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Research . 2024
License: CC BY
Data sources: Datacite
ZENODO
Research . 2024
License: CC BY
Data sources: Datacite
ZENODO
Research . 2024
License: CC BY
Data sources: Datacite
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Creative Informatics Ethics Statement (version 2.0)

Authors: Osborne, Nicola; McDonald, Caitlin; Schafer, Burkhard; Terras, Melissa;

Creative Informatics Ethics Statement (version 2.0)

Abstract

Creative Informatics has been an ambitious research and development programme based in Edinburgh, which aimed to bring the city’s world-class creative industries and tech sector together, providing funding and development opportunities that enabled creative individuals and organisations to explore how data could be used to drive ground-breaking new products, businesses and experiences. Creative Informatics has nurtured local talent through funding programmes and regular events that supported Edinburgh’s creative industries to do inspiring things with data. This work has been supported by research into the cluster and emerging data driven creative practices. The Creative Informatics Ethics Statement was created to capture the programme’s position on the values and priorities for the work undertaken and supported, and forms part of our work to encourage best practices and thoughtful reflection on work with data and new technologies in the creative industries. This Ethics Statement provides guidance for those working in and around the creative industries, or with data more broadly in a creative context, and should be used as a tool for reflection with prompts to consider, document, and review approaches and practices, and as a way to encourage positive engagement with legal and societal responsibilities. In the Creative Informatics programme we have used this ethics process as a required component of forming contracts with companies selected for R&D grant funding, with participants required to complete and submit the form for review before the signing of contracts. In some cases (based either on the complexity of issues raised, and/or on the preference of participants for additional support), the review process was accompanied by further discussion, guidance, and a resubmitted version of the form prior to official sign off by the programme team. The authors are publishing this work openly as we enthusiastically welcome reuse and remixing of the Creative Informatics Ethics Statement and welcome questions or comments that may feed into future iterations and best practices. Since the original publication of the Creative Informatics Ethics Statement (v1.3), it has been adopted by other organisations as a tool, particularly those working with creative SMEs. This updated statement (v2.0) includes a number of additions, changes and updates informed by Creative Informatics’ use of this process with over 130 R&D projects, as well as feedback from wider stakeholders. 

Creative Informatics has been a partnership between The University of Edinburgh, Edinburgh Napier University, Creative Edinburgh and Codebase. Creative Informatics was funded by: the Creative Industries Clusters Programme managed by the Arts & Humanities Research Council as part of the Industrial Strategy; the Scottish Funding Council; the Data Driven Innovation Programme of the Edinburgh and South East Scotland City Region Deal; and the UK Government Department for Culture, Media and Sport.

Related Organizations
Keywords

creative industries, data ethics, best practice, SME ethics, ethics self-review, ethics process, data-driven innovation, ethics, ai ethics, Creative Informatics

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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