I2S2 Final Report

Manjula Patel

    Research output: Book/ReportCommissioned report


    One of our main aims has been to investigate the research and data management infrastructure
    needs of researchers in the Structural Sciences by examining issues relating to scale, complexity and
    inter-disciplinary issues over the useful lifetime of research data. It is important to realise that more
    and more scientific research is derivative in nature, dependent on data generated, managed and then
    made widely accessible to third parties for repurposing and reuse.
    We have found that individual researchers, groups, departments, institutions and central facilities
    appear to be all working within their own technological frameworks so that proprietary and insular
    technical solutions have been adopted (e.g. use of multiple and/or inconsistent identifiers); this makes
    it onerous for researchers to mange research data which can be generated, collected and analysed
    over a period of time, at multiple locations and across different collaborative groups. Researchers
    need to be able to move data across institutional and domain boundaries in a seamless and
    integrated manner. Furthermore, there is an acute danger that processed and derived data in
    particular is likely to be permanently lost since at present these types of data typically reside on an
    individual’s laptop, on DVDs and even on memory sticks.
    We have therefore attempted to understand the nature of the interfaces between individuals,
    institutions and with central facilities and scoped an integrated data management framework which
    allows researchers to work across these boundaries. This has involved aligning infrastructures and
    providing data management tools for individuals that fit into this framework. In particular, we have
    prototyped a desk-top tool that enables a scientist to store and manage all his/her research data as
    they are generated, collected and processed during the course of scientific experimentation. An
    integrated approach to providing robust data management infrastructure enables an efficient
    exchange and reuse of data across disciplinary boundaries; the aggregation and/or cross-searching
    of related datasets; and data mining to identify patterns or trends in research and experiment results.
    A related key aim of the project has been to identify the costs and benefits of the integrated approach
    proposed by the project. Two parallel benefits case studies have explored the perspectives of “scale
    and complexity” and “research discipline” throughout the data lifecycle and resulted in tools that have
    the potential to be useful to a much wider community.
    Original languageEnglish
    PublisherUKOLN, University of Bath
    Number of pages27
    Publication statusPublished - 20 Jun 2011


    • research data management
    • infrastructure
    • structural sciences

    ASJC Scopus subject areas

    • General Computer Science


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