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Arts Research Data at GSA: The Good, The Bad, and The Ugly VADS4R National Workshop, 16 th June 2014 Dr Robin Burgess

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Presentation on theme: "Arts Research Data at GSA: The Good, The Bad, and The Ugly VADS4R National Workshop, 16 th June 2014 Dr Robin Burgess"— Presentation transcript:

1 Arts Research Data at GSA: The Good, The Bad, and The Ugly VADS4R National Workshop, 16 th June 2014 Dr Robin Burgess

2 “What is arts research data? What does it mean to you? Research, art, design, architecture, I’m going to tell you. What is arts research data? We tried to find out. We asked various researchers, and this is what we found…”

3 Objectives Comment on RDM related projects The GOOD: The current status of RDM at GSA, such as our policy The BAD: Lessons we have learnt and advice we can give The UGLY: What we hope to do next and support needed

4 KAPTUR To investigate the nature of research data in the visual arts To consider the application of technology to support collection, discoverability, usage, and preservation of research data in the arts To review appropriate policies, procedures and systems To develop case studies and showcase good practice to a wider audience

5 VADS4R Visual Arts Data Skills 4 Researchers Aim to provide a research data management (RDM) training programme tailored to the needs of early careers researchers and postgraduate students in the visual arts. Led by the Centre for Digital Scholarship (formerly known as VADS)

6 RADAR In 2011 GSA embarked on the development of a research repository using EPrints technology, funded by JISC The interface was supported through web technologies provided by ScreenMedia The funding allowed GSA to produce a whole new repository, replacing the previous Filemaker system EPrints chosen as the preferred software Links made with the Kultivate Project 2013 saw improved uptake and deposits in RADAR

7 The GOOD!

8 RADAR

9 Continued Development Determining the new requirements for RADAR What are our priorities? We are at a cross-roads New modules or new instances of RADAR What does the future hold for repositories and RDM?

10 A Roadmap Gives direction for development of RADAR Highlighting the points to be tackled: E.G. Policies, workflows, Interface, Access, Data Management Shared with the institute for approval

11 Submission/Deposit Process

12 Metadata Development of a metadata policy and guidelines to accompany information present in RADAR Mandatory metadata fields stipulated Cleaning up the data records

13 Access Options Application of better standards Administrator, editor and user rights Access to content Application of embargoes Funder and publisher guidelines

14 Documentation

15 Communication Awareness of RADAR EPrints User Group Internal and External communication Staff Profiles MEPrints(?) Showcase for work at GSA

16 Reporting Monthly reporting Data extracted from RADAR Admin functions IRStats2 package Record of staff and output details Internal distribution

17 Research Data Management Requirements stipulated by HEFCE and Funders Development of polices and roadmaps Application of repository technologies to manage data Visual arts data is complex Data is difference to the output Training packages

18 Thesis Submission New area for GSA Separate browse function Searches possible Improved thesis metadata Thesis submission process created for students Digitisation of theses Important research

19 The BAD

20 RDM in the Visual Arts What is Research Data? Providing a single, authoritative definition of research data in the visual arts is challenging. Research data could be described as: "data which arises out of, and evidences, research...examples of visual arts research data may include sketchbooks, log books, sets of images, video recordings, trials, prototypes, ceramic glaze recipes, found objects, and correspondence. Research data may also be defined as: "evidence which is used or created to generate new knowledge and interpretations. 'Evidence' may be intersubjective or subjective; physical or emotional; persistent or ephemeral; personal or public; explicit or tacit; and is consciously or unconsciously referenced by the researcher at some point during the course of their research. As part of the research process, research data may be collated in a structured way to create a dataset to substantiate a particular interpretation, analysis or argument. A dataset may or may not lead to a research output, which regardless of method of presentation, is a planned public statement of new knowledge or interpretation. Research data can be seen as your “stuff”!

21 Principles and Expectations (1) Research organisations will promote internal awareness… (2) Published research papers should include a short statement about access to supporting data (3) Specific Policies developed (5) Metadata will be structured appropriately (8) Effective data curation is provided throughout the full data lifecycle EPSRC-funded research data is a public good produced in the public interest and should be made feely and openly available Polices should ensure constraints are considered Institutional and project specific policies Sharing research data is important Sufficient metadata should be recorded and made openly available

22 Lessons Learnt Share plans with Research, IT, Library, executive… Prioritize work load Develop tracking and recording procedures Work closely with researchers Engage with developers

23 The UGLY

24 Open Access Finch Report HEFCE Policy on Open Access for REF 2020 Funder and publisher guidance for outputs Copyright and standards A lot for GSA to think about!

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29 Continued Support

30 Next Steps Continued development of the online training Further guidance on RDM Greater engagement with the institution and community Further funding

31 The Future… Identifying further needs from researchers Additional Interviews Development of RDM systems and processes REF2020 requirements RDM in the Visual Arts – a book

32 The Research Community

33 THANKYOU Images: Screenshots taken from RADAR Photography courtesy of the BBC website and Mark Sutherland Original Digital Art and Paintings Produced by Gii Bear and Robin Burgess of Burgess & Bear (www.facebook.com/burgessbear)www.facebook.com/burgessbear


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