Management-First Study on Results of Surveys among German Universities ( 2018 )

With the arise of digitalization in science, the amount of research data, i.e. data produced or used during research, has been growing very fast. With the technological development and raising of new scientific methods, also the relevance of research data has increased enormously. Reliable verification of scientific results is possible with the deployment of new technological methods. Furthermore, technology makes it feasible to make new and innovative research built upon existing data. Research data has moved to be an important resource for research, being even called the gold of science [1]. Type of research data differs within different scientific disciplines, given different formats (e.g. text, images, video, audio recordings, etc.). At the same time, the needs for handling data differ, including different levels of legal treatment of sensitive data in some disciplines, handling of very large data sets in computational intensive science, access restrictions for re-use, etc. Some scientific disciplines show a long tradition in handling their data in a standardized way, there exist large international well-accepted data centers, while other disciplines lack of standards and experience in management of research data [2], [3]. Platforms exist, where researchers are able to store, manage and spread their data [4]. As literature shows, these platforms struggle in terms of adoption and acceptance rate [5]. At the same time, researchers are starting to formulate their needs with respect to the management of their research data, addressing the necessity for technical platforms to support the whole research process (e.g. sharing and storage of data or preparation for publication). To handle the ever-growing number of research data in academia, universities and research institutions started to set up own technical infrastructures to manage the increasing flood of information. To avoid the development of inadequate information systems, universities started to carry out surveys asking their researchers what they want. The resulting information is highly relevant for current IS development and could help to design and improve current SaaS applications [6]. The latter resulted in the following research question: RQ: How can technical research solutions be improved in order to raise researchers' acceptance for Research Data Management? As stated 2015 in [7] there are still "only few empirical studies on the subject of research data management in scientific practice [and] these are often characterized by very small samples [and] restrictions to individual departments". Still, to find responses to the stated research question, it cannot be reasonable to wait until every single university or research institution carries out a survey asking researchers for their needs for research platforms. Therefore, this study compares results from ten surveys that have already been carried out at universities, with a focus on German universities. Being the first comparison of survey results regarding RDM-practice among scientists, this thesis has a strong exploratory character. The structure of the thesis will be presented as follows: A Literature Review presents the state of the art regarding research in the topic of acceptance of research data management connected with the evolution of research platforms. The method for comparison of survey results is explained in detail, containing the description of the qualitative content analysis, and the description of quantitative facts and the distribution of frequencies among the defined categories. The results are presented, describing the categories that resulted from the qualitative content analysis. In a discussion, the results are evaluated in relation to the research question showing new outcomes for the research question and describing the limitations of the method. In a conclusion, we explain our interpretation of results an give an outlook for further research questions.