SlideShare a Scribd company logo
1 of 30
Download to read offline
Arts Research Data:
It’s as easy as 1 2 3 or is that A B C




             Dr Robin Burgess
              6th March 2013
Context
 • Describe the processes that lead to the
   development of GSAs Research Data Management
   Policy
 • Engagement in the Kaptur Project
 • Raising awareness amongst staff of the importance
   of research data management – teaching and
   training
 • Sharing lessons learnt and recommendations
 • Describing the A-Z of arts research data
Background - GSA
                   •   A creative hothouse
                   •   At the heart of one of Europe’s
                       most influential creative artistic
                       communities
                   •   Producers of mature and
                       confident graduates in fine art,
                       design and architecture
                   •   Researchers that influence world
                       culture and generate new
                       knowledge
Background – Cont.
•   No existing RDM policy or
    infrastructure in place at GSA
•   Some policies present such as Ethics
•   Determined that involvement in
    KAPTUR would come from the
    research office and Learning
    Resources
•   Research outputs are varied and
    complex in the visual arts
•   Little is known about the state of
    research data in the visual arts
•   None of the specialist arts institutions
    have research data management
    policies or infrastructure
•   Very beneficial for GSA
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
Expectations
 • To develop and implement the RDM
   policy throughout the school
 • Raise awareness of staff
 • Understand what research data is
 • Understand further what funders are
   expecting of HEIs
Process
          • Environmental
            Assessment
          • User
            Requirements,
            systems evaluation
            and piloting
          • Policy formation
          • Capacity building
          • Sustainability
          • Dissemination
Environmental Assessment
•   Discover, Create and pilot   •   4 researchers from each institute
    a sectoral model of best         chosen, from a broad range of
    practice in the                  disciplines
    management of research       •   Areas discussed
    data in the arts             -   Terminology
•   What is research data in     -   Role of the visual arts researcher
    the arts?
                                 -   Creation of visual arts research
•   How can visual arts data         data
    be managed appropriately
                                 -   Use/re-use of visual arts data
                                 -   Visual arts data in the longer term
Interview Findings
•   The term ‘research data’ was not helpful
•   Researchers undertake multiple roles
•   Creation of data altered
•   Awareness of use and re-use present
•   Importance of archiving raised
•   Little consensus in the visual arts on what research data is
•   Described as tangible, intangible, digital, and physical
•   Visual arts data is heterogeneous and infinite,
    complex and complicated
Quote from a researcher:
“… I am not sure what constitutes research
data… What is data? I mean, I talk to you about
my data as a researcher, but for the institution,
what does it consider data? Would it be
conference proceedings, would a performance
be data even if it was not recorded, sometimes I
don’t record my performances…”
Definition
“Research data means data in the form of facts, observations, images,
computer program results, recordings, measurement or experiences on
which a research output is based. Data maybe numerical, descriptive,
visual or tactile. It may be raw, cleaned or processed, and may be held
in any format or media. Research data in the arts mirrors the complexity
of the outputs, taking many forms including logbooks, journals,
workbooks, sample libraries, sketchbooks, sets of images, video
recordings, trials, prototypes, ceramic glaze recipes, found objects, and
correspondence. Provenance information about the data might also be
included: the how, when, where it was collected and with what. This
metadata facilitates later interpretation and re-use of data"
Additional Outputs




 • DCC Roadshows
 • International Open Repository Conference
 • http://www.youtube.com/watch?v=tbG1Tg9_0l8
Teaching and Training



                        Methods, Methodologies
                        and Techniques
                        MRes students and early
                        career researchers
Teaching and Training
                Being Boring By Wendy Cope

                If you ask me ‘What’s new?’, I have nothing to say
                Except that the garden is growing
                I had a slight cold but it’s better today
                I’m content with the way things are going
                Yes, he is the same as he usually is
                Still eating and sleeping and snoring
                I get on with my work. He gets on with his
                I know this is all very boring...
Teaching and Training
Why Manage Research Data?
 • What are the drivers and incentives for
   management of research data?
 • Who benefits?
 • Funder Requirements
 • Institutional Requirements
 • Good practice in research
Funder Requirements
 • EPSRC                  • AHRC
 • Policies required to   • Technical Summary
   secure funding by      •   “We expect all or research projects
                              to have some form of documentation
   1st May 2015               of the research process, which
 • Road map                   usually takes the form of textual
                              analysis or explanation to support
   development and            the research’s position and to
   data management            demonstrate critical reflection”
   plans
Policy Development
• Involvement of Kaptur and Support from project
  partners
• Liaison with outside sources – e.g. the DCC
• Attendance at events – Conference in Leeds
• Involvement of interested parties at GSA – IT,
  Information Services and the Library, Research
  Office, Researchers
• Existing policies and procedures and plans
Approach




• Context                       • Iterative process
• Definition of research data   • Discussions held
• Policy statements             • Obtaining feedback
• Implementation methods        • Sign off and agreement
The Policy
 Roles and                 Preservation
 Responsibilities
• The Glasgow School of    • Data curation/retention
  Art                      • Presentation and
• Individual Researchers     showcasing work
• IT                       • Selection process
• Information Services     • FOI
• The Research Office      • Institutional policies and
                             guidelines/strategies
Data Management,
Methods

 Research Repository   Other Software
                       • DCC tools
                       • DMP Online
                       • https://dmponline.dcc.ac.uk/
                       • Free data management
                         planning tool
                       • Includes AHRC technical
                         plan and others
                       • Can be customised
Comments
Challenges:                Lessons Learnt:
• Building the support     • Identify the correct people
  network at GSA             to engage with
• Extensive focus on the   • Formulate an action plan
  REF process                for development
• Changes in management    • Communicate
• Expressing the           • Obtain by-in early on
  importance of policies
• EPSRC letter
• RDM Understanding
Next Steps and
Key Points
                                    1.  Engage early with interested
                                        departments
                                    2. Engage with end users
                                    3. Engage with external bodies
                                    4. Research data in the arts is not
                                        simple
                                    5. Be aware of the varying nature of
                                        arts research data
                                    6. Ensure suitable processes are in
                                        place for policy development
                                    7. Be aware of requirements from
• Further approval of the policy        funders
                                    8. Provide adequate teaching and
• Implementation of Policy within       training
  the ethos of research at GSA      9. Ensure suitable institutional
                                        infrastructure is in place
• Support from Learning             10. Be aware of the views of the
  Resources and Research                individual

  Office
Acknowledgements
•   The project officers from partner institutes
•   VADS
•   JISC for sponsoring the project
•   DCC
•   Artwork images – By Burgess&Bear
•   (http://www.facebook.com/BurgessBear)

                        THANKYOU!
http://www.vads.ac.uk/kaptur/

More Related Content

What's hot

Research Integrity - Supervision Enhancement Program, Feb 2016
Research Integrity - Supervision Enhancement Program, Feb 2016Research Integrity - Supervision Enhancement Program, Feb 2016
Research Integrity - Supervision Enhancement Program, Feb 2016Merilyn Childs
 
Principles and key responsibilities in RI, RDM, RIAs and their intersection
Principles and key responsibilities in RI, RDM, RIAs and their intersectionPrinciples and key responsibilities in RI, RDM, RIAs and their intersection
Principles and key responsibilities in RI, RDM, RIAs and their intersectionARDC
 
Trends in-connecting-research-sgd-2013
Trends in-connecting-research-sgd-2013Trends in-connecting-research-sgd-2013
Trends in-connecting-research-sgd-2013Sanjeev Deshmukh
 
Okraku_Research Prospectus Outline_042016
Okraku_Research Prospectus Outline_042016Okraku_Research Prospectus Outline_042016
Okraku_Research Prospectus Outline_042016Therese Kennelly Okraku
 
Research Integrity: Philosophical Perspectives
Research Integrity: Philosophical Perspectives Research Integrity: Philosophical Perspectives
Research Integrity: Philosophical Perspectives Robert Farrow
 
Northern Collaboration Conference 2014: Evolving Roles by Helen McEvoy
Northern Collaboration Conference 2014: Evolving Roles by Helen McEvoyNorthern Collaboration Conference 2014: Evolving Roles by Helen McEvoy
Northern Collaboration Conference 2014: Evolving Roles by Helen McEvoynortherncollaboration
 
Research Data in the Arts and Humanities: A Few Difficulties
Research Data in the Arts and Humanities: A Few DifficultiesResearch Data in the Arts and Humanities: A Few Difficulties
Research Data in the Arts and Humanities: A Few DifficultiesMartin Donnelly
 
Teaching research methods in LIS programs: Approaches, formats, and innovativ...
Teaching research methods in LIS programs: Approaches, formats, and innovativ...Teaching research methods in LIS programs: Approaches, formats, and innovativ...
Teaching research methods in LIS programs: Approaches, formats, and innovativ...Lynn Connaway
 
E research africa presentation (19 nov 2014)
E research africa presentation (19 nov 2014)E research africa presentation (19 nov 2014)
E research africa presentation (19 nov 2014)Isak Van der Walt
 
Impact of Integration of OER in Teacher Education_GO-GN-Webinar_Shironica_Kar...
Impact of Integration of OER in Teacher Education_GO-GN-Webinar_Shironica_Kar...Impact of Integration of OER in Teacher Education_GO-GN-Webinar_Shironica_Kar...
Impact of Integration of OER in Teacher Education_GO-GN-Webinar_Shironica_Kar...Shironica Karunanayaka
 
Writing Research Projects
Writing Research ProjectsWriting Research Projects
Writing Research ProjectsSalvador Cenita
 
Penny Abbott - New HR Professional Practice Standards
Penny Abbott - New HR Professional Practice StandardsPenny Abbott - New HR Professional Practice Standards
Penny Abbott - New HR Professional Practice StandardsSABPP
 
Social science research methods for libraries
Social science research methods for librariesSocial science research methods for libraries
Social science research methods for librariesCILIPScotland
 
A needs analysis for information literacy provision for research: a case stud...
A needs analysis for information literacy provision for research: a case stud...A needs analysis for information literacy provision for research: a case stud...
A needs analysis for information literacy provision for research: a case stud...IL Group (CILIP Information Literacy Group)
 
Measuring Scientific Productivity
Measuring Scientific ProductivityMeasuring Scientific Productivity
Measuring Scientific ProductivityMuruli N. Tarikere
 

What's hot (19)

Research Integrity - Supervision Enhancement Program, Feb 2016
Research Integrity - Supervision Enhancement Program, Feb 2016Research Integrity - Supervision Enhancement Program, Feb 2016
Research Integrity - Supervision Enhancement Program, Feb 2016
 
Principles and key responsibilities in RI, RDM, RIAs and their intersection
Principles and key responsibilities in RI, RDM, RIAs and their intersectionPrinciples and key responsibilities in RI, RDM, RIAs and their intersection
Principles and key responsibilities in RI, RDM, RIAs and their intersection
 
Trends in-connecting-research-sgd-2013
Trends in-connecting-research-sgd-2013Trends in-connecting-research-sgd-2013
Trends in-connecting-research-sgd-2013
 
Sarah mahurter
Sarah mahurterSarah mahurter
Sarah mahurter
 
Okraku_Research Prospectus Outline_042016
Okraku_Research Prospectus Outline_042016Okraku_Research Prospectus Outline_042016
Okraku_Research Prospectus Outline_042016
 
Research Integrity: Philosophical Perspectives
Research Integrity: Philosophical Perspectives Research Integrity: Philosophical Perspectives
Research Integrity: Philosophical Perspectives
 
Northern Collaboration Conference 2014: Evolving Roles by Helen McEvoy
Northern Collaboration Conference 2014: Evolving Roles by Helen McEvoyNorthern Collaboration Conference 2014: Evolving Roles by Helen McEvoy
Northern Collaboration Conference 2014: Evolving Roles by Helen McEvoy
 
Research Data in the Arts and Humanities: A Few Difficulties
Research Data in the Arts and Humanities: A Few DifficultiesResearch Data in the Arts and Humanities: A Few Difficulties
Research Data in the Arts and Humanities: A Few Difficulties
 
Teaching research methods in LIS programs: Approaches, formats, and innovativ...
Teaching research methods in LIS programs: Approaches, formats, and innovativ...Teaching research methods in LIS programs: Approaches, formats, and innovativ...
Teaching research methods in LIS programs: Approaches, formats, and innovativ...
 
Section 2
Section 2Section 2
Section 2
 
E research africa presentation (19 nov 2014)
E research africa presentation (19 nov 2014)E research africa presentation (19 nov 2014)
E research africa presentation (19 nov 2014)
 
Impact of Integration of OER in Teacher Education_GO-GN-Webinar_Shironica_Kar...
Impact of Integration of OER in Teacher Education_GO-GN-Webinar_Shironica_Kar...Impact of Integration of OER in Teacher Education_GO-GN-Webinar_Shironica_Kar...
Impact of Integration of OER in Teacher Education_GO-GN-Webinar_Shironica_Kar...
 
CHEPSAA final networking meeting: capacity assessments
CHEPSAA final networking meeting: capacity assessmentsCHEPSAA final networking meeting: capacity assessments
CHEPSAA final networking meeting: capacity assessments
 
Writing Research Projects
Writing Research ProjectsWriting Research Projects
Writing Research Projects
 
Penny Abbott - New HR Professional Practice Standards
Penny Abbott - New HR Professional Practice StandardsPenny Abbott - New HR Professional Practice Standards
Penny Abbott - New HR Professional Practice Standards
 
Social science research methods for libraries
Social science research methods for librariesSocial science research methods for libraries
Social science research methods for libraries
 
A needs analysis for information literacy provision for research: a case stud...
A needs analysis for information literacy provision for research: a case stud...A needs analysis for information literacy provision for research: a case stud...
A needs analysis for information literacy provision for research: a case stud...
 
Measuring Scientific Productivity
Measuring Scientific ProductivityMeasuring Scientific Productivity
Measuring Scientific Productivity
 
Lecture4 (cs351) (research proposal)
Lecture4 (cs351) (research proposal)Lecture4 (cs351) (research proposal)
Lecture4 (cs351) (research proposal)
 

Similar to Robin burgess

Engaging with students and researchers: the case of the social sciences
Engaging with students and researchers: the case of the social sciencesEngaging with students and researchers: the case of the social sciences
Engaging with students and researchers: the case of the social sciencesLouise Corti
 
Creating and Maintaining a Sustainable Research Data Management Service: Wher...
Creating and Maintaining a Sustainable Research Data Management Service: Wher...Creating and Maintaining a Sustainable Research Data Management Service: Wher...
Creating and Maintaining a Sustainable Research Data Management Service: Wher...ARLGSW
 
Disciplinary dimensions of digital curation: introduction and synthesis
Disciplinary dimensions of digital curation: introduction and synthesisDisciplinary dimensions of digital curation: introduction and synthesis
Disciplinary dimensions of digital curation: introduction and synthesisChris Rusbridge
 
RDAP14: University-wide Research Data Management Policy
RDAP14: University-wide Research Data Management PolicyRDAP14: University-wide Research Data Management Policy
RDAP14: University-wide Research Data Management PolicyASIS&T
 
Briefing on Research Data Management at LSBU December 2015
Briefing on Research Data Management at LSBU December 2015Briefing on Research Data Management at LSBU December 2015
Briefing on Research Data Management at LSBU December 2015London South Bank University
 
Minding the skills gap: Developments in information-training handling for res...
Minding the skills gap: Developments in information-training handling for res...Minding the skills gap: Developments in information-training handling for res...
Minding the skills gap: Developments in information-training handling for res...Research Information Network
 
Creating a thriving research environment
Creating a thriving research environmentCreating a thriving research environment
Creating a thriving research environmentEmma Gillaspy
 
RDM at Northampton EMALINK 130313 v3
RDM at Northampton EMALINK 130313 v3RDM at Northampton EMALINK 130313 v3
RDM at Northampton EMALINK 130313 v3mjpickt
 
Immersive informatics - research data management at Pitt iSchool and Carnegie...
Immersive informatics - research data management at Pitt iSchool and Carnegie...Immersive informatics - research data management at Pitt iSchool and Carnegie...
Immersive informatics - research data management at Pitt iSchool and Carnegie...Keith Webster
 
Developing Research Data Management Policy and Services
Developing Research Data Management Policy and ServicesDeveloping Research Data Management Policy and Services
Developing Research Data Management Policy and ServicesRobin Rice
 
Laying the Foundation: Establishing an institutional RDM Support Service for ...
Laying the Foundation: Establishing an institutional RDM Support Service for ...Laying the Foundation: Establishing an institutional RDM Support Service for ...
Laying the Foundation: Establishing an institutional RDM Support Service for ...GarethKnight
 
LIBER Webinar: Supporting Data Literacy
LIBER Webinar: Supporting Data LiteracyLIBER Webinar: Supporting Data Literacy
LIBER Webinar: Supporting Data LiteracyLIBER Europe
 
Teaching data management in a lab environment (IASSIST 2014)
Teaching data management in a lab environment (IASSIST 2014)Teaching data management in a lab environment (IASSIST 2014)
Teaching data management in a lab environment (IASSIST 2014)IUPUI
 
Data Management for librarians
Data Management for librariansData Management for librarians
Data Management for librariansC. Tobin Magle
 

Similar to Robin burgess (20)

Dcc roadshow dundee_rb
Dcc roadshow dundee_rbDcc roadshow dundee_rb
Dcc roadshow dundee_rb
 
Kaptur rburgess 18th july 2012
Kaptur rburgess 18th july 2012Kaptur rburgess 18th july 2012
Kaptur rburgess 18th july 2012
 
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
 
Engaging with students and researchers: the case of the social sciences
Engaging with students and researchers: the case of the social sciencesEngaging with students and researchers: the case of the social sciences
Engaging with students and researchers: the case of the social sciences
 
Creating and Maintaining a Sustainable Research Data Management Service: Wher...
Creating and Maintaining a Sustainable Research Data Management Service: Wher...Creating and Maintaining a Sustainable Research Data Management Service: Wher...
Creating and Maintaining a Sustainable Research Data Management Service: Wher...
 
Disciplinary dimensions of digital curation: introduction and synthesis
Disciplinary dimensions of digital curation: introduction and synthesisDisciplinary dimensions of digital curation: introduction and synthesis
Disciplinary dimensions of digital curation: introduction and synthesis
 
RDAP14: University-wide Research Data Management Policy
RDAP14: University-wide Research Data Management PolicyRDAP14: University-wide Research Data Management Policy
RDAP14: University-wide Research Data Management Policy
 
Briefing on Research Data Management at LSBU December 2015
Briefing on Research Data Management at LSBU December 2015Briefing on Research Data Management at LSBU December 2015
Briefing on Research Data Management at LSBU December 2015
 
Minding the skills gap: Developments in information-training handling for res...
Minding the skills gap: Developments in information-training handling for res...Minding the skills gap: Developments in information-training handling for res...
Minding the skills gap: Developments in information-training handling for res...
 
Creating a thriving research environment
Creating a thriving research environmentCreating a thriving research environment
Creating a thriving research environment
 
RDM at Northampton EMALINK 130313 v3
RDM at Northampton EMALINK 130313 v3RDM at Northampton EMALINK 130313 v3
RDM at Northampton EMALINK 130313 v3
 
Immersive informatics - research data management at Pitt iSchool and Carnegie...
Immersive informatics - research data management at Pitt iSchool and Carnegie...Immersive informatics - research data management at Pitt iSchool and Carnegie...
Immersive informatics - research data management at Pitt iSchool and Carnegie...
 
Developing Research Data Management Policy and Services
Developing Research Data Management Policy and ServicesDeveloping Research Data Management Policy and Services
Developing Research Data Management Policy and Services
 
LEAD 901 Chapter 3
LEAD 901 Chapter 3LEAD 901 Chapter 3
LEAD 901 Chapter 3
 
Laying the Foundation: Establishing an institutional RDM Support Service for ...
Laying the Foundation: Establishing an institutional RDM Support Service for ...Laying the Foundation: Establishing an institutional RDM Support Service for ...
Laying the Foundation: Establishing an institutional RDM Support Service for ...
 
LIBER Webinar: Supporting Data Literacy
LIBER Webinar: Supporting Data LiteracyLIBER Webinar: Supporting Data Literacy
LIBER Webinar: Supporting Data Literacy
 
Open data publishing and incentives/Susan Veldsman
Open data publishing and incentives/Susan VeldsmanOpen data publishing and incentives/Susan Veldsman
Open data publishing and incentives/Susan Veldsman
 
LEAD 901 Chapter 7
LEAD 901 Chapter 7LEAD 901 Chapter 7
LEAD 901 Chapter 7
 
Teaching data management in a lab environment (IASSIST 2014)
Teaching data management in a lab environment (IASSIST 2014)Teaching data management in a lab environment (IASSIST 2014)
Teaching data management in a lab environment (IASSIST 2014)
 
Data Management for librarians
Data Management for librariansData Management for librarians
Data Management for librarians
 

More from JISC funded KAPTUR project

More from JISC funded KAPTUR project (20)

A working archive in the studio and on screen
A working archive in the studio and on screenA working archive in the studio and on screen
A working archive in the studio and on screen
 
Research data-visual arts-presentation
Research data-visual arts-presentationResearch data-visual arts-presentation
Research data-visual arts-presentation
 
Leigh garrett
Leigh garrettLeigh garrett
Leigh garrett
 
Carlos silva
Carlos silvaCarlos silva
Carlos silva
 
Anne spalding
Anne spaldingAnne spalding
Anne spalding
 
Andrew gray
Andrew grayAndrew gray
Andrew gray
 
Kaptur business-plan-template-public
Kaptur business-plan-template-publicKaptur business-plan-template-public
Kaptur business-plan-template-public
 
The prayer companion_boucher_et_al
The prayer companion_boucher_et_alThe prayer companion_boucher_et_al
The prayer companion_boucher_et_al
 
Lm gsa training
Lm gsa trainingLm gsa training
Lm gsa training
 
Kaptur mrd example
Kaptur mrd exampleKaptur mrd example
Kaptur mrd example
 
Kaptur mrd questions
Kaptur mrd questionsKaptur mrd questions
Kaptur mrd questions
 
Uca mrd presentation january 2013
Uca mrd presentation january 2013Uca mrd presentation january 2013
Uca mrd presentation january 2013
 
Rdm training presentation 16.01.2013
Rdm training presentation 16.01.2013Rdm training presentation 16.01.2013
Rdm training presentation 16.01.2013
 
20130116 dmp training
20130116 dmp training20130116 dmp training
20130116 dmp training
 
Kaptur IT costs public
Kaptur IT costs publicKaptur IT costs public
Kaptur IT costs public
 
20130108 kaptur lg
20130108 kaptur lg20130108 kaptur lg
20130108 kaptur lg
 
20130108 kaptur mtg
20130108 kaptur mtg20130108 kaptur mtg
20130108 kaptur mtg
 
20130108 kaptur gold_jc
20130108 kaptur gold_jc20130108 kaptur gold_jc
20130108 kaptur gold_jc
 
20130108 kaptur gsa_rb
20130108 kaptur gsa_rb20130108 kaptur gsa_rb
20130108 kaptur gsa_rb
 
20130108 kaptur uca_as
20130108 kaptur uca_as20130108 kaptur uca_as
20130108 kaptur uca_as
 

Robin burgess

  • 1. Arts Research Data: It’s as easy as 1 2 3 or is that A B C Dr Robin Burgess 6th March 2013
  • 2. Context • Describe the processes that lead to the development of GSAs Research Data Management Policy • Engagement in the Kaptur Project • Raising awareness amongst staff of the importance of research data management – teaching and training • Sharing lessons learnt and recommendations • Describing the A-Z of arts research data
  • 3. Background - GSA • A creative hothouse • At the heart of one of Europe’s most influential creative artistic communities • Producers of mature and confident graduates in fine art, design and architecture • Researchers that influence world culture and generate new knowledge
  • 4. Background – Cont. • No existing RDM policy or infrastructure in place at GSA • Some policies present such as Ethics • Determined that involvement in KAPTUR would come from the research office and Learning Resources • Research outputs are varied and complex in the visual arts • Little is known about the state of research data in the visual arts • None of the specialist arts institutions have research data management policies or infrastructure • Very beneficial for GSA
  • 5. 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
  • 6. Expectations • To develop and implement the RDM policy throughout the school • Raise awareness of staff • Understand what research data is • Understand further what funders are expecting of HEIs
  • 7. Process • Environmental Assessment • User Requirements, systems evaluation and piloting • Policy formation • Capacity building • Sustainability • Dissemination
  • 8. Environmental Assessment • Discover, Create and pilot • 4 researchers from each institute a sectoral model of best chosen, from a broad range of practice in the disciplines management of research • Areas discussed data in the arts - Terminology • What is research data in - Role of the visual arts researcher the arts? - Creation of visual arts research • How can visual arts data data be managed appropriately - Use/re-use of visual arts data - Visual arts data in the longer term
  • 9. Interview Findings • The term ‘research data’ was not helpful • Researchers undertake multiple roles • Creation of data altered • Awareness of use and re-use present • Importance of archiving raised • Little consensus in the visual arts on what research data is • Described as tangible, intangible, digital, and physical • Visual arts data is heterogeneous and infinite, complex and complicated
  • 10. Quote from a researcher: “… I am not sure what constitutes research data… What is data? I mean, I talk to you about my data as a researcher, but for the institution, what does it consider data? Would it be conference proceedings, would a performance be data even if it was not recorded, sometimes I don’t record my performances…”
  • 11. Definition “Research data means data in the form of facts, observations, images, computer program results, recordings, measurement or experiences on which a research output is based. Data maybe numerical, descriptive, visual or tactile. It may be raw, cleaned or processed, and may be held in any format or media. Research data in the arts mirrors the complexity of the outputs, taking many forms including logbooks, journals, workbooks, sample libraries, sketchbooks, sets of images, video recordings, trials, prototypes, ceramic glaze recipes, found objects, and correspondence. Provenance information about the data might also be included: the how, when, where it was collected and with what. This metadata facilitates later interpretation and re-use of data"
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18. Additional Outputs • DCC Roadshows • International Open Repository Conference • http://www.youtube.com/watch?v=tbG1Tg9_0l8
  • 19. Teaching and Training Methods, Methodologies and Techniques MRes students and early career researchers
  • 20. Teaching and Training Being Boring By Wendy Cope If you ask me ‘What’s new?’, I have nothing to say Except that the garden is growing I had a slight cold but it’s better today I’m content with the way things are going Yes, he is the same as he usually is Still eating and sleeping and snoring I get on with my work. He gets on with his I know this is all very boring...
  • 22. Why Manage Research Data? • What are the drivers and incentives for management of research data? • Who benefits? • Funder Requirements • Institutional Requirements • Good practice in research
  • 23. Funder Requirements • EPSRC • AHRC • Policies required to • Technical Summary secure funding by • “We expect all or research projects to have some form of documentation 1st May 2015 of the research process, which • Road map usually takes the form of textual analysis or explanation to support development and the research’s position and to data management demonstrate critical reflection” plans
  • 24. Policy Development • Involvement of Kaptur and Support from project partners • Liaison with outside sources – e.g. the DCC • Attendance at events – Conference in Leeds • Involvement of interested parties at GSA – IT, Information Services and the Library, Research Office, Researchers • Existing policies and procedures and plans
  • 25. Approach • Context • Iterative process • Definition of research data • Discussions held • Policy statements • Obtaining feedback • Implementation methods • Sign off and agreement
  • 26. The Policy Roles and Preservation Responsibilities • The Glasgow School of • Data curation/retention Art • Presentation and • Individual Researchers showcasing work • IT • Selection process • Information Services • FOI • The Research Office • Institutional policies and guidelines/strategies
  • 27. Data Management, Methods Research Repository Other Software • DCC tools • DMP Online • https://dmponline.dcc.ac.uk/ • Free data management planning tool • Includes AHRC technical plan and others • Can be customised
  • 28. Comments Challenges: Lessons Learnt: • Building the support • Identify the correct people network at GSA to engage with • Extensive focus on the • Formulate an action plan REF process for development • Changes in management • Communicate • Expressing the • Obtain by-in early on importance of policies • EPSRC letter • RDM Understanding
  • 29. Next Steps and Key Points 1. Engage early with interested departments 2. Engage with end users 3. Engage with external bodies 4. Research data in the arts is not simple 5. Be aware of the varying nature of arts research data 6. Ensure suitable processes are in place for policy development 7. Be aware of requirements from • Further approval of the policy funders 8. Provide adequate teaching and • Implementation of Policy within training the ethos of research at GSA 9. Ensure suitable institutional infrastructure is in place • Support from Learning 10. Be aware of the views of the Resources and Research individual Office
  • 30. Acknowledgements • The project officers from partner institutes • VADS • JISC for sponsoring the project • DCC • Artwork images – By Burgess&Bear • (http://www.facebook.com/BurgessBear) THANKYOU! http://www.vads.ac.uk/kaptur/