This is a preprint of the article: L. Candela, D. Castelli, P. Manghi, A. Tani Data Journals: A Survey. Journal of the Association for Information and Science Technology. Accepted for publication in June 2014. Will appear with DOI: 10.1002/asi.23358 ----- Data Journals: A Survey Leonardo Candela, Donatella Castelli, Paolo Manghi, and Alice Tani Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo”, Italian National Research Council, via G. Moruzzi, 1, 56124, Pisa, Italy. E‐mail: {candela, castelli, manghi, tani}@isti.cnr.it 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 datasets description, availability, citation, quality and open access. We close by identifying ways to expand and strengthen the data journals approach as a means to actually promote datasets access and exploitation. Introduction Data – that serving “Big Science” as well as that serving “Long‐tail Science” (Murray‐Rust, 2008) – is emerging as a driving instrument in science. Benefitting from data availability researchers are envisaging a large variety of new research patterns that are revolutionizing how science is being conducted. The full realization of this paradigm shift, however, requires addressing many onerous and challenging issues (Bell, Hey, & Szalay, 2009; Hey, Tansley, & Tolle, 2009; Halevi & Moed, 2012). Although there is an almost universal agreement on the benefits of “data sharing and re‐use” as a means to accelerate science performance, there are a number of barriers hindering the realization of this objective in a systematic and effective way (Borgman, 2011; Tenopir et al., 2011; Pampel & Dallmeier‐Tiessen, 2014). These barriers are methodological, legal, technical, and often related to the lack of incentives for researchers to share their data (Douglass, Allard, Tenopir, Wu, & Frame, 2014; Asher et al., 2013; Bourne et al., 2012; Bourne, 2010). The effects of these obstacles on science is deleterious, e.g., Vines et al. (2014) demonstrates how the availability of research data was strongly affected by article’s age when no policy is in place. Thus, proper data sharing practices and policies must be introduced to foster the data availability. Moreover, mechanisms must be identified to make the scientific community aware of the available data sets, to facilitate their understanding and to foster their effective re‐use. In this changing landscape Data Journals have been proposed as first step solution to some of the above discussed barriers. They realize the “data publication” concept by mirroring the scientific publication model. They promote the publication of data papers, “scholarly publication of a searchable metadata document describing a particular on‐line accessible dataset, or a group of datasets, published in accordance to the standard academic practices” (Chavan & Penev, 2011). Their final aim being to provide “information on the what, where, why, how and who of the data” (Callaghan et al., 2012). Thus data publication is a pre‐requisite to enable data sharing and reuse. Despite their potentiality, data journals are not the ultimate and complete solution for all the data sharing and reuse issues and, in some cases, they are considered to induce false expectations in the research community (Parsons & Fox, 2013). In this survey we review current data journals to discuss the different approaches put in place to overcome the data sharing barriers. In particular, the rest of the survey is structured as follows. The rationale, motivations and initiatives leading to data journals are described. Then a survey of over 100 data journals is discussed by comparing their approaches to data papers concept implementation including how to properly describe a dataset, how to promote datasets availability, how to properly cite a dataset and guarantee rewards, how to guarantee dataset quality, and how to guarantee open access to dataset. The paper ends by giving some suggestions aiming at enhancing the role of data journals as a true data sharing means.