Designing an information architecture for data management technologies: Introducing the DIAMANT model

Abstract

Although research institutions take on increased responsibility for providing infrastructures and services around the proper handling of research data, there is no comprehensive framework addressing the ideal conditions of this implementation process. To overcome this gap, we present the DIAMANT model, a reference model aimed at providing an orientation framework for the implementation of research data management guided by the research process itself. It builds upon a central research data management information unit controlling the information flow between all other organizational units involved in research data management. Due to the possibility of outsourcing organizational units, the implementation process is maximally flexible and efficient.

Research data management systems and the organization of universities and research institutes: A systematic literature review

“…The implementation of an RDMS will support researchers but could also lead to a change within the organizational structures of HEI. These changes can be realized through new services or the reconfiguration of existing ones to support researchers in the handling of data (Blask and Förster, 2020; Castle, 2019; Cruz et al, 2019; Verbaan and Cox, 2014), the collaboration between different institutional units to realize or advance services and infrastructure (Mohammed and Ibrahim, 2019; Whyte, 2014) or the reallocation of resources in favor of infrastructure or human resources/further education for RDM activities (e.g. Chiware and Mathe, 2016; Cox et al, 2019; Schirrwagen et al, 2019).…”

“…The establishment of legal consulting could decrease these barriers. Hence, the importance to incorporate the legal department or ethic review boards for specific question in the research process increases (Blask and Förster, 2020; Jackson, 2018) and can enhance the responsibilities as well as service profiles of this unit. Copy rights, intellectual property rights, data security, or data ethics were named as examples for legal issues (e.g.…”

“…Bardyn et al, 2018; Clare et al, 2019; Macdonald and Martinez-Uribe, 2010; Willaert et al, 2019). Again, the involvement of users and the orientation on the research process are essential to decide about new infrastructure (Blask and Förster, 2020; Willaert et al, 2019). To use resources as efficient as possible, the sample proposed that HEI should collaborate and share services as well as infrastructure (Grasse et al, 2018; Schmidt and Dierkes, 2015).…”

Annolog: A Query Processing Framework for Modelling and Reasoning with Annotated Data

“…Metadata refers to the contextual information that establishes relationships between the data and the real-world aspects it applies to [1]. In other words, metadata is the data that describes information about a piece of data [2], thereby creating a relationship in terms of the content and functionality of that data [3]. Annotation is a type of metadata that keeps extra information about data [4].…”

The matter of meta in research data management: Introducing the CESSDA Metadata Office Project

“…Accompanying these developments, research on RDM has become more important over the last years, although it is still considered to be at an early stage. For instance, some scholars investigate how information infrastructures at universities and research institutions have to be designed in order to optimally incorporate RDM processes (Blask and Förster 2019). Other scholars focus on how to encourage researchers to perform RDM (van den Eynden and Bishop 2014), since for many researchers, the disadvantages of doing RDM still dominate.…”