublin. It focuses primarily on the implementation control rooms, junction controller software, and sche- duling systems for public transport. Therefore, it pro- UCD School of Architecture, Planning and Environmental Policy, Dublin, vides a counter-example to the creation of new urban Ireland corporate districts branded as ‘smart’ (Wiig, 2019), or reductive concepts of a universal urban science Corresponding author: (Shelton, 2017), inasmuch as it accounts for a gradual Liam Heaphy, UCD School of Architecture, Planning and Environmental evolution of ‘smart’ or intelligent technologies within a Policy, Richview, Clonskeagh, Dublin 14, Ireland. specific sector. Email: liam.heaphy@ucd.ie Creative Commons CC-BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http:// www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 Big Data & Society of RTPI on bus services and considers the wide array of of the field of microbiology on particular visual and technologies on which RTPI is reliant, including loca- mechanical model kits. tional technologies, telecommunications and informa- The digital revolution has expanded the remit of tion standards. infrastructure studies. Star and Ruhleder’s (2001) sem- The following section reviews existing theory on data inal study on the creation of a unified, computer-based infrastructures in relation to its bearing for understand- and networked worm system for scientists examines the ing the deployment of new technologies. This is fol- frictions that occur around arcane choices of network- lowed by a description of the fieldwork and methods ing technologies or operating system, providing a useful underpinning the empirical content. The subsequent distinction between first-, second- and third-order three empirical sections then detail the deployment issues. First-order issues concern direct matter-of-fact of RTPI in Dublin, largely in temporal order and iden- phenomena and can be solved with existing resources tifying the various phases of development. This and processes, such as finding and enabling a software covers earlier trials, the negotiation of common infor- option. Second-order issues reflect unforeseen context- mation standards, forms of data-driven behavioural or ual effects, such as the choice of one suite of procedures procedural change, and the consolidation of oper- or standards over another and the path dependencies ational intelligence technologies. The penultimate sec- that result. Third-order issues are inherently political, tion further discusses data ratcheting in relation involving ethical frameworks, theoretical paradigms to procedural and organisational change. The conclu- and schools of thought. They may arise from combin- sion then discusses the evolution of data-driven ations of first- and second-order issues, such as where change in transport and speculates on further research an awareness emerges that legacy technologies are con- directions. straining accessibility, opening the path towards more fundamental questions on the collective good. Following Kitchin (2014a), we can associate the cen- Combining studies of the mundane with turies-old Big Data of climate science referred to above data assemblages with volume and variety. However, it is with ITS and The study of infrastructure has covered both epic trans- similar forms of sensor-fed, large-scale digital networks formations, such as the electrification of Western socie- and models that we can see the increasing importance ties (Hughes, 1993) and the mundane ‘boring things’ of velocity (i.e. real-time or close to it). ITS relies on (Star, 1999), such as the file folder system for comput- complex assemblages of information networks, human ing and its consequences for systems management engineers and controllers, transport policies, road-side (Yates, 1993). In the former, Hughes’ panoramic view sensors, in-vehicle computers and global positioning of large technical systems repurposes the military term systems to choreograph in real-time an increasingly ‘reverse salient’, pertaining to line formation, to define wide array of objects in space. It is part of a shift where blockages in one domain may be cleared by pro- towards data-driven design and maintenance of urban gress in another. Infrastructure becomes a means of transport systems, drawn into discourse on the ‘smart analysing how systems travel and extend into local con- city’ through including ‘smart travel’ or transport in texts, and a basis for forming concepts to explore their funding programmes and established practices of clas- many contingencies and the development of common sifying smart technologies (Giffinger and Pichler- standards of information exchange. Milanovic´ , 2007), as well as through the inroads into Infrastructure studies blend the archival patience of transport sought by data analytics companies. the historian with the attentive eye of the ethnographer Calls have been made to study actually existing and require a predilection for interrogating technical ‘smart cities’ (Coletta et al., 2018a; Shelton et al., reports and manuals. In this vein, Edwards (2010) 2015), and engage with software by analysing critically covers the pioneering work of climate observers in the how data interact with urban space and society 19th and 20th centuries and the process of reanalysis, (Kitchin and Dodge, 2011). This can take the form of where scientists reconcile data from multiple sources following the data and ‘attending to the sociotechnical into uniform global datasets. This large temporal fuzziness of data as it falls between epistemological scale opens up concepts such as ‘infrastructural inver- problems, material infrastructure and organizational sion’, where ‘historical changes frequently ascribed to concerns’ (Coletta et al., 2018b: 6). It implies looking to the ‘proxies’ of data, where data flows are trans- some spectacular product of an age are frequently more a feature of an infrastructure permitting the develop- formed, bifurcated, or collated; whether that be ment of that product’ (Star and Bowker, 2006: 233). It errors and anomalies in sensor networks and transport also facilitates the analysis of positive and negative systems (Reed, 2018; Reed and Webster, 2010), or externalities associated with standards, such as the rollout of sophisticated city-wide projects in Meinel’s historical study (2004) on the contingencies partnership with industry giants (Shapiro, 2018). Heaphy 3 Furthermore, it requires attention to the power rela- organisational technologies. A continual negotiation tions and values implied as these data are recruited and policing of standards is necessary to ensure data- into new modes of data-driven urban governance. driven processes can function to a required degree of Shelton (2017) shows how Big Data-inspired visual- resilience, for which the study of first-, second-, isations of vacant lots may depoliticise ethnic and social and third-order issues aid in our comprehension of inequalities, normalising the principles by which such how this occurs on different levels. Finally, the titu- inequalities are largely left in place. Consequently, it is lar concept of data ratcheting functions as a creative useful to account for the totality of politics, data, values interlacing of these final and overlapping phases as and materialities that underwrite such visualisations or new functions, products and services are discovered policy tools. Kitchin and Lauriault (2014: 1) advance and implemented in a context of data-driven the concept of a ‘data assemblage that encompasses all rationalisation. of the technological, political, social and economic The fieldwork introduced below corresponds to apparatuses and elements that constitutes and frames recent phases of data expansionism and operational the generation, circulation and deployment of data’. It consolidation. However, the implementation of RTPI functions as a means of expanding discussion to how in Dublin, particularly on bus services, evidences the data reshape society, and resultantly, how data-driven long infrastructural timelines of ITS. Therefore, the sec- change leads to further developments and the creation tion thereafter covers this initial period from the 1970s of new path dependencies. This aids in drawing atten- until the near-present, before then considering how tion to the politics of Big Data (Shelton, 2017), the RTPI standards were negotiated and how data-driven rights of citizens to the digital city (Foth et al., 2015), organisational change ensued. and data literacy (Gray et al., 2018). This article takes its cue from data assemblages as a Fieldwork and methods means of exploring how urban datafication reshapes urban management and control. Kitchin (2014b: 25) Dublin’s RTPI system covers Bus Atha Cliath (hence- pursues data assemblages in relation to how data can forth Dublin Bus), Bus Eireann (a public national usher in new regimes of data-driven societal control, coach company), Luas (tram system), and Iarnrod tabling a broad array of constituent factors. The fram- Eireann (the public national railway company). ing of RTPI as a data assemblage opens discussion into Dublin Bus registered 136.3 million journeys in 2017, how ‘each apparatus and their elements frame what is as compared to 37.6m for the Luas, and 45.5m for possible, desirable and expected of data’, including gov- Iarnro´dEireann nationwide (NTA, 2018: 201). The ernmentalities, materialities, practices and systems of focus of research reflects the operational area of thought. This article is particularly concerned with Dublin Bus, corresponding to the Greater Dublin procedure; how transport systems have integrated Area (GDA). The GDA comprises four predominantly data-driven technologies into their internal modes of urban local authorities with a combined population of organisation and coordination rather than their chan- 1,347,359 in the 2016 census and three surrounding ging relationship to passengers and broader society. rural counties. There is no corresponding transport Modern intelligent transport technologies, it is main- authority for the GDA. Instead, the national scale tained, represent an instance of urban datafication and tends to be the favoured tier for integrated services consolidation, as organisations experiment with Big across local authorities (Coletta et al., 2018a: 4). The Data in the interests of increased efficiency and per- National Transport Authority (NTA) is responsible for formance. This process of urban datafication can be both national and regional transport planning includ- described with recourse to three translations. Firstly, ing the GDA. data expansionism occurs through the deployment of The choice of the fieldwork site and the topic of sensing technologies and ICT infrastructure to create transport technology reflect a wider objective of track- new datasets. Concepts from infrastructural studies ing Dublin’s self-promotion as a ‘smart city’ as part of a such as ‘reverse salients’ help explain how data plat- large multi-researcher project. It forms one of several forms come into being as new technologies facilitate complementary case studies on how smart technologies change and transport authorities and providers build and Big Data are transforming urban life (cf. Cardullo necessary infrastructure. Secondly, as new data sources and Kitchin, 2018; Coletta et al., 2018a; Perng and become available, data experimentalism ensues as a Kitchin, 2016). The empirical research presented in range of actors compete to create new services and this article draws on 12 semi-structured interviews products. Finally, a third phase of operational consoli- derived from two related fieldwork datasets. The first dation can be delineated, as new forms of data-driven six are a subset are drawn from a larger set of 77 inter- behavioural change, based on the dynamic treatment of views conducted with government and city workers, real-time data, are encoded into procedures and corporations, and other stakeholders on Dublin’s 4 Big Data & Society emerging smart city strategy in 2015/2016. These radio-based triangulation systems to an acceptable include five transport engineers from local and national degree of accuracy and temporal resolution. It was government and one transport consultant, all of whom tested for select bus routes in urban areas throughout discuss ITS in relation to traffic control, road design the 1970s with varying degrees of success (Roth, 1977). and maintenance, and public transport reform. The For mass transport systems, AVM promised a more remaining six are part of subsequent in-depth studies efficient and less costly alternative to the ‘point men’, with transport operators (Bus Eireann, Dublin Bus, employed to record stop times of buses and inform Luas) and traffic control room engineers (Dublin City schedule adherence and redesign (Roth, 1977). These Council) on interrelated RTPI and traffic management elemental technologies of control contribute towards technologies in 2016/2017. tackling the perennial issues of buses running ahead Interviews were conducted in situ in back offices of schedule (understood to be considerably worse (NTA, Luas, Bus Eireann) and control rooms (Dublin than running behind, as it causes disruption to drivers Bus and the traffic control rooms of Dublin City further back down the line and frustration to patrons) Council and South Dublin County Council). and maintaining even headway (where buses are dis- Observational fieldnotes from visits to the control tributed evenly along the route). It was recognised in rooms and impromptu conservations with operators the late 1970s that AVM could be used to provide both provided additional perspectives. Interviewees were frequent and reliable service information to passengers asked to explain their roles, the deployment of RTPI and also integrate with traffic control systems to give in their organisation and its relationship to other tech- signal priority to oncoming public transport vehicles nologies, decisions on standards and their implementa- running behind schedule (Symes, 1980: 237). Dublin tion, and their coordination with other transport Bus first trialled AVM in the 1970s using odometers providers and regulators. The insights offered by par- fitted on buses that reported by radio to a central ticipants were supplemented by reports and secondary server every 45 seconds, subsequently rolled out to all literature to inform the longer timeline of ITS in bus depots by 1981. In 1985–1987, Dublin Bus also Dublin. trialled traffic prioritisation based on a combination of infrared transponders installed on buses and road- side detectors. This was linked to the AVM system, but Four decades of pilots in Dublin funding was not available to continue a successful pilot. In Dublin as elsewhere, the development of ITS can be The AVM system continued until the end of its useful seen to be dependent on a supporting infrastructure life in the 1990s but was not replaced, with controllers which allows innovation to occur over multi-decadal reverting to radio contact with drivers (World timescales. There were many instances of transport Bank, 2011). innovation over the last few decades, but without suf- In 2001, a second trial of next-generation GPS-based ficient coordination between the relevant bodies, they Automatic Vehicle Location (AVL) called ‘Q-time’ was failed to scale up or attract sufficient continuity support conducted on select Dublin Bus routes, and for the first from national or local government. time, RTPI signage was fitted (Caulfield and RTPI allows public transport users to consult the O’Mahony, 2004). This trial continued for three years predicted departure time of services and determine the during a period in which there was perennial threats (or most efficient mode of travel, based on the latest infor- opportunities) to liberalise the transport sector. The mation on traffic delays, interruptions and capacity. Irish Minister for Transport announced in 2002 that RTPI improves perceived reliability as passengers rate 25% of bus routes in the capital were to be opened to their transport providers more highly if they are kept private competition, while also proposing the develop- informed of how the system is performing and can ment of a ‘Dublin Land Use and Transport Authority’ make more sophisticated information-driven travel in line with best practice across the European Union decisions (Caulfield and O’Mahony, 2009; Watkins (Caulfield and O’Mahony, 2003: 2). Privatisation in et al., 2011). Although transport operators can fall transport is associated with market deficiencies includ- back on scheduled timetables and rosters to provide ing the dumping of non-profitable but socially basic transport infrastructure, the higher levels of ser- important routes, and fare-creep on monopolised vice attained with transport technologies are critically well-transited routes. Observing the UK experience, further inefficiencies may include competing companies dependent on software and automation. RTPI is dependent on automatic vehicle monitoring serving the same routes, multiple and incompatible (AVM), a technology which reports real-time informa- ticketing options, and the duplication of management tion on the location of vehicles back to a central server. and control resources (cf. Sørensen and Gudmundsson, AVM dates back to the late 1960s, with trials in the 2010). Privatisation is therefore often accompanied United States of America and other nations to develop with a parallel investment in new regulatory structures Heaphy 5 to mitigate these issues while proceeding on the ideo- was initiated] that Dublin City Council was a better logical basis of lowering public investment costs and vehicle to actually procure the RTPI and subsequently mitigating militant trade unionism (Gomez-Ibanez that project and contract moved over to the NTA’ and Meyer, 2011). (interview DSC27, NTA). The NTA have adopted the In this context of uncertainty and privatisation in the infrastructure created by Dublin City Council and early 2000s, Dublin Bus did not attain funding for a added further measures to ensure its resilience, while city-wide implementation of their Q-time pilot. also extending RTPI and the Leap smart travel card Therefore, by the time RTPI was finally funded and to other cities and towns in Ireland. implemented city-wide on buses from 2009 to 2011, it The AVL data from services are fed back into a was a mature and largely consolidated technology com- central RTPI server, and subsequently into roadside monplace in European cities like Gothenburg and display panels via cellular communication or GSM, Helsinki since the mid to late 1990s. Acting as a reverse with data hosted in two data centres in the Dublin salient, the arrival of GPS was making locational tech- Docklands with various failsafe mechanisms. This nologies part of everyday experience for both transport informs two official NTA apps (RealTime Ireland and operators and personal devices (Kitchin, 2014b: 58), Journey Planner) that cover all services, as well as sev- and could overcome technology resistances experienced eral operator apps (Iarnro´ dEireann and Luas). RTPI during the first 1980s generation of AVM. The first data are available via a public API to researchers and service-wide implementation of RTPI in Dublin was commercial developers under a CCBY 4.0 license. for a new tram service in 2004, Luas, run on a franchise Programmers can write their own queries in XML basis by Veolia, and before the bus implementation was (extended mark-up language) or JSON (JavaScript finalised. It shares road-space with private vehicles for object notation) to pull down specific information, which it gets priority when approaching junctions. which can then be pushed into custom-made displays Sensors are placed at intervals of 100m or more for specific purposes. which gather information from transponders on trams These developments have given rise to two forms of and send it to a central server and operations room. data expansionism: that within and between the core As evident in the timeline below (Figure 1), Dublin operators themselves and largely based on AVL, Bus had accumulated or retained experience with RTPI including scheduling, data analytics and traffic priori- tisation; and that permitted by the API, for research through successive trials by the time of its definitive roll-out of AVL, in partnership with a specialist and commercial usage. The next section details how German transport technology company, INIT. RTPI standards are managed between operators and A Dublin Transportation Office had been created in the regulator in order to support this two-tier ecosys- 1995 to put into place a transport strategy for the city tem, while the final empirical section considers how region under the remit of the Department of Transport. AVL and RTPI are supporting the operational consoli- It established a committee to oversee the implementa- dation of data-driven functionalities. tion of RTPI in 2001, and contracted Atkins consult- ants in 2002 to create a general strategy. The report, Negotiating and maintaining data published in 2006, noted the inconsistencies of informa- standards tion provision between services and the absence of an overarching mechanism to ensure holistic planning of It was the responsibility of Dublin City Council, and both physical and informational infrastructure. It then the NTA, to create consistency of information strongly recommended the creation of a specific provision, ensure infrastructure compatibility, and public transport information office ‘with responsibility develop a common brand with its accompanying clear for collecting data, publishing information and setting aesthetic. This involved the redesign of bus-stops, the standards’, ‘the development and marketing of a public rollout of RTPI displays for multiple operators, the transport ‘‘brand’’ common to all modes and operators creation of an efficient and reliable back-end and tele- that the public can identify with, trust and rely upon’, communications system, and the policing of informa- and ‘the development of a set of agreements and pro- tion systems to ensure interoperability between cesses governing agency participation’ (Atkins, 2006: iv). transport providers. This required a co-constitutive The mooted idea of a land use and transport authority development of procedures encompassing both human materialised in the form of the NTA, which fulfils the operators and software, where the latter is understood remit suggested in the report at the national scale. It also as partial or fully automated procedural systems. incorporated the Dublin Transportation Office and its Anomalies and breakdowns make infrastructure vis- data-modelling team (interview DSC27, NTA). ible (Star and Ruhleder, 2001), and their resolution As the NTA was not created until 2008, ‘it was allows us to follow how standards are negotiated and agreed at the time [that the implementation of RTPI stabilised. Such is the case with ‘ghost buses’, where 6 Big Data & Society 1 1978 AVM/L Automatic Vehicle Monitoring / Location DPT Dynamic Prioritisation of Traffic RTPI Real-Time Passenger Information Technology pilot Operational implementation Dublin's Traffic Management Centre opens 1987 SCATS deployed on junction controllers across Dublin Dublin Transport Office created 1995 Announcement of partial bus privatisation and 2001 idea of a "Dublin Land Use and Transport 2002 Authority" 2003 Atkins RTPI Report published 2006 Creation of National Transport Authority (incorporates the Dublin Transport Office) Leap smart card launched 2011 Dublinked data store launch with API for RTPI (all providers) Data.Gov.ie launched Privatisation of select routes begins 2016 BusConnects consultation (a new rationalisation 2018 of all Dublin Bus routes) Dublin Bus Luas (tram) Bus Éireann Figure 1. A timeline of RTPI-related transport technology deployments in Dublin for bus and tram services, with further events on the left. IarnrodEireann is not included, which relies on its legacy signalling systems in addition to AVL. services shown in RTPI fail to materialise. This anom- their anglicised counterparts, e.g. Cluain Saileach (a aly provides insight into the various orders of issues meadow of willows) and ‘Clonsilla’. The ghost bus encountered and their relationship to organisational anomaly resulted from a series of actions starting change as the NTA exercised its authority over trans- with Dublin Bus curtailing a bus and redirecting it port operators. There are many reasons for ghost buses, before meeting its scheduled destination. Of the two one of which was due to communication failures information standards used by transport organisations between operators as discussed below and resolved by in Ireland, VDV452 is used for scheduled timetables early 2016. Its elimination and that of other issues that and SIRI for real-time feeds. Dublin Bus changed a affected accuracy involved both repairing bugs and 19-character field in SIRI called ‘DestinationRef’ in a policing adherence to standards. For 2017, it was way that partners did not expect, as the employee cited reported that 97.5% of RTPI information was correct below explains, because it did not have enough space with reference to arriving within 1 minute of the ‘Due’ for both languages, necessitating the use of a further prediction (Bus Atha Cliath, 2017), up from 92% in field called ‘JourneyNote’: 2012 (Worrall, 2012) and 89% when initially launched. In agreement with language policies for State bodies, For example, we send the journey ref [which] would RTPI information, including destination information, say, ‘Okay, this journey is doing this destination and on trains, buses, and trams, is displayed and announced now that destination has changed’. So say, for example, in both English and Irish. The original versions of a trip is going from A to B and we decide, okay, it is not many Irish place names now share equal space with going to B anymore, we’ll bring it back somewhere. AVL AVL AVM RTPI RTPI DPT Data-driven scheduling DPT DPT AVL RTPI AVL RTPI Heaphy 7 Figure 2. Dublin bus live monitoring of schedule adherence in their control room. Now it can’t handle that at the moment, the new des- corresponding real-world names in various languages tination, it still tells passengers you are going all the in adjacent columns: way to B. They are working on it and they are almost there. We had the same problem with the street signs Yes, and largely that works fine if you don’t go putting for quite some time but they worked on that and they stuff in places where it shouldn’t be, like journey notes were fixed [by their external contractor] and that got shouldn’t be in there. So the system trying to under- resolved, that got changed. So now for example if you stand that doesn’t see it and therefore these, I suppose are going to Maynooth on a 66 [bus] for example, and important things, because curtailments and cancella- for whatever reason, operational or whatever, they tions are really what you need to know about in real- decide, okay this bus can’t go the full journey, it can time. You need to know if your bus is not going to the only go as far as Leixlip. We can now tell on the street destination or if it has been cancelled. So they are signs, we can tell on our app on our website that to the things we can fix but they are expensive because what passengers straight away, it could be on the bus itself, you will find is that an incumbent will see that as an on the displays, they can be told this bus is now finish- opportunity to, let’s say, know that nobody is going to ing in Leixlip. Whereas on the NTA’s app they are still compete with their price and therefore I would say give telling you ‘Maynooth’. So it will be fixed quite soon, in ridiculously high prices to do fairly simple stuff. [.. .] they have been working on it for a number of months And so really our experience is to kick back and say, now so it should be fixed soon. But on the street signs ‘Sorry, guys’, right at the very start, stick to the speci- and our web that is reflected correctly. But that is kind fications. [.. .] So over the years the system has been in of a bug thing, that isn’t anything to do with the stand- place and more people want to build ancillary systems ards really, that is more a bug on their internal system or reuse the information, the more we have learned that than anything. It is no limitation of SIRI or the VDV right at the start you need to be the policeman. that has caused that. (Interview RTPI01, Dublin Bus) (Interview SD13, NTA) Dublin Bus considered that their usage was consistent The central regulator talks of their role of policing with SIRI and that the issue reflected an external con- common standards to ensure fair competition between tractor’s inability to read this information. In contrast, providers through shared rather than privileged infor- the NTA interviewee cited below indicated mation. It has weekly meetings with RTPI representa- ‘JourneyNote’ as being more for minor notes like tives from the main transport providers during which being ‘guide dog-friendly’. This alleged non-standard anomalies and their potential solutions are discussed. use broke the information feed downstream, even if While assertive about its policing role, a solution was the change suited the challenge of frequently curtailing negotiated that allowed Dublin Bus a degree of flexibil- buses due to the large but necessary interruptions ity in their implementation of SIRI, creating custom caused by Luas cross city. code to recognise Dublin Bus curtailments. The A common solution for multiple language provision changes were visible first on the street signs, and is to use a generic code in a look-up table with reflected later on the NTA smartphone app. 8 Big Data & Society This second-order issue on adherence to common at cubicles equipped with several graphical user inter- standards reflects a transition from putting in place faces for monitoring buses in real-time. the basic infrastructure towards consolidating RTPI Much the same as the recording devices affixed to in a new suite of procedures and processes, yet also chain retail workers, these technologies constrain interacts with higher third-order reconfigurations of employee behaviour in order to provide an experience power relations as the regulator imposes a new perfor- to customers that is invariable and therefore negotiable mance-driven ethos on operators. As the transport with less cognitive effort. Dublin Bus is a public com- franchise-holder, the NTA has the power to outsource pany and many of the staff in the control room are ex- routes to other suppliers, oversees performance man- drivers themselves, their exchanges with drivers replete agement for all contracted transport providers, and is with banter and laughter yet nevertheless effecting a therefore at the heart of negotiations on privatisation culture change within the organisation: and standardisation. During the time of fieldwork, there were industrial disputes involving Luas tram dri- [B]efore the AVL system, the only way of knowing vers, and protracted discussions on the costs and bene- where a bus was, unless there was a guy out on the fits of partial privatisation of national services targeting street watching the buses coming in and the inspector Dublin Bus and Bus Eireann. Over the course of 2016 on the road. Or else it was the control up above calling to 2018, 24 routes from Dublin Bus and 6 routes from the driver and saying, ‘Where are you?’ And now it is a Bus Eireann were listed for privatisation (Tallaght case of ... It was funny at first seeing it happen because News, 2017) with UK firm Go-Ahead winning both they’d be saying I am in such and such a street. And the competitions. The NTA manages routes, schedules, controller would say, ‘No you are not. I can see within fares, vehicles, quality control and RTPI for new pro- 20 seconds of where you are’. That took a bit of getting viders. In this manner, it hopes that like with Transport used to and now the drivers are at the point where they for London, tenders for routes are largely inconsequen- are embracing it very much so. It took a while for them tial for passengers through a model of competition for to trust it. [.. .] But yeah, they have taken it on board the market rather than in the market (Preston and now and they do realise all the old ways of operating Almutairi, 2013). have to change. (Interview RTPI01, Dublin Bus) Operational consolidation here was the prerogative of an increasingly assertive state actor, the NTA, which The interviewee above notes the role of AVL in sup- addressed administrative fractures between State com- porting measures to improve quality of service. They panies through control over both markets and data. are enforced not only by control room operators, on This facet of data ratcheting comprises data- whose terminal screens buses are highlighted in red for driven organisational control over operators and being behind or ahead of schedule (see Figure 2), but requires collective adherence to data policies. At the also on vehicles themselves through devices to notify intra-organisational scale, within Dublin Bus and Bus drivers if they are running ahead of their scheduled Eireann, real-time data on the location of vehicles stops via a beep and a red dashboard light (only and drivers also enabled data-driven organisational when the vehicle is stationary). Together with the con- control, in part based on new data-driven functional- trol room and its real-time displays, data analytics, and ities. This ratcheting provides momentum to the a management team with key performance indicators to cycle of expansionism, experimentalism and consolida- meet, these technologies all coerce human behaviour tion as new datasets are created and further use- towards minimising error and irregularities. A realisa- cases found. tion of the potential of data to drive internal reform has led to further local innovations, including using data analytics packages to recalibrate schedules (timetables) Data-driven procedural change and data based on statistically examined journey times, and ratcheting developing new internal performance metrics for man- AVM and RTPI technologies in Dublin have given rise agement. These measures further improve RTPI accur- to a cascade of data-driven organisational changes. In acy, and evidence how data ratcheting reshapes internal many instances, these are local learnings of established organisational control as engineers experiment with, international best-practices, yet also include instances and operationalise, new functionalities. of innovation such as the many small data-driven In addition to schedule and route alterations, further changes to routes to reach industry-standard RTPI interventions in the interest of efficiency can be either accuracy. Dublin Bus’s schedule management software physical, such as changes to the road layout, or digital, is reliant on AVL and creates a more constant and through alterations to the junction signalisation pat- intimate connection between drivers and controllers. terns of traffic lights. The greater part of Dublin’s The latter are housed in a control centre and seated road network is managed with industry-standard Heaphy 9 software (SCATS) that alters junctions dynamically in we were collecting and providing. But certainly we have response to traffic by swapping between pre- realised now that we have a huge wealth of information programmed plans. Traffic prioritisation has now at our disposal in terms of where buses are at, the been rolled across the SCATS network for public trans- best journey patterns being used, and we can analyse port by using RTPI data in SIRI format to estimate that now and start using that to make the planning proximity (O’Donnell et al., 2018). This belated but decisions more effective going forward. (Interview eventually successful deployment of traffic prioritisa- DSC27, NTA) tion (see Figure 1) relates to third-order issues sur- rounding the dominant trend of transitioning to a The expansion of metrics and accountability reinforces low-carbon future by progressively revoking privileges an ‘audit culture’ (Strathern, 2000), dependent on tech- once handed out willingly to the private motorist and nologies that ostensibly serve passenger service provi- increasing investment into public transport. sion but which also expand into technologies of control The schedule and fleet management software, the and regulation. Data ratcheting represents a quasi- data analytics functions for route optimisation, and Lamarckian evolutionary progression as organisations automated bus prioritisation form part of an estab- create ever more sophisticated secondary products from lished practice of ratcheting the recognised power of high-quality data, recognising its power and curating it data to redefine procedures, and by extension, urban with discretion according to socio-cultural specificities flows and spatial relations. Data-driven functionalities and legal frameworks. On the one hand, this may become perceived as integral during this phase of effi- involve preventing such data from being misused for ciency and rationalisation. A Dublin Bus technician criminal purposes, while on the other, it could be notes that data are ‘growing more and more into deci- used to maintain competitive advantage or increase sion-making around the company’ and adds: control over consumers or citizens. The empirical data presented here account for largely internal and So it is a complete [change of] mind-set, everything has inter-organisational data-driven innovations yet may changed. Once you trust in the data better decisions can eventually lead to broader data assemblages beyond be made [.. .]. the transport sector, aligning with broader commercial It was unbelievable straight away, things like when a or political interests. door opened, you could see straight away, just infor- mation that you just couldn’t have before so straight Conclusion away you were just giving the power to the managers to see exactly what was going on, the routes, and ultim- In their future roadmap of ubiquitous computing, ately that is getting back to the customers. (Interview Dourish and Bell (2011) highlight the emergent nature RTPI04, Dublin Bus) of technologies, which initially developed separately, coalesce in what are seen retrospectively as unitary sys- This localised data experimentalism and consolidation tems such as the smart home or the city dashboard occur alongside larger-scale operational changes as cen- (Kitchin et al., 2016). Technological changes are also tralised authorities coordinate transport services and essentially organisational and procedural, liberating the data, creating new products and services to consolidate human mind from repetitive drudgery, and facilitating those initially created by individual transport providers. new forms of behaviour between people and their inter- This includes the present BusConnects programme, action with the environment. Tracing their evolutionary initiated in 2017 and led by the NTA, for the rational- development reveals the multiple path dependencies isation of all bus services in Dublin. Two NTA partici- and reverse salients (Hughes, 1993) that characterise pants below recognise the potential of data for better their real-world implementation, and furthermore illus- strategic planning: trates the value of blending the historicism of infra- structure studies with the study of data assemblages. So I think once you have the kit with proper manage- The rollout of RTPI in Dublin is interrelated with ment and working between different companies you can broader transport technologies including automated make these improvements to raise the reliability and the vehicle location systems and traffic control systems, perception of reliability to people. So I see expanding and evidences how its local implementation is part of the system but also harvesting it to offer better prod- an arc of technological changes in ITS. It initiates in the ucts. (Interview SD13, NTA) 1970s with advanced trials that were inconsistently Yes, we use the data for a number of purposes. The resourced by the State until the context itself had initial objective was to provide more information to the shifted. The national economy had moved towards consumers to actually make transport more accessible; higher-value technologies and services with a more that is the real value we saw from the information that informed and demanding workforce, necessitating the 10 Big Data & Society provision of seamless multimodal transport, integrated cultural contexts, as well as from the extended time- ticketing, and RTPI. scales of infrastructure development and attention to The deployment of RTPI allowed individual oper- glitches and breakdowns. ators such as Dublin Bus to experiment with and drive their own internal procedural reforms, with instances of Acknowledgements both localised learnings and more genuine innovations I am indebted to Professor Rob Kitchin for his very helpful as local actors participated in European and inter- feedback and input into this article and research, which formed national networks for developing and disseminating part of a larger research project on the smart city for which he best practices. These activities are described here as was principle investigator. My thanks also to Dr Sheila Convery for her comments on the article, and to the editorial instances of data ratcheting, as new data-driven func- team and three anonymous reviewers for their comments. tionalities are implemented iteratively as they are dis- covered in a local context, oriented towards a more Declaration of conflicting interests rationalised data-driven culture. Glitches such as ‘ghost buses’ provide a window into the politics of The author(s) declared no potential conflicts of interest with data, as the transport sector modernised and the respect to the research, authorship, and/or publication of this article. NTA consolidated its mandate to improve passenger experience by policing standards and controlling pro- Funding viders. This hierarchy of procedural authority, from regulator to operator to driver, has been strengthened The author(s) disclosed receipt of the following financial sup- through the creation of governmental bodies that port for the research, authorship, and/or publication of this article: The research for this article was provided by a ensure seamless exchange of data and the oper- European Research Council Advanced Investigator Award, ational consolidation of data-driven procedures. In ‘The Programmable City’ (ERC-2012-AdG-323636). addition to favouring a rationalised audit culture (Strathern, 2000), this will likely assist in future data- ORCID iD driven functionalities that integrate with other sectors Liam Heaphy https://orcid.org/0000-0003-1452-4369 and services. Urban datafication in transport has been charac- terised here as consisting of the three translations of data expansionism, data experimentalism and oper- Notes ational consolidation. It is tentatively argued, pending 1. A clear instance of technology-dependent automation is further comparative reviews of in-depth local studies, driverless underground trains in cities like Paris (Lines 1 that there will be an increasing tendency to curate and and 14), where the speed and intervals between trains are streamline data as the potentialities of Big Data shared tightly controlled through a central system and arrays of sensors and machinery. In this case, they become code/ across multiple domains are appreciated and realised. spaces (Kitchin and Dodge, 2011) in which software and Transport operators, particularly those serving massive space are mutually constitutive. urban populations, can use tracking technologies for 2. Service Interface for Real-time Information (SIRI) is a efficiency, commerce and security. Transport for European standard in the form of an extended mark-up London, for example, while maintaining their open language (XML) for distributing real-time transport data portal and subject to comprehensive UK and information developed by a partnership of European EU data protection and privacy regulations, are invest- transport bodies (see: http://www.transmodbku.kiljikil- ing in large-scale tracking technologies to inform their jik;/liilulel-cen.eu/standards/siri/, accessed 13 November services (McMullan, 2018; Sweeney, 2018). Transport 2018). VDV stands for the German Verband Deutscher data may be combined with social networks and public Verkehrsunternehmen (Association of German services profiles to perform new forms of citizenship as Transport Companies), who have created three timeta- bling standards. VDV452 is the main planned timetable, smartphone-delivered personalised notifications and while VDV453 is stop-centric, providing real-time services become normalised. Further research could updates per stop. VDV454 is route-centric, reflecting enquire as to the multiple data streams that are becom- scheduled times on a given route. ing operational, their epistemologies, and their primary 3. According to the SIRI documentation (https:// benefactors. For instance in China, transport apps for www.vdv.de/siri.aspx) and its implementation elsewhere, citizens are being tied to unique identifiers that may it would seem for the Estimated Timetable function in restrict or incentivise transport options according to SIRI, JourneyNote is by design indicated primarily, but their government-measured ‘social credits’ (Carney, by no means exclusively, for additional information such 2018). 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Data ratcheting and data-driven organisational change in transport:

Heaphy, Liam
Big Data & Society , Volume 6 (2): 1 – Aug 6, 2019
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Abstract

This article explores the process by which intelligent transport system technologies have further advanced a data- driven culture in public transport and traffic control. Based on 12 interviews with transport engineers and field- work visits to three control rooms, it follows the implementation of Real-Time Passenger Information in Dublin and the various technologies on which it is dependent. It uses the concept of ‘data ratcheting’ to describe how a new data- driven rational order supplants a gradualist, conservative ethos, creating technological dependencies that pressure organisations to take control of their own data and curate accessibility to outside organisations. It is argued that the implementation of Real-Time Passenger Information forms part of a changing landscape of urban technologies as cities move from a phase of opening data silos and expanded communication across departments and with citizens towards one in which new streams of digital data are recognised for their value in stabilising novel forms of city administration. Keywords Intelligent transport systems, real-time information, smart city, Big Data, organisational change ITS forms the basis for a longitudinal study on how Introduction data-driven organisational control is being enacted in There is a quiet ‘revolution’ underway in the transport our cities, drawing attention to the concept of ‘data- sector as intelligent transport systems (ITS) technolo- ratcheting’ to show how these data-driven changes are gies are used to increase efficiencies and integrate urban iterative and leveraged off previous innovations. The functions, through an alliance of well-established trans- evolution of ITS is dependent on long-standing com- port technology companies in partnership with city mitments to shared infrastructure, and indicative of a engineers and technologists. ITS originates in the con- shift to increasing autonomous management of public text of managing and coordinating road use, but inter- transport and traffic while overseen by human oper- faces with air, rail and water systems (Williams, 2008: ators. The article seeks to contribute to the theoretical 3). While discursively enveloped in the promise of the literature on standards and Big Data by building an smart city in recent marketing programmes such as that explanatory account of data-driven organisational of Dublin (Coletta et al., 2018a; Kitchin et al., 2018), change based on a case study on the deployment of the history of ITS extends back further over several Real-Time Passenger Information (henceforth RTPI) decades with the development of CCTV-supplied traffic in Dublin. It focuses primarily on the implementation control rooms, junction controller software, and sche- duling systems for public transport. Therefore, it pro- UCD School of Architecture, Planning and Environmental Policy, Dublin, vides a counter-example to the creation of new urban Ireland corporate districts branded as ‘smart’ (Wiig, 2019), or reductive concepts of a universal urban science Corresponding author: (Shelton, 2017), inasmuch as it accounts for a gradual Liam Heaphy, UCD School of Architecture, Planning and Environmental evolution of ‘smart’ or intelligent technologies within a Policy, Richview, Clonskeagh, Dublin 14, Ireland. specific sector. Email: liam.heaphy@ucd.ie Creative Commons CC-BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http:// www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 Big Data & Society of RTPI on bus services and considers the wide array of of the field of microbiology on particular visual and technologies on which RTPI is reliant, including loca- mechanical model kits. tional technologies, telecommunications and informa- The digital revolution has expanded the remit of tion standards. infrastructure studies. Star and Ruhleder’s (2001) sem- The following section reviews existing theory on data inal study on the creation of a unified, computer-based infrastructures in relation to its bearing for understand- and networked worm system for scientists examines the ing the deployment of new technologies. This is fol- frictions that occur around arcane choices of network- lowed by a description of the fieldwork and methods ing technologies or operating system, providing a useful underpinning the empirical content. The subsequent distinction between first-, second- and third-order three empirical sections then detail the deployment issues. First-order issues concern direct matter-of-fact of RTPI in Dublin, largely in temporal order and iden- phenomena and can be solved with existing resources tifying the various phases of development. This and processes, such as finding and enabling a software covers earlier trials, the negotiation of common infor- option. Second-order issues reflect unforeseen context- mation standards, forms of data-driven behavioural or ual effects, such as the choice of one suite of procedures procedural change, and the consolidation of oper- or standards over another and the path dependencies ational intelligence technologies. The penultimate sec- that result. Third-order issues are inherently political, tion further discusses data ratcheting in relation involving ethical frameworks, theoretical paradigms to procedural and organisational change. The conclu- and schools of thought. They may arise from combin- sion then discusses the evolution of data-driven ations of first- and second-order issues, such as where change in transport and speculates on further research an awareness emerges that legacy technologies are con- directions. straining accessibility, opening the path towards more fundamental questions on the collective good. Following Kitchin (2014a), we can associate the cen- Combining studies of the mundane with turies-old Big Data of climate science referred to above data assemblages with volume and variety. However, it is with ITS and The study of infrastructure has covered both epic trans- similar forms of sensor-fed, large-scale digital networks formations, such as the electrification of Western socie- and models that we can see the increasing importance ties (Hughes, 1993) and the mundane ‘boring things’ of velocity (i.e. real-time or close to it). ITS relies on (Star, 1999), such as the file folder system for comput- complex assemblages of information networks, human ing and its consequences for systems management engineers and controllers, transport policies, road-side (Yates, 1993). In the former, Hughes’ panoramic view sensors, in-vehicle computers and global positioning of large technical systems repurposes the military term systems to choreograph in real-time an increasingly ‘reverse salient’, pertaining to line formation, to define wide array of objects in space. It is part of a shift where blockages in one domain may be cleared by pro- towards data-driven design and maintenance of urban gress in another. Infrastructure becomes a means of transport systems, drawn into discourse on the ‘smart analysing how systems travel and extend into local con- city’ through including ‘smart travel’ or transport in texts, and a basis for forming concepts to explore their funding programmes and established practices of clas- many contingencies and the development of common sifying smart technologies (Giffinger and Pichler- standards of information exchange. Milanovic´ , 2007), as well as through the inroads into Infrastructure studies blend the archival patience of transport sought by data analytics companies. the historian with the attentive eye of the ethnographer Calls have been made to study actually existing and require a predilection for interrogating technical ‘smart cities’ (Coletta et al., 2018a; Shelton et al., reports and manuals. In this vein, Edwards (2010) 2015), and engage with software by analysing critically covers the pioneering work of climate observers in the how data interact with urban space and society 19th and 20th centuries and the process of reanalysis, (Kitchin and Dodge, 2011). This can take the form of where scientists reconcile data from multiple sources following the data and ‘attending to the sociotechnical into uniform global datasets. This large temporal fuzziness of data as it falls between epistemological scale opens up concepts such as ‘infrastructural inver- problems, material infrastructure and organizational sion’, where ‘historical changes frequently ascribed to concerns’ (Coletta et al., 2018b: 6). It implies looking to the ‘proxies’ of data, where data flows are trans- some spectacular product of an age are frequently more a feature of an infrastructure permitting the develop- formed, bifurcated, or collated; whether that be ment of that product’ (Star and Bowker, 2006: 233). It errors and anomalies in sensor networks and transport also facilitates the analysis of positive and negative systems (Reed, 2018; Reed and Webster, 2010), or externalities associated with standards, such as the rollout of sophisticated city-wide projects in Meinel’s historical study (2004) on the contingencies partnership with industry giants (Shapiro, 2018). Heaphy 3 Furthermore, it requires attention to the power rela- organisational technologies. A continual negotiation tions and values implied as these data are recruited and policing of standards is necessary to ensure data- into new modes of data-driven urban governance. driven processes can function to a required degree of Shelton (2017) shows how Big Data-inspired visual- resilience, for which the study of first-, second-, isations of vacant lots may depoliticise ethnic and social and third-order issues aid in our comprehension of inequalities, normalising the principles by which such how this occurs on different levels. Finally, the titu- inequalities are largely left in place. Consequently, it is lar concept of data ratcheting functions as a creative useful to account for the totality of politics, data, values interlacing of these final and overlapping phases as and materialities that underwrite such visualisations or new functions, products and services are discovered policy tools. Kitchin and Lauriault (2014: 1) advance and implemented in a context of data-driven the concept of a ‘data assemblage that encompasses all rationalisation. of the technological, political, social and economic The fieldwork introduced below corresponds to apparatuses and elements that constitutes and frames recent phases of data expansionism and operational the generation, circulation and deployment of data’. It consolidation. However, the implementation of RTPI functions as a means of expanding discussion to how in Dublin, particularly on bus services, evidences the data reshape society, and resultantly, how data-driven long infrastructural timelines of ITS. Therefore, the sec- change leads to further developments and the creation tion thereafter covers this initial period from the 1970s of new path dependencies. This aids in drawing atten- until the near-present, before then considering how tion to the politics of Big Data (Shelton, 2017), the RTPI standards were negotiated and how data-driven rights of citizens to the digital city (Foth et al., 2015), organisational change ensued. and data literacy (Gray et al., 2018). This article takes its cue from data assemblages as a Fieldwork and methods means of exploring how urban datafication reshapes urban management and control. Kitchin (2014b: 25) Dublin’s RTPI system covers Bus Atha Cliath (hence- pursues data assemblages in relation to how data can forth Dublin Bus), Bus Eireann (a public national usher in new regimes of data-driven societal control, coach company), Luas (tram system), and Iarnrod tabling a broad array of constituent factors. The fram- Eireann (the public national railway company). ing of RTPI as a data assemblage opens discussion into Dublin Bus registered 136.3 million journeys in 2017, how ‘each apparatus and their elements frame what is as compared to 37.6m for the Luas, and 45.5m for possible, desirable and expected of data’, including gov- Iarnro´dEireann nationwide (NTA, 2018: 201). The ernmentalities, materialities, practices and systems of focus of research reflects the operational area of thought. This article is particularly concerned with Dublin Bus, corresponding to the Greater Dublin procedure; how transport systems have integrated Area (GDA). The GDA comprises four predominantly data-driven technologies into their internal modes of urban local authorities with a combined population of organisation and coordination rather than their chan- 1,347,359 in the 2016 census and three surrounding ging relationship to passengers and broader society. rural counties. There is no corresponding transport Modern intelligent transport technologies, it is main- authority for the GDA. Instead, the national scale tained, represent an instance of urban datafication and tends to be the favoured tier for integrated services consolidation, as organisations experiment with Big across local authorities (Coletta et al., 2018a: 4). The Data in the interests of increased efficiency and per- National Transport Authority (NTA) is responsible for formance. This process of urban datafication can be both national and regional transport planning includ- described with recourse to three translations. Firstly, ing the GDA. data expansionism occurs through the deployment of The choice of the fieldwork site and the topic of sensing technologies and ICT infrastructure to create transport technology reflect a wider objective of track- new datasets. Concepts from infrastructural studies ing Dublin’s self-promotion as a ‘smart city’ as part of a such as ‘reverse salients’ help explain how data plat- large multi-researcher project. It forms one of several forms come into being as new technologies facilitate complementary case studies on how smart technologies change and transport authorities and providers build and Big Data are transforming urban life (cf. Cardullo necessary infrastructure. Secondly, as new data sources and Kitchin, 2018; Coletta et al., 2018a; Perng and become available, data experimentalism ensues as a Kitchin, 2016). The empirical research presented in range of actors compete to create new services and this article draws on 12 semi-structured interviews products. Finally, a third phase of operational consoli- derived from two related fieldwork datasets. The first dation can be delineated, as new forms of data-driven six are a subset are drawn from a larger set of 77 inter- behavioural change, based on the dynamic treatment of views conducted with government and city workers, real-time data, are encoded into procedures and corporations, and other stakeholders on Dublin’s 4 Big Data & Society emerging smart city strategy in 2015/2016. These radio-based triangulation systems to an acceptable include five transport engineers from local and national degree of accuracy and temporal resolution. It was government and one transport consultant, all of whom tested for select bus routes in urban areas throughout discuss ITS in relation to traffic control, road design the 1970s with varying degrees of success (Roth, 1977). and maintenance, and public transport reform. The For mass transport systems, AVM promised a more remaining six are part of subsequent in-depth studies efficient and less costly alternative to the ‘point men’, with transport operators (Bus Eireann, Dublin Bus, employed to record stop times of buses and inform Luas) and traffic control room engineers (Dublin City schedule adherence and redesign (Roth, 1977). These Council) on interrelated RTPI and traffic management elemental technologies of control contribute towards technologies in 2016/2017. tackling the perennial issues of buses running ahead Interviews were conducted in situ in back offices of schedule (understood to be considerably worse (NTA, Luas, Bus Eireann) and control rooms (Dublin than running behind, as it causes disruption to drivers Bus and the traffic control rooms of Dublin City further back down the line and frustration to patrons) Council and South Dublin County Council). and maintaining even headway (where buses are dis- Observational fieldnotes from visits to the control tributed evenly along the route). It was recognised in rooms and impromptu conservations with operators the late 1970s that AVM could be used to provide both provided additional perspectives. Interviewees were frequent and reliable service information to passengers asked to explain their roles, the deployment of RTPI and also integrate with traffic control systems to give in their organisation and its relationship to other tech- signal priority to oncoming public transport vehicles nologies, decisions on standards and their implementa- running behind schedule (Symes, 1980: 237). Dublin tion, and their coordination with other transport Bus first trialled AVM in the 1970s using odometers providers and regulators. The insights offered by par- fitted on buses that reported by radio to a central ticipants were supplemented by reports and secondary server every 45 seconds, subsequently rolled out to all literature to inform the longer timeline of ITS in bus depots by 1981. In 1985–1987, Dublin Bus also Dublin. trialled traffic prioritisation based on a combination of infrared transponders installed on buses and road- side detectors. This was linked to the AVM system, but Four decades of pilots in Dublin funding was not available to continue a successful pilot. In Dublin as elsewhere, the development of ITS can be The AVM system continued until the end of its useful seen to be dependent on a supporting infrastructure life in the 1990s but was not replaced, with controllers which allows innovation to occur over multi-decadal reverting to radio contact with drivers (World timescales. There were many instances of transport Bank, 2011). innovation over the last few decades, but without suf- In 2001, a second trial of next-generation GPS-based ficient coordination between the relevant bodies, they Automatic Vehicle Location (AVL) called ‘Q-time’ was failed to scale up or attract sufficient continuity support conducted on select Dublin Bus routes, and for the first from national or local government. time, RTPI signage was fitted (Caulfield and RTPI allows public transport users to consult the O’Mahony, 2004). This trial continued for three years predicted departure time of services and determine the during a period in which there was perennial threats (or most efficient mode of travel, based on the latest infor- opportunities) to liberalise the transport sector. The mation on traffic delays, interruptions and capacity. Irish Minister for Transport announced in 2002 that RTPI improves perceived reliability as passengers rate 25% of bus routes in the capital were to be opened to their transport providers more highly if they are kept private competition, while also proposing the develop- informed of how the system is performing and can ment of a ‘Dublin Land Use and Transport Authority’ make more sophisticated information-driven travel in line with best practice across the European Union decisions (Caulfield and O’Mahony, 2009; Watkins (Caulfield and O’Mahony, 2003: 2). Privatisation in et al., 2011). Although transport operators can fall transport is associated with market deficiencies includ- back on scheduled timetables and rosters to provide ing the dumping of non-profitable but socially basic transport infrastructure, the higher levels of ser- important routes, and fare-creep on monopolised vice attained with transport technologies are critically well-transited routes. Observing the UK experience, further inefficiencies may include competing companies dependent on software and automation. RTPI is dependent on automatic vehicle monitoring serving the same routes, multiple and incompatible (AVM), a technology which reports real-time informa- ticketing options, and the duplication of management tion on the location of vehicles back to a central server. and control resources (cf. Sørensen and Gudmundsson, AVM dates back to the late 1960s, with trials in the 2010). Privatisation is therefore often accompanied United States of America and other nations to develop with a parallel investment in new regulatory structures Heaphy 5 to mitigate these issues while proceeding on the ideo- was initiated] that Dublin City Council was a better logical basis of lowering public investment costs and vehicle to actually procure the RTPI and subsequently mitigating militant trade unionism (Gomez-Ibanez that project and contract moved over to the NTA’ and Meyer, 2011). (interview DSC27, NTA). The NTA have adopted the In this context of uncertainty and privatisation in the infrastructure created by Dublin City Council and early 2000s, Dublin Bus did not attain funding for a added further measures to ensure its resilience, while city-wide implementation of their Q-time pilot. also extending RTPI and the Leap smart travel card Therefore, by the time RTPI was finally funded and to other cities and towns in Ireland. implemented city-wide on buses from 2009 to 2011, it The AVL data from services are fed back into a was a mature and largely consolidated technology com- central RTPI server, and subsequently into roadside monplace in European cities like Gothenburg and display panels via cellular communication or GSM, Helsinki since the mid to late 1990s. Acting as a reverse with data hosted in two data centres in the Dublin salient, the arrival of GPS was making locational tech- Docklands with various failsafe mechanisms. This nologies part of everyday experience for both transport informs two official NTA apps (RealTime Ireland and operators and personal devices (Kitchin, 2014b: 58), Journey Planner) that cover all services, as well as sev- and could overcome technology resistances experienced eral operator apps (Iarnro´ dEireann and Luas). RTPI during the first 1980s generation of AVM. The first data are available via a public API to researchers and service-wide implementation of RTPI in Dublin was commercial developers under a CCBY 4.0 license. for a new tram service in 2004, Luas, run on a franchise Programmers can write their own queries in XML basis by Veolia, and before the bus implementation was (extended mark-up language) or JSON (JavaScript finalised. It shares road-space with private vehicles for object notation) to pull down specific information, which it gets priority when approaching junctions. which can then be pushed into custom-made displays Sensors are placed at intervals of 100m or more for specific purposes. which gather information from transponders on trams These developments have given rise to two forms of and send it to a central server and operations room. data expansionism: that within and between the core As evident in the timeline below (Figure 1), Dublin operators themselves and largely based on AVL, Bus had accumulated or retained experience with RTPI including scheduling, data analytics and traffic priori- tisation; and that permitted by the API, for research through successive trials by the time of its definitive roll-out of AVL, in partnership with a specialist and commercial usage. The next section details how German transport technology company, INIT. RTPI standards are managed between operators and A Dublin Transportation Office had been created in the regulator in order to support this two-tier ecosys- 1995 to put into place a transport strategy for the city tem, while the final empirical section considers how region under the remit of the Department of Transport. AVL and RTPI are supporting the operational consoli- It established a committee to oversee the implementa- dation of data-driven functionalities. tion of RTPI in 2001, and contracted Atkins consult- ants in 2002 to create a general strategy. The report, Negotiating and maintaining data published in 2006, noted the inconsistencies of informa- standards tion provision between services and the absence of an overarching mechanism to ensure holistic planning of It was the responsibility of Dublin City Council, and both physical and informational infrastructure. It then the NTA, to create consistency of information strongly recommended the creation of a specific provision, ensure infrastructure compatibility, and public transport information office ‘with responsibility develop a common brand with its accompanying clear for collecting data, publishing information and setting aesthetic. This involved the redesign of bus-stops, the standards’, ‘the development and marketing of a public rollout of RTPI displays for multiple operators, the transport ‘‘brand’’ common to all modes and operators creation of an efficient and reliable back-end and tele- that the public can identify with, trust and rely upon’, communications system, and the policing of informa- and ‘the development of a set of agreements and pro- tion systems to ensure interoperability between cesses governing agency participation’ (Atkins, 2006: iv). transport providers. This required a co-constitutive The mooted idea of a land use and transport authority development of procedures encompassing both human materialised in the form of the NTA, which fulfils the operators and software, where the latter is understood remit suggested in the report at the national scale. It also as partial or fully automated procedural systems. incorporated the Dublin Transportation Office and its Anomalies and breakdowns make infrastructure vis- data-modelling team (interview DSC27, NTA). ible (Star and Ruhleder, 2001), and their resolution As the NTA was not created until 2008, ‘it was allows us to follow how standards are negotiated and agreed at the time [that the implementation of RTPI stabilised. Such is the case with ‘ghost buses’, where 6 Big Data & Society 1 1978 AVM/L Automatic Vehicle Monitoring / Location DPT Dynamic Prioritisation of Traffic RTPI Real-Time Passenger Information Technology pilot Operational implementation Dublin's Traffic Management Centre opens 1987 SCATS deployed on junction controllers across Dublin Dublin Transport Office created 1995 Announcement of partial bus privatisation and 2001 idea of a "Dublin Land Use and Transport 2002 Authority" 2003 Atkins RTPI Report published 2006 Creation of National Transport Authority (incorporates the Dublin Transport Office) Leap smart card launched 2011 Dublinked data store launch with API for RTPI (all providers) Data.Gov.ie launched Privatisation of select routes begins 2016 BusConnects consultation (a new rationalisation 2018 of all Dublin Bus routes) Dublin Bus Luas (tram) Bus Éireann Figure 1. A timeline of RTPI-related transport technology deployments in Dublin for bus and tram services, with further events on the left. IarnrodEireann is not included, which relies on its legacy signalling systems in addition to AVL. services shown in RTPI fail to materialise. This anom- their anglicised counterparts, e.g. Cluain Saileach (a aly provides insight into the various orders of issues meadow of willows) and ‘Clonsilla’. The ghost bus encountered and their relationship to organisational anomaly resulted from a series of actions starting change as the NTA exercised its authority over trans- with Dublin Bus curtailing a bus and redirecting it port operators. There are many reasons for ghost buses, before meeting its scheduled destination. Of the two one of which was due to communication failures information standards used by transport organisations between operators as discussed below and resolved by in Ireland, VDV452 is used for scheduled timetables early 2016. Its elimination and that of other issues that and SIRI for real-time feeds. Dublin Bus changed a affected accuracy involved both repairing bugs and 19-character field in SIRI called ‘DestinationRef’ in a policing adherence to standards. For 2017, it was way that partners did not expect, as the employee cited reported that 97.5% of RTPI information was correct below explains, because it did not have enough space with reference to arriving within 1 minute of the ‘Due’ for both languages, necessitating the use of a further prediction (Bus Atha Cliath, 2017), up from 92% in field called ‘JourneyNote’: 2012 (Worrall, 2012) and 89% when initially launched. In agreement with language policies for State bodies, For example, we send the journey ref [which] would RTPI information, including destination information, say, ‘Okay, this journey is doing this destination and on trains, buses, and trams, is displayed and announced now that destination has changed’. So say, for example, in both English and Irish. The original versions of a trip is going from A to B and we decide, okay, it is not many Irish place names now share equal space with going to B anymore, we’ll bring it back somewhere. AVL AVL AVM RTPI RTPI DPT Data-driven scheduling DPT DPT AVL RTPI AVL RTPI Heaphy 7 Figure 2. Dublin bus live monitoring of schedule adherence in their control room. Now it can’t handle that at the moment, the new des- corresponding real-world names in various languages tination, it still tells passengers you are going all the in adjacent columns: way to B. They are working on it and they are almost there. We had the same problem with the street signs Yes, and largely that works fine if you don’t go putting for quite some time but they worked on that and they stuff in places where it shouldn’t be, like journey notes were fixed [by their external contractor] and that got shouldn’t be in there. So the system trying to under- resolved, that got changed. So now for example if you stand that doesn’t see it and therefore these, I suppose are going to Maynooth on a 66 [bus] for example, and important things, because curtailments and cancella- for whatever reason, operational or whatever, they tions are really what you need to know about in real- decide, okay this bus can’t go the full journey, it can time. You need to know if your bus is not going to the only go as far as Leixlip. We can now tell on the street destination or if it has been cancelled. So they are signs, we can tell on our app on our website that to the things we can fix but they are expensive because what passengers straight away, it could be on the bus itself, you will find is that an incumbent will see that as an on the displays, they can be told this bus is now finish- opportunity to, let’s say, know that nobody is going to ing in Leixlip. Whereas on the NTA’s app they are still compete with their price and therefore I would say give telling you ‘Maynooth’. So it will be fixed quite soon, in ridiculously high prices to do fairly simple stuff. [.. .] they have been working on it for a number of months And so really our experience is to kick back and say, now so it should be fixed soon. But on the street signs ‘Sorry, guys’, right at the very start, stick to the speci- and our web that is reflected correctly. But that is kind fications. [.. .] So over the years the system has been in of a bug thing, that isn’t anything to do with the stand- place and more people want to build ancillary systems ards really, that is more a bug on their internal system or reuse the information, the more we have learned that than anything. It is no limitation of SIRI or the VDV right at the start you need to be the policeman. that has caused that. (Interview RTPI01, Dublin Bus) (Interview SD13, NTA) Dublin Bus considered that their usage was consistent The central regulator talks of their role of policing with SIRI and that the issue reflected an external con- common standards to ensure fair competition between tractor’s inability to read this information. In contrast, providers through shared rather than privileged infor- the NTA interviewee cited below indicated mation. It has weekly meetings with RTPI representa- ‘JourneyNote’ as being more for minor notes like tives from the main transport providers during which being ‘guide dog-friendly’. This alleged non-standard anomalies and their potential solutions are discussed. use broke the information feed downstream, even if While assertive about its policing role, a solution was the change suited the challenge of frequently curtailing negotiated that allowed Dublin Bus a degree of flexibil- buses due to the large but necessary interruptions ity in their implementation of SIRI, creating custom caused by Luas cross city. code to recognise Dublin Bus curtailments. The A common solution for multiple language provision changes were visible first on the street signs, and is to use a generic code in a look-up table with reflected later on the NTA smartphone app. 8 Big Data & Society This second-order issue on adherence to common at cubicles equipped with several graphical user inter- standards reflects a transition from putting in place faces for monitoring buses in real-time. the basic infrastructure towards consolidating RTPI Much the same as the recording devices affixed to in a new suite of procedures and processes, yet also chain retail workers, these technologies constrain interacts with higher third-order reconfigurations of employee behaviour in order to provide an experience power relations as the regulator imposes a new perfor- to customers that is invariable and therefore negotiable mance-driven ethos on operators. As the transport with less cognitive effort. Dublin Bus is a public com- franchise-holder, the NTA has the power to outsource pany and many of the staff in the control room are ex- routes to other suppliers, oversees performance man- drivers themselves, their exchanges with drivers replete agement for all contracted transport providers, and is with banter and laughter yet nevertheless effecting a therefore at the heart of negotiations on privatisation culture change within the organisation: and standardisation. During the time of fieldwork, there were industrial disputes involving Luas tram dri- [B]efore the AVL system, the only way of knowing vers, and protracted discussions on the costs and bene- where a bus was, unless there was a guy out on the fits of partial privatisation of national services targeting street watching the buses coming in and the inspector Dublin Bus and Bus Eireann. Over the course of 2016 on the road. Or else it was the control up above calling to 2018, 24 routes from Dublin Bus and 6 routes from the driver and saying, ‘Where are you?’ And now it is a Bus Eireann were listed for privatisation (Tallaght case of ... It was funny at first seeing it happen because News, 2017) with UK firm Go-Ahead winning both they’d be saying I am in such and such a street. And the competitions. The NTA manages routes, schedules, controller would say, ‘No you are not. I can see within fares, vehicles, quality control and RTPI for new pro- 20 seconds of where you are’. That took a bit of getting viders. In this manner, it hopes that like with Transport used to and now the drivers are at the point where they for London, tenders for routes are largely inconsequen- are embracing it very much so. It took a while for them tial for passengers through a model of competition for to trust it. [.. .] But yeah, they have taken it on board the market rather than in the market (Preston and now and they do realise all the old ways of operating Almutairi, 2013). have to change. (Interview RTPI01, Dublin Bus) Operational consolidation here was the prerogative of an increasingly assertive state actor, the NTA, which The interviewee above notes the role of AVL in sup- addressed administrative fractures between State com- porting measures to improve quality of service. They panies through control over both markets and data. are enforced not only by control room operators, on This facet of data ratcheting comprises data- whose terminal screens buses are highlighted in red for driven organisational control over operators and being behind or ahead of schedule (see Figure 2), but requires collective adherence to data policies. At the also on vehicles themselves through devices to notify intra-organisational scale, within Dublin Bus and Bus drivers if they are running ahead of their scheduled Eireann, real-time data on the location of vehicles stops via a beep and a red dashboard light (only and drivers also enabled data-driven organisational when the vehicle is stationary). Together with the con- control, in part based on new data-driven functional- trol room and its real-time displays, data analytics, and ities. This ratcheting provides momentum to the a management team with key performance indicators to cycle of expansionism, experimentalism and consolida- meet, these technologies all coerce human behaviour tion as new datasets are created and further use- towards minimising error and irregularities. A realisa- cases found. tion of the potential of data to drive internal reform has led to further local innovations, including using data analytics packages to recalibrate schedules (timetables) Data-driven procedural change and data based on statistically examined journey times, and ratcheting developing new internal performance metrics for man- AVM and RTPI technologies in Dublin have given rise agement. These measures further improve RTPI accur- to a cascade of data-driven organisational changes. In acy, and evidence how data ratcheting reshapes internal many instances, these are local learnings of established organisational control as engineers experiment with, international best-practices, yet also include instances and operationalise, new functionalities. of innovation such as the many small data-driven In addition to schedule and route alterations, further changes to routes to reach industry-standard RTPI interventions in the interest of efficiency can be either accuracy. Dublin Bus’s schedule management software physical, such as changes to the road layout, or digital, is reliant on AVL and creates a more constant and through alterations to the junction signalisation pat- intimate connection between drivers and controllers. terns of traffic lights. The greater part of Dublin’s The latter are housed in a control centre and seated road network is managed with industry-standard Heaphy 9 software (SCATS) that alters junctions dynamically in we were collecting and providing. But certainly we have response to traffic by swapping between pre- realised now that we have a huge wealth of information programmed plans. Traffic prioritisation has now at our disposal in terms of where buses are at, the been rolled across the SCATS network for public trans- best journey patterns being used, and we can analyse port by using RTPI data in SIRI format to estimate that now and start using that to make the planning proximity (O’Donnell et al., 2018). This belated but decisions more effective going forward. (Interview eventually successful deployment of traffic prioritisa- DSC27, NTA) tion (see Figure 1) relates to third-order issues sur- rounding the dominant trend of transitioning to a The expansion of metrics and accountability reinforces low-carbon future by progressively revoking privileges an ‘audit culture’ (Strathern, 2000), dependent on tech- once handed out willingly to the private motorist and nologies that ostensibly serve passenger service provi- increasing investment into public transport. sion but which also expand into technologies of control The schedule and fleet management software, the and regulation. Data ratcheting represents a quasi- data analytics functions for route optimisation, and Lamarckian evolutionary progression as organisations automated bus prioritisation form part of an estab- create ever more sophisticated secondary products from lished practice of ratcheting the recognised power of high-quality data, recognising its power and curating it data to redefine procedures, and by extension, urban with discretion according to socio-cultural specificities flows and spatial relations. Data-driven functionalities and legal frameworks. On the one hand, this may become perceived as integral during this phase of effi- involve preventing such data from being misused for ciency and rationalisation. A Dublin Bus technician criminal purposes, while on the other, it could be notes that data are ‘growing more and more into deci- used to maintain competitive advantage or increase sion-making around the company’ and adds: control over consumers or citizens. The empirical data presented here account for largely internal and So it is a complete [change of] mind-set, everything has inter-organisational data-driven innovations yet may changed. Once you trust in the data better decisions can eventually lead to broader data assemblages beyond be made [.. .]. the transport sector, aligning with broader commercial It was unbelievable straight away, things like when a or political interests. door opened, you could see straight away, just infor- mation that you just couldn’t have before so straight Conclusion away you were just giving the power to the managers to see exactly what was going on, the routes, and ultim- In their future roadmap of ubiquitous computing, ately that is getting back to the customers. (Interview Dourish and Bell (2011) highlight the emergent nature RTPI04, Dublin Bus) of technologies, which initially developed separately, coalesce in what are seen retrospectively as unitary sys- This localised data experimentalism and consolidation tems such as the smart home or the city dashboard occur alongside larger-scale operational changes as cen- (Kitchin et al., 2016). Technological changes are also tralised authorities coordinate transport services and essentially organisational and procedural, liberating the data, creating new products and services to consolidate human mind from repetitive drudgery, and facilitating those initially created by individual transport providers. new forms of behaviour between people and their inter- This includes the present BusConnects programme, action with the environment. Tracing their evolutionary initiated in 2017 and led by the NTA, for the rational- development reveals the multiple path dependencies isation of all bus services in Dublin. Two NTA partici- and reverse salients (Hughes, 1993) that characterise pants below recognise the potential of data for better their real-world implementation, and furthermore illus- strategic planning: trates the value of blending the historicism of infra- structure studies with the study of data assemblages. So I think once you have the kit with proper manage- The rollout of RTPI in Dublin is interrelated with ment and working between different companies you can broader transport technologies including automated make these improvements to raise the reliability and the vehicle location systems and traffic control systems, perception of reliability to people. So I see expanding and evidences how its local implementation is part of the system but also harvesting it to offer better prod- an arc of technological changes in ITS. It initiates in the ucts. (Interview SD13, NTA) 1970s with advanced trials that were inconsistently Yes, we use the data for a number of purposes. The resourced by the State until the context itself had initial objective was to provide more information to the shifted. The national economy had moved towards consumers to actually make transport more accessible; higher-value technologies and services with a more that is the real value we saw from the information that informed and demanding workforce, necessitating the 10 Big Data & Society provision of seamless multimodal transport, integrated cultural contexts, as well as from the extended time- ticketing, and RTPI. scales of infrastructure development and attention to The deployment of RTPI allowed individual oper- glitches and breakdowns. ators such as Dublin Bus to experiment with and drive their own internal procedural reforms, with instances of Acknowledgements both localised learnings and more genuine innovations I am indebted to Professor Rob Kitchin for his very helpful as local actors participated in European and inter- feedback and input into this article and research, which formed national networks for developing and disseminating part of a larger research project on the smart city for which he best practices. These activities are described here as was principle investigator. My thanks also to Dr Sheila Convery for her comments on the article, and to the editorial instances of data ratcheting, as new data-driven func- team and three anonymous reviewers for their comments. tionalities are implemented iteratively as they are dis- covered in a local context, oriented towards a more Declaration of conflicting interests rationalised data-driven culture. Glitches such as ‘ghost buses’ provide a window into the politics of The author(s) declared no potential conflicts of interest with data, as the transport sector modernised and the respect to the research, authorship, and/or publication of this article. NTA consolidated its mandate to improve passenger experience by policing standards and controlling pro- Funding viders. This hierarchy of procedural authority, from regulator to operator to driver, has been strengthened The author(s) disclosed receipt of the following financial sup- through the creation of governmental bodies that port for the research, authorship, and/or publication of this article: The research for this article was provided by a ensure seamless exchange of data and the oper- European Research Council Advanced Investigator Award, ational consolidation of data-driven procedures. In ‘The Programmable City’ (ERC-2012-AdG-323636). addition to favouring a rationalised audit culture (Strathern, 2000), this will likely assist in future data- ORCID iD driven functionalities that integrate with other sectors Liam Heaphy https://orcid.org/0000-0003-1452-4369 and services. Urban datafication in transport has been charac- terised here as consisting of the three translations of data expansionism, data experimentalism and oper- Notes ational consolidation. It is tentatively argued, pending 1. A clear instance of technology-dependent automation is further comparative reviews of in-depth local studies, driverless underground trains in cities like Paris (Lines 1 that there will be an increasing tendency to curate and and 14), where the speed and intervals between trains are streamline data as the potentialities of Big Data shared tightly controlled through a central system and arrays of sensors and machinery. In this case, they become code/ across multiple domains are appreciated and realised. spaces (Kitchin and Dodge, 2011) in which software and Transport operators, particularly those serving massive space are mutually constitutive. urban populations, can use tracking technologies for 2. Service Interface for Real-time Information (SIRI) is a efficiency, commerce and security. Transport for European standard in the form of an extended mark-up London, for example, while maintaining their open language (XML) for distributing real-time transport data portal and subject to comprehensive UK and information developed by a partnership of European EU data protection and privacy regulations, are invest- transport bodies (see: http://www.transmodbku.kiljikil- ing in large-scale tracking technologies to inform their jik;/liilulel-cen.eu/standards/siri/, accessed 13 November services (McMullan, 2018; Sweeney, 2018). Transport 2018). VDV stands for the German Verband Deutscher data may be combined with social networks and public Verkehrsunternehmen (Association of German services profiles to perform new forms of citizenship as Transport Companies), who have created three timeta- bling standards. VDV452 is the main planned timetable, smartphone-delivered personalised notifications and while VDV453 is stop-centric, providing real-time services become normalised. Further research could updates per stop. VDV454 is route-centric, reflecting enquire as to the multiple data streams that are becom- scheduled times on a given route. ing operational, their epistemologies, and their primary 3. According to the SIRI documentation (https:// benefactors. For instance in China, transport apps for www.vdv.de/siri.aspx) and its implementation elsewhere, citizens are being tied to unique identifiers that may it would seem for the Estimated Timetable function in restrict or incentivise transport options according to SIRI, JourneyNote is by design indicated primarily, but their government-measured ‘social credits’ (Carney, by no means exclusively, for additional information such 2018). 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Journal

Big Data & Society – SAGE

Published: Aug 6, 2019

Keywords: Intelligent transport systems; real-time information; smart city; Big Data; organisational change

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