Academic research data re-usage in a digital age: modelling best practice

Abstract

Recent high profile retractions – such as the case of Woo Suk Hwang and others – demonstrate that there are still significant issues regarding the reliability of published academic research data. While technological advances offer the potential for greater data re-usability on the Web, models of best practice are yet to be fully re-purposed for a digital age. Employing interdisciplinary web science practices, this thesis asks what makes for excellent quality academic research across the sciences, social sciences and humanities. This thesis uses a case study approach to explore five existing digital data platforms within chemistry, marine environmental sciences and modern languages research. It evaluates their provenance metadata, legal, technological and socio cultural frameworks. This thesis further draws on data collected from semi-structured interviews conducted with eighteen individuals connected to these five data platforms. The participants have a wide range of expertise in the following areas: data management, data policy, academia, law and technology. Through the interdisciplinary literature review and cross-comparison of the three case studies, this thesis identifies the five main principles for improved modelling of best practice for academic research data re-usage both now and in the future. These principles are: (1) sustainability, (2) working towards a common understanding, (3) accreditation, (4) discoverability, and (5) a good user experience. It also reveals nine key grey areas that require further investigation.

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ORCID for Laura German: orcid.org/0000-0001-9391-1310

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