Purpose Open data and data sharing should improve transparency of research. The purpose of this paper is to investigate how different institutional and individual factors affect the data sharing behavior of authors of research articles in sociology and political science. Design/methodology/approach Desktop research analyzed attributes of sociology and political science journals (n=262) from their websites. A second data set of articles (n=1,011; published 2012-2014) was derived from ten of the main journals (five from each discipline) and stated data sharing was examined. A survey of the authors used the Theory of Planned Behavior to examine motivations, behavioral control, and perceived norms for sharing data. Statistical tests (Spearman’s ρ, χ2) examined correlations and associations. Findings Although many journals have a data policy for their authors (78 percent in sociology, 44 percent in political science), only around half of the empirical articles stated that the data were available, and for only 37 percent of the articles could the data be accessed. Journals with higher impact factors, those with a stated data policy, and younger journals were more likely to offer data availability. Of the authors surveyed, 446 responded (44 percent). Statistical analysis indicated that authors’ attitudes, reported past behavior, social norms, and perceived behavioral control affected their intentions to share data. Research limitations/implications Less than 50 percent of the authors contacted provided responses to the survey. Results indicate that data sharing would improve if journals had explicit data sharing policies but authors also need support from other institutions (their universities, funding councils, and professional associations) to improve data management skills and infrastructures. Originality/value This paper builds on previous similar research in sociology and political science and explains some of the barriers to data sharing in social sciences by combining journal policies, published articles, and authors’ responses to a survey.

Sharing social media research datasets allows for reproducibility and peer-review, but it is very often difficult or even impossible to achieve due to legal restrictions and can also be ethically questionable. What is more, research data repositories and other research infrastructure and research support institutions are only starting to target social media researchers. In this paper, we present a practical solution to sharing social media data with the help of a social science data archive. Our aim is to contribute to the effort of enhancing comparability and reproducibility in social media research by taking some first steps towards setting standards for sustainable data archiving. We present a showcase for sharing social media data with the example of a big dataset containing geotagged tweets (several months of continued geotagged tweets from the United States from 2014 and 2015; nearly half a billion tweets in total) through a research data archive. We provide a general background to the process of long-term archiving of research data. After some consideration of the current obstacles for sharing and archiving social media data, we present our solution of archiving the specific dataset of geotagged tweets at the GESIS Data Archive for the Social Sciences, a publicly funded German data archive for secure and long-term archiving of social science data. We archived and documented tweet IDs and additional information to improve reproducibility of the initial research while also attending to ethical and legal considerations, and taking into account Twitter's terms of service in particular.

Purpose – Data sharing is key for replication and re-use in empirical research. Scientific journals can play a central role by establishing data policies and providing technologies. The purpose of this paper is to analyses the factors which influence data sharing by investigating journal data policies and the behaviour of authors in sociology. Design/methodology/approach – The web sites of 140 sociology journals were consulted to check their data policy. The results are compared with similar studies from political science and economics. A broad selection of articles published in five selected journals over a period of two years are examined to determine whether authors really cite and share their data and the factors which are related to this. Findings – Although only a few sociology journals have explicit data policies, most journals make reference to a common policy supplied by their association of publishers. Among the journals selected, relatively few articles provide data citations and even fewer make data available – this is true both for journals with and without a data policy. But authors writing for journals with higher impact factors and with data policies are more likely to cite data and to make it really accessible. Originality/value – No study of journal data policies has been undertaken to date for the domain of sociology. A comparison of authors’ behaviours regarding data availability, data citation, and data accessibility for journals with or without a data policy provides useful information about the factors which improve data sharing.

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This paper is part of a series that focuses on DDI usage and how the metadata specification should be applied in a variety of settings by a variety of organizations and individuals. Support for this working Building a Modular DDI 3 Editor B Y J A N N I K J E N S E N A N D D A N K R I S T I A N S E N W I T H A L E R K A M I N , A R O F A N G R E G O R Y , A G O S T I N A M A R T I N E Z , M A R T I N M E C H T E L , M A R Y V A R D I G A N , A N D W O L F G A N G Z E N K -M Ö L T G E N ABSTRACTDevelopers at the Danish Data Archive (DDA) have built an open source DDI 3 editor using a layered architecture. The tool plays a critical role in the work flow at the DDA, providing needed integration of information. The design decisions made during development may be instructive for others building tools based on DDI 3.