Data-Driven Insights for a Holistic Understanding of Research Culture

Research environments (and their measurement and tracking) are becoming increasingly complex, with rapid Artificial Intelligence (AI) advancements, interdisciplinary collaboration, and global connectivity shaping the way research knowledge is created and disseminated. Within this dynamic landscape, universities hold an ever increasing collection of valuable data, which are stored within core operational systems including research information systems, research management systems or grants databases, human resource systems and course management systems. This treasure trove of information, often overlooked and underutilised, not only serves as a valuable tool in guiding strategic decisions, but also could be further used to provide a comprehensive approach to monitoring research integrity and culture. This critical reflection follows extensive conversations and debates around defining and assessing ‘research culture’. How can we possibly measure something that has, up until now, been viewed as merely a concept? How can we generate useful metrics that reflect the culture of a research institution? Our reflections will draw attention to the potential of leveraging readily accessible information to gauge and benchmark research integrity and culture practices. We discuss how regular habitual integration of these data sources enables continuous monitoring and measurement of research culture as well as the ability to assist in the assessment of interventions or initiatives designed to improve it. We reflect on how this approach ensures that University leaders have a consistent and up-to-date understanding of the research environment through which they can identify strengths, pinpoint areas for improvement, and cultivate a more robust, inclusive, and transparent research ecosystem. The current paper, through illustrative examples from one UK-based institution, explores the potential in harnessing existing data, such as collaborative trends and prevailing research practices, to gain valuable insights into the dynamics of academic research. In addition, we explore the advantages and drawbacks of using this data to develop potential metrics that can be used to recognise and reward a healthy research culture.

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Publication Details

Journal
Exchanges The Interdisciplinary Research Journal
Published
2024-10-31
DOI
https://doi.org/10.31273/eirj.v12i1.1610
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

Data-Driven Insights for a Holistic Understanding of Research Culture

Victoria Simms, Ann Campbell, Maria Prince
Exchanges The Interdisciplinary Research Journal
Computational and Text Analysis Methods
article

Data-Driven Insights for a Holistic Understanding of Research Culture

Victoria Simms, Ann Campbell, Maria Prince
article en

Abstract

Research environments (and their measurement and tracking) are becoming increasingly complex, with rapid Artificial Intelligence (AI) advancements, interdisciplinary collaboration, and global connectivity shaping the way research knowledge is created and disseminated. Within this dynamic landscape, universities hold an ever increasing collection of valuable data, which are stored within core operational systems including research information systems, research management systems or grants databases, human resource systems and course management systems. This treasure trove of information, often overlooked and underutilised, not only serves as a valuable tool in guiding strategic decisions, but also could be further used to provide a comprehensive approach to monitoring research integrity and culture. This critical reflection follows extensive conversations and debates around defining and assessing ‘research culture’. How can we possibly measure something that has, up until now, been viewed as merely a concept? How can we generate useful metrics that reflect the culture of a research institution? Our reflections will draw attention to the potential of leveraging readily accessible information to gauge and benchmark research integrity and culture practices. We discuss how regular habitual integration of these data sources enables continuous monitoring and measurement of research culture as well as the ability to assist in the assessment of interventions or initiatives designed to improve it. We reflect on how this approach ensures that University leaders have a consistent and up-to-date understanding of the research environment through which they can identify strengths, pinpoint areas for improvement, and cultivate a more robust, inclusive, and transparent research ecosystem. The current paper, through illustrative examples from one UK-based institution, explores the potential in harnessing existing data, such as collaborative trends and prevailing research practices, to gain valuable insights into the dynamics of academic research. In addition, we explore the advantages and drawbacks of using this data to develop potential metrics that can be used to recognise and reward a healthy research culture.

Exchanges The Interdisciplinary Research JournalVol. 12(1)
University of Ulster (GB), Digital Science (United Kingdom) (GB)
Openalex Percentile: Top 66%
Computational and Text Analysis Methods
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