Purpose – XML has spread beyond the computer science fields and reached other areas such as, e‐commerce, identification, information storage, instant messaging and others. Data communicated over these domains are now mainly based on XML. Thus, allowing non‐expert programmers to manipulate and control their XML data is essential. The purpose of this paper is to present an XA2C framework intended for both non‐expert and expert programmers and provide them with means to write/draw their XML data manipulation operations. Design/methodology/approach – In the literature, this issue has been dealt with from two perspectives: first, XML alteration/adaptation techniques requiring a certain level of expertise to be implemented and are not unified yet; and second, Mashups, which are not formally defined yet and are not specific to XML data, and XML‐oriented visual languages are based on structural transformations and data extraction mainly and do not allow XML textual data manipulations. The paper discusses existing approaches and the XA2C framework is presented. Findings – The framework is defined based on the dataflow paradigm (visual diagram compositions) while taking advantage of both Mashups and XML‐oriented visual languages by defining a well‐founded modular architecture and an XML‐oriented visual functional composition language based on colored petri nets allowing functional compositions. The framework takes advantage of existing XML alteration/adaptation techniques by defining them as XML‐oriented manipulation functions. A prototype called XA2C is developed and presented here for testing and validating the authors' approach. Originality/value – This paper presents a detailed description of an XML‐oriented manipulation framework implementing the XML‐oriented composition definition language.
International Journal of Web Information Systems – Emerald Publishing
Published: Aug 30, 2011
Keywords: Visual languages; Colored petri nets; Composition; XML data manipulation; Concurrency; Extensible markup language; Programming and algorithm theory
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera