Abstract
[full article, abstract in English; abstract in Lithuanian]
 The purpose of this paper is to develop an understanding of factors that affect the respondents to drop out of an already started survey on research data management. We decided to take a questionnaire on data management survey at Vilnius University and Oulu University implemented in 2017 as a case study. The data for the analysis was collected using the questionnaire, which was used in multinational research for Data Literacy and Research Data Management, performed by a group of researchers in more than ten countries, initiated by Serap Kurbanoğlu and Joumana Boustany. This paper describes the analysis of 1 185 survey samples, of which 515 were unfinished and 670 finished in both universities. For the analysis of the data, we used Framework for Web Survey Participation created by Andy Peytchev (2009). The collected data was analyzed using IBM SPSS Statistics ver. 19 with descriptive and inferential statistical tests. The most significant factors on deciding not to finish the survey were the length of the survey, the scientific field, experience, age and the topic of the survey. No statistically significant difference was measured between those who finished the survey and unfinished evaluating the data by gender and job position. An important factor in not finishing the survey was the design of the survey.
Highlights
Many higher education institutions (HEIs) have recognized the need to develop Research and Data Management (RDM) services and are currently engaged in this activity (in the UK, over 40 universities have been involved in developing RDM services within Managing Research Data (MRD) programs)
The purpose of this paper is to develop an understanding of the factors that had affected the respondents to drop out of the already started survey on research data management
By analyzing the potential demographic factors behind the reason not to finish the survey, we have found the most important to be the scientific field, experience and age
Summary
Many higher education institutions (HEIs) have recognized the need to develop Research and Data Management (RDM) services and are currently engaged in this activity (in the UK, over 40 universities have been involved in developing RDM services within Managing Research Data (MRD) programs). A significant move toward the management and research of data sharing is implemented at Vilnius University by creating a national, institutional repository for data archiving and preparing legal documents and recommendations for researchers on data management and sharing. Very few researchers began to archive their data and were eager to prepare a plan for data management and sharing when there are no requirements from research funding organizations or scholarly journals. The Lithuanian research council does not imperatively require that the scholars prepare a data management and sharing plan. Creating a data management and sharing plan would benefit both researchers and universities themselves. It would ensure the possibility of finding and understanding data when there is a need to use it, avoiding unnecessary duplication. When recollecting or reworking data, the data underlying their respective publications are maintained, allowing for the validation of results; data sharing leads to more collaboration and advances in research; research becomes more visible and has greater impact; researchers can cite the data of other scholars, who, in turn, get credited for their studies (Jones, Pryor, Whyte 2013)
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