期刊名称：DATA TECHNOLOGIES AND APPLICATIONS
 期刊简介(About the journal)
投稿须知(Instructions to Authors)
编辑部信息(Editorial Board)
About the journal
Journal history
Previously published as Program
Follow the Table of Contents link above for previous content.
This journal received a 2017 CiteScore of 1.30, under its former name Program. The 2017 CiteScore is calculated using articles published between 2014 and 2016. Click here for more details. The Journal will receive its first CiteScore as Data Technologies and Applications for 2018 (NB this will be calculated in 2019).
It received a 2017 Impact Factor of 1.170, also under the former name Program. The 2017 Impact Factor is calculated using articles published between 2015 and 2016.
Aims & Scope
Data Technologies and Applications (DTA) is a scholarly refereed journal which, since its inception in 1966 focused on the management of digital information, mostly covering Information Science and Information System aspects. From 2013, the journal started to shift its focus to cover all aspects of the data revolution brought about by the Internet and the World-Wide-Web.
Data Technologies and Applications 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 Data Technologies and Applications covers also novel computational techniques when they are of an applied nature and include relevant empirical evaluation.
Data Technologies and Applications 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.
Data Technologies and Applications is indexed and abstracted in:
- Academic Search Alumni Edition;
- Academic Search Complete;
- Academic Search Premier;
- CompuMath Citation Index®;
- Current Abstracts;
- Current Contents®/Social and Behavioral Sciences;
- Education Full Text;
- Information Science and Technology Abstracts (ISTA);
- INSPEC;
- Library and Information Science Abstracts (LISA);
- Library Literature & Information Science;
- Library Literature and Information Science Full Text;
- Library, Information Science and Technology Abstracts;
- Norwegian Scientific Index
- OmniFile Full Text Mega;
- OmniFile Full Text Select;
- Scopus;
- The Informed Librarian;
- Social Sciences Citation Index® (SSCI)
This journal is ranked by:
BFI (Denmark), Clarivate Analytics Journal Citation Reports, Computing Research & Education (CORE) Journal Ranking (C), The Publication Forum (Finland), Social Sciences Citation Index® (SSCI), Scopus
 Media Partner
Data Technologies and Applications is a media partner with ODBMS.org - The Resource Portal for Big Data, New Data Management Technologies and Data Science.
Emerald is not responsible for the content of third party sites.
Data Technologies and Applications is available as part of an online subscription to the Emerald Library Studies eJournals Collection. For more information, please email collections@emeraldinsight.com or visit the Emerald Library Studies eJournals Collection page.
This journal is a member of and subscribes to the principles of the Committee on Publication Ethics. More on Emerald's approach is available in our Publication Ethics guidelines.
Instructions to Authors
Quick index
- Submit to the journal
- Review process
- Copyright
- Third party copyright permissions
- Committee on Publication Ethics (COPE)
- Copyright forms
- Editorial Services
- Transparency and Openness Promotion (TOP) Guidelines
- Final submission
- Open access submissions and information
- Frequently asked questions
Manuscript requirements
Editorial Board
Editor
Dr Miguel-Angel Sicilia
Professor, Computer Science Department, University of Alcalá, Spain
msicilia@uah.es
Editorial Assistant
Ms Effie Tsiflidou
Librarian Expert, Agro-Know Technologies, Greece
effie@agroknow.gr
Associate Editors
Dr Wen-Yu Chiang
Associate Professor, Department of Air Transportation Management, Aletheia University, Taiwan
ianc8866@gmail.com
Dr Frances Johnson
Senior Lecturer, Manchester Metropolitan University, UK
F.Johnson@mmu.ac.uk
Dr Zoe Lacroix
Arizona State University, USA
zlacroi@asu.edu
Dr Fabio Sartori
Department of Informatics, Systems and Communication, University of Milano-Bicocca, Italy
sartori@disco.unimib.it
Topic Area Editor - Open and social data: data sharing
Dr Emmanouel Garoufallou
Assistant Professor, Alexander Technological Educational Inst of Thessaloniki, Greece
mgarou@libd.teithe.gr
Topic Area Editor - Semantic data: computational semantics and interoperability
Assoc Prof Robert Trypuz
Associate Professor, John Paul II Catholic University of Lublin, Poland
robert.trypuz@makolab.com
Topic Area Editor - Big data: scale and analytics
Professor Roberto V. Zicari
Institute of Computer Science, Goethe University Frankfurt, Germany
zicari@ dbis.cs.uni-frankfurt.de
Publisher
Eileen Breen
ebreen@emeraldgroup.com
Content Editor
James Whiteley
jwhiteley@emeraldgroup.com
Editorial Advisory Board
Alessia Amelio
Research Fellow in computer science, DIMES University of Calabria, Italy
Matthew Eric Bassett
Executive Director & Co-founder, Gower Street Analytics, UK
Piotr Bródka
Wroclaw University of Technology, Poland
Andrew Cox
Lecturer, Department of Information Studies, University of Sheffield, UK
Alfio Ferrara
University of Milan, Italy
Alok Mishra
Department of Software Engineering, Atilim University, Turkey
Mr Johnson Paul
Deputy Director, Information Services, National Library Board, and Chief Networking Officer, CONSAL, Singapore
Marco Pennacchiotti
eBbay, USA
Elena Simperl
University of Southampton, UK
Dusan Vudragovic
Institute of Physics Belgrade, Serbia
Cecilia Zanni-Merk
Professor in Computer Science, INSA Rouen Normandie, France
Jianfeng Zhan
Chinese Academy of Sciences and University of Chinese Academy of Sciences, People's Republic of China
Maja Zumer
Professor, Department of Library and Information Science and Book Studies, Faculty of Arts, University of Ljubljana, Slovenia
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