Logo des Repositoriums

Auflistung nach Schlagwort "FAIR principles"

1 - 4 von 4
  • Zeitschriftenartikel
    Exploring research data management planning challenges in practice
    (it - Information Technology: Vol. 62, No. 1, 2020) Lefebvre, Armel; Bakhtiari, Baharak; Spruit, Marco
    Research data management planning (RDMP) is the process through which researchers first get acquainted with research data management (RDM) matters. In recent years, public funding agencies have implemented governmental policies for removing barriers to access to scientific information. Researchers applying for funding at public funding agencies need to define a strategy for guaranteeing that the acquired funds also yield high-quality and reusable research data. To achieve that, funding bodies ask researchers to elaborate on data management needs in documents called data management plans (DMP). In this study, we explore several organizational and technological challenges occurring during the planning phase of research data management, more precisely during the grant submission process. By doing so, we deepen our understanding of a crucial process within research data management and broaden our understanding of the current stakeholders, practices, and challenges in RDMP.
  • Conference paper
    FAIR Learning Technologies with Web Components and Packages
    (Proceedings of DELFI 2024, 2024) Salmen, Frederic; Breuer, Martin; Görzen, Sergej; Persike, Malte; Schroeder, Ulrik
    Making the diverse software artifacts of the learning technologies community findable, accessible, interoperable, and reusable (FAIR) can be a technical challenge. We introduce a concept informed by our research involving packages and components to achieve FAIRness for web-based artifacts. This result is presented as a guideline to make FAIR technology choices when creating web-based learning technologies. The guideline compares classic choices with new paths afforded by technological innovation of the web platform. Supported by practical examples (learning analytics dashboards, e-assessment, and explorables) we discuss practical applications of our result.
  • Zeitschriftenartikel
    From FAIR research data toward FAIR and open research software
    (it - Information Technology: Vol. 62, No. 1, 2020) Hasselbring, Wilhelm; Carr, Leslie; Hettrick, Simon; Packer, Heather; Tiropanis, Thanassis
    The Open Science agenda holds that science advances faster when we can build on existing results. Therefore, research data must be FAIR (Findable, Accessible, Interoperable, and Reusable) in order to advance the findability, reproducibility and reuse of research results. Besides the research data, all the processing steps on these data – as basis of scientific publications – have to be available, too. For good scientific practice, the resulting research software should be both open and adhere to the FAIR principles to allow full repeatability, reproducibility, and reuse. As compared to research data, research software should be both archived for reproducibility and actively maintained for reusability. The FAIR data principles do not require openness, but research software should be open source software. Established open source software licenses provide sufficient licensing options, such that it should be the rare exception to keep research software closed. We review and analyze the current state in this area in order to give recommendations for making research software FAIR and open.
  • Konferenzbeitrag
    On the Lack of Recognition of Software Artifacts and IT Infrastructure in Educational Technology Research
    (20. Fachtagung Bildungstechnologien (DELFI), 2022) Kiesler, Natalie; Schiffner, Daniel
    In the context of educational technology research, it is common practice that computer scientists and IT specialists provide support in terms of software and infrastructure for data gathering and processing, storage, analysis and many other services. Ever since Big Data, Learning Analytics and machine learning algorithms have become increasingly feasible, the implementation of programs can be considered a cornerstone of today’s professional research. Contrary to this trend, software as a method for research is hardly recognized within the community, conferences and publication organs. The same applies to processed research data. Therefore, the authors question the current practices and lack of FAIRness related to the publication of software artifacts by discussing the challenges in terms of acknowledgements, review processes, reproducibility and reuse. The paper concludes with recommendations for future FAIR and Open Science practices.