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Data Technologies and Applications focusses on the management of digital information, mostly covering Information Science and Information System aspects. Covers all aspects of the data revolution brought about by the Internet and the World-Wide-Web.

ISSN: 2514-9288
eISSN: 2514-9318

Aims and scope

This is now an inter-disciplinary journal with broader coverage. It continues to cover Computing and Information Science, but now also the Social Sciences in general and any other discipline that is concerned with digital data. In all cases, research papers should include relevant evaluation or empirical content. Surveys on important emerging topics are also sought, whenever they follow a rigorous and systematic approach to review the literature and a sound and insightful analysis of promising avenues for research. Previous related surveys or reviews need to be properly discussed, and they have to be comprehensive, detailed and insightful.

DTA also welcomes 'Short communications' as well as research articles. These are shorter papers addressing new ideas that bring new perspectives to a topic, controversial views of established issues, negative results or new empirical insights, with a typical paper length of 3,000-5,000 words. This category is intended for new areas of research or new perspectives that do not fit well in the category of full research papers.

There are no limitations on the approaches to selecting data analysis or research methods. These may include experimental designs, longitudinal studies, social network analysis, statistical profiling and measurement against benchmarks to name a few. Qualitative methods are acceptable whenever properly justified and having a strong analysis design. The scope of DTA covers also novel computational techniques when they are of an applied nature and include relevant empirical evaluation.

DTA covers any topic related to Web Science, data analytics and digital information management.

Relevant topics include but are not limited to the following:

  • Studies on information creation or use of Web information including collaboration (e.g. Wikis) social media or other.
  • Sharing of data using the Web of Data/Linked Data approach.
  • E-science and data science.
  • Semantic Web and intelligent techniques exploiting digital information on the Web.
  • Dealing with large volumes of data with novel processing techniques.
  • Studies on the structure of social networks and social platforms.
  • Information behaviour of users in the Web, including social platforms, games and any other kind of interaction place.
  • Empirical analysis of on-line communities.
  • Classification and recommendation approaches for digital information of any kind.
  • Analytics and business analytics.

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