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Joint research projects in Ecology, as in other field study and data-intensive research areas, have manifold use cases and requirements for information, collaboration, and data management. Some examples are:
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The recording of action logs for irrigation and other occurences on the experimental plots
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The coordination of joint measurement campaigns
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The management of carpools for driving to research fields
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The spread of information by means of project coordination
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The provision of base data for further data analysis
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The exchange and management of measurement data
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The validation of automatically recorded measurement data
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The joint writing of publication manuscripts and project reports
The need for eResearch Infrastructures for those requirements especially increases when the research teams are geographically dispersed (Siemens, 2010). With the help of IT systems, the exchange of information and data can be made independently from time and/or location. Therefore, eResearch Infrastructures comprising collaboration, information, and data management systems can deliver a substantial contribution to an efficient information and data flow in joint research projects (see, e.g., Markauskaite, Kennan, Richardson, Aditomo, & Hellmers, 2012; Martin, 2014; Thomas, 2011).
Particularly, the task of the management, provision and preservation of research data gained increasing attention ever since several years ago (Akers, Sferdean, Nicholls, & Green, 2014; Androulakis et al., 2009; Pinfield, Cox, & Smith, 2014; Pryor, 2013). Even the Organization for Economic Co-operation and Development (OECD) promotes the internet-based accessibility and preservation of research data from public funding as a key element of the research infrastructure (OECD, 2007).
In recent years, several scientific libraries picked up the topic and are now planning to build up or are already operating public data repositories (Corrall, Kennan, & Afzal, 2013; Cox, Kennan, Lyon, & Pinfield, 2017; Cox & Pinfield, 2014; Tenopir, Sandusky, Allard, & Birch, 2014; Wittenberg & Elings, 2017).
Moreover, some research funders explicitly request strategies for data management for joint research projects (German Research Foundation, 2009; National Science Foundation, 2017). This requirement resulted in the development of several further research data repositories— either for a specific research project (Curdt & Hoffmeister, 2015; Engelhardt, 2013; Willmes, Kürner, & Bareth, 2014) or as public available repositories such as Pangea (Diepenbroek et al., 2002; Grobe, Diepenbroek, Dittert, Reinke, & Sieger, 2006), DataONE (Michener et al., 2012), and Dryad (Miller, 2016; Vision, 2010). Furthermore, in the context of biodiversity research, a microcosm of sophisticated data repositories have been set up (see, e.g., Bendix, Nieschulze, & Michener, 2012). Nevertheless, as stated by Bach et al. (2012), many of these systems have been build up from scratch without the reuse of existing open-source software for data management and without the support of existing data exchange interfaces—so-called harvesting interfaces, such as OIA-PMH (Open Archives Initiative, 2015) or CSW (Open Geospatial Consortium, 2016)—for the interconnection of repositories in order to build up a data network.