Paving the Way For Data‑Centric, Open Science: An Example From the Social Sciences

Abstract

INTRODUCTION Data has moved into the spotlight as an important scholarly output that should be shared with the scientific community for replication and re-use in new contexts. This has a direct impact on libraries, archives, and other service providers in the data curation and access landscape. DESCRIPTION OF PROJECT The GESIS Data Archive for the Social Sciences (DAS) has been curating and disseminating social science research data since 1960. The article presents tools, services, and strategies developed by the DAS to support the research community in adequately responding to the legal, ethical, and practical challenges that the transformation towards data-centric, open science presents. These include GESIS's Secure Data Center, the data publication platform "datorium" and a recent project to create a georeferencing service for survey data. LESSONS LEARNED The experiences gained through these activities show that getting involved-now, rather than further down the road-pays off in that it allows service providers to actively shape the ongoing transformation. At the same time, by cooperating with suitable partners, the effort and investment of resources can be kept at a manageable level for individual organizations.

Negotiating Open Science: The Open Science Framework as a Technology-in-Practice

“…For instance, data show that scientists often especially value their reputation and career advancement. Consistent with findings from academic open source work [9], Recker, Müller, Trixa, and Schumann emphasize in their literature review "the importance of a reward system making it possible for researchers to gain recognition for sharing their data" [18,4]. Furthermore, while open science advocates frequently reference adherence to open science norms as "just science" [8,2], science and technology scholars indicate that those norms are more akin to an ideology than a true representation of institutionalized scientific behaviors [14].…”

A manifesto for data sharing in social media research

“…Making research data accessible for reuse is in line with initiatives calling for a more 'open science' [26], which also include programs for enabling 'open access' to publications. Such efforts are often supported by funding agencies who increasingly insist on publications and research data to be shared publicly.…”

“…As a consequence, it is desirable to enable more than one researcher or team to make use of the data. Using the same dataset to answer more than one research question is desiredand researchers in the social sciences are used to the practice of accessing data archives for receiving high quality data that they can then use for their specific questions, often in novel combinations with other datasets [26]. Linguists are also used to having access to reusable datasets, so-called linguistic corpora (e.g.…”

Forschungsdatenmanagement systematisch planen und umsetzen

“…In Bezug auf die erste Frage nach dem Inhalt der Dokumentation empfiehlt sich die Unterscheidung von Informationen auf der Studien-und der Variablenebene. Auf Studienebene müssen der übergreifende Kontext der Datenerhebung und deren methodische Grundlagen beschrieben werden, etwa in Form eines Methodenberichts (Watteler 2010). Dieser sollte auch Informationen über rechtliche Aspekte, wie zum Datenschutz oder zum Urheberrecht (s.u.…”

“…Neben der Frage, welche Daten verfügbar gemacht werden sollen, muss für das Konzept zur Erstellung nachnutzbarer Daten auch berücksichtigt werden, was die Bereitstellung überhaupt bedeutet. Um dies besser verstehen zu können, empfiehlt sich ein kurzer Blick auf die sogenannten FAIR Data Principles (Force11 2017;Wilkinson et al 2016;Recker et al 2015). Das Akronym FAIR steht für vier grundlegende Prinzipien -findable, accessible, interoperable und re-usable -, die die Daten erfüllen müssen, um als nachnutzbar zu gelten.…”