Data Technologies and Applications

Aims & 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.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.5
2024	1.70

SJR (SCImago Journal Rank)

Year	Value
2024	0.540

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	37

Journal Rank

Year	Value
2024	10770

Journal Citation Indicator

Year	Value
2024	368

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Social Sciences, designed to support cutting-edge academic discovery.

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Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• M-banking barriers in Pakistan: a customer perspective of adoption and continuity intention

  Citation: 54

  Authors: Abdul Waheed, Donghong, Saeed

• A systematic review of machine learning-based missing value imputation techniques

  Citation: 52

  Authors: Tressy, Enayat

• An analysis of academic librarians competencies and skills for implementation of Big Data analytics in libraries

  Citation: 44

  Authors: Khurshid, Zheng, Muhammad

• A survey on mining stack overflow: question and answering (Q&A) community

  Citation: 42

  Authors: Arshad, Chong, Shi, Abdallah

• The role of negative network externalities in SNS fatigue

  Citation: 41

  Authors: Yun, Zheshi

• A systematic literature review on Wikidata

  Citation: 34

  Authors: Marçal, Salvador, Elena

• Domain-specific word embeddings for patent classification

  Citation: 33

  Authors: Julian, Ralf

• A multi-objective approach to determining the usefulness of papers in academic search

  Citation: 31

  Authors: Shah, Shengli, Fang

• Social network fatigue affecting continuance intention of social networking services

  Citation: 29

  Authors: Wen, Jing, Zheshi

• Data science from a library and information science perspective

  Citation: 29

  Authors: Sirje, Emmanouel

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