Advancing research data management practices in ecology and biodiversity with technology, training, and support

Title: Advancing research data management practices in ecology and biodiversity with technology, training, and support
Authors: Roman Gerlach, Birgitta König-Ries
Source: Ecological Society of America - Annual Meeting 2015
Place: Baltimore, USA
Date: 2015-08-13
Type: Conference Paper
Abstract:

Background/Question/Methods

Over the past decade data management in ecology and biodiversity has seen a proliferation of concepts, standards, software tools, and data infrastructures. The importance of data management is widely acknowledged by funding agencies and researchers alike. Technical solutions for all aspects of the data life cycle are available now. However, from our experiences with research communities in Germany, data management practices are only partially adopted into the scientific workflow and awareness of existing tools is often limited to some aspects, such as analysis or storage. Although there is a growing interest in data management issues and technical solutions, there still seems to be a gap between the technology available today and what is taken up by the scientific community.

In our presentation, we will discuss obstacles and shortcomings that lead to this conclusion. We will argue that to overcome these challenges, a threefold approach is necessary: First, the provision of suitable data management platforms for the ecological and biodiversity research community, second, training efforts to raise awareness and empower researchers to do proper data management, and third the establishment of organizational structures to support researchers.

Results/Conclusions

In the second part of our presentation, we highlight how we implement this threefold approach at our institution:

First, we spearhead the development of the BExIS 2 data management platform (http://fusion.cs.uni-jena.de/bexis). The aim is to provide a generic, scalable, and modular platform following the data life cycle concept. The system is based on a conceptual model and provides modules for data collection, discovery, dissemination, integration, quality assurance and research planning. Advanced features are dataset evolution (versioning) or views on variables of multiple datasets (spanning views). Overall, this development is a community driven effort supported by multiple projects at different research institutions. The user community is engaged through dedicated requirements and usability workshops.

Second, in addition to BExIS 2 specific training we conduct research data management workshops for PhD students (all disciplines), students of Computational science (M.Sc.), and students of ecology and geography (B.Sc., M.Sc.).

Third, we are in the process of establishing a helpdesk to provide support to all scientists of the University of Jena. This involves presentations to raise awareness on research data management topics, but also to assist members in creating data policies, data management plans, data publications and advise on long-term archiving.

These activities are partially funded by the German Science Foundation (DFG) and the Friedrich-Schiller-University of Jena.

URL: https://eco.confex.com/eco/2015/webprogram/Paper55116.html