Data Journals: A Survey - Tables

Datacite citation style:
Leonardo Candela; Donatella Castelli; Paolo Manghi; Alice Tani (2014): Data Journals: A Survey - Tables. Version 1. 4TU.ResearchData. dataset.
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
This dataset groups all the tables supplementing the contents of the article "Data Journals: A Survey", which is going to be published by the Journal of the Association for Information Science and Technology (JASIST). Tables are published with no header. Any details can be found in the article. Abstract Data occupy a key role in our information society. However, although the amount of published data continues to grow and terms like “data deluge” and “big data” today characterize numerous (research) initiatives, a lot of work is still needed in the direction of publishing data in order to make them effectively discoverable, available, and reusable by others. Several barriers hinder data publishing, from lack of attribution and rewards, vague citation practices, quality issues, to a rather general lack of data sharing culture. Lately, data journals came forward as a solution to overcome some of these barriers. In this study of more than 100 currently existing data journals, we describe the approaches they promote for description, availability, citation, quality and open access or datasets. We close by identifying ways to expand and strengthen the data journals approach as a means to actually promote datasets access and exploitation.
  • 2014-06-18 first online, published, posted
media types: application/zip, text/plain


files (1)