SlideShare ist ein Scribd-Unternehmen logo
1 von 41
Research Data Management:
a gentle introduction
Martin Donnelly, Digital Curation Centre, University of Edinburgh
CLS Live, University of Huddersfield, 3 June 2014
OVERVIEW
1. Introductions and definitions
 The Digital Curation Centre
 Research data management
 What do we mean by ‘data’, exactly?
2. Data as a hot topic: politics and practical concerns
3. Barriers and current activities
 Quick interactive session
4. Support and resources
 A few rules of thumb / do’s and don’ts
 Take-home messages
1. INTRODUCTIONS AND DEFINITIONS
The Digital Curation Centre
 The (est. 2004) is…
 A UK centre of expertise in digital
preservation, with a particular focus on
research data management (RDM)
 Based across three sites: Universities of
Edinburgh, Glasgow and Bath
 Working with a number of UK universities
to identify gaps in RDM provision and
raise capabilities across the sector
 Also involved in a variety of international
collaborations
Working with UK universities
DCC networks and partnerships
What is RD(M)?
“the active management and
appraisal of data over the
lifecycle of scholarly and
scientific interest”
Data management is a part of
good research practice.
- RCUK Policy and Code of Conduct on the
Governance of Good Research Conduct
The old way of doing things
1. Researcher collects data (information)
2. Researcher interprets/synthesises data
3. Researcher writes paper based on data
4. Paper is published (and preserved)
5. Data is left to benign neglect, and
eventually ceases to be accessible
The new way of doing things
Plan
Collect
Assure
Describe
Preserve
Discover
Integrate
Analyze
SHARE
…and
RE-USE
The DataONE
lifecycle model
Helicopter view:What are the benefits of RDM?
 TRANSPARENCY: The data that underpins research
can be made open for anyone to scrutinise, and
attempt to replicate findings.
 EFFICIENCY: Data collection can be funded once, and
used many times for a variety of purposes.
 RISK MANAGEMENT: A pro-active approach to data
management reduces the risk of inappropriate
disclosure of sensitive data, whether commercial or
personal.
 PRESERVATION: Lots of data is unique, and can only
be captured once. If lost, it can’t be replaced.
 Definitions vary from discipline to discipline, and from funder to funder…
 Here’s a science-centric definition:
 “The recorded factual material commonly accepted in the scientific community as
necessary to validate research findings.” (US Office of Management and Budget,
Circular 110)
 [Addendum: This policy applies to scientific collections, known in some disciplines
as institutional collections, permanent collections, archival collections, museum
collections, or voucher collections, which are assets with long-term scientific value.
(US Office of Science and Technology Policy, Memorandum, 20 March 2014)]
 And another from the visual arts:
 “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.”
(Leigh Garrett, KAPTUR project: see http://kaptur.wordpress.com/
2013/01/23/what-is-visual-arts-research-data-revisited/)
Okay, but what is ‘data’ exactly?
2. POLITICS AND PRACTICAL CONCERNS
Nature, 09/08 Economist, 02/10
Popular Science,Science, 02/11
Nature, 09/09ACM, 12/08
InformationWeek, 08/10 Computerworld,
A hot topic: 5 years of front pages…
 Developments in sensor technology,
networking and digital storage enable
new research and scientific paradigms
 As costs also fall, possibilities for data
sharing, citation and re-use become
much more widespread
 Journals dedicated solely to publishing
data have even started to appear. That’s
not to say it’s an entirely new thing:
journals have always published data,
just never before at such scale…
Technology
Rosse
from
Philosophical
Transactions of
the Royal Society,
(MDCCCLXI) (or
1861 if you’d
prefer)
Repurposing /VfM via data re-use
Ships’ log books build picture of climate
change 14 October 2010
You can now help scientists understand the
climate of the past and unearth new historical
information by revisiting the voyages of First
World War Royal Navy warships.
Visitors to OldWeather.org will be able to
retrace the routes taken by any of 280 Royal
Navy ships. These include historic vessels such
as HMS Caroline, the last survivor of the 1916
Battle of Jutland still afloat. By transcribing
information about the weather and interesting
events from images of each ship's logbook, web
volunteers will help scientists build a more
accurate picture of how our climate has
changed over the last century.
http://www.nationalarchives.gov.uk/news/503.
htm
Detail from Royal Navy Recruitment poster, RNVR
Signals branch, 1917 (Catalogue reference: ADM
1/8331)
Endeavour, 1768-71
(Captain Cook)
HMS Beagle,
1830-34
HMS Torch,
1918
6.9 The Research Councils expect the researchers they fund
to deposit published articles or conference proceedings in
an open access repository at or around the time of
publication. But this practice is unevenly enforced.
Therefore, as an immediate step, we have asked the
Research Councils to ensure the researchers they fund
fulfil the current requirements. Additionally, the Research
Councils have now agreed to invest £2 million in the
development, by 2013, of a UK ‘Gateway to Research’. In
the first instance this will allow ready access to Research
Council funded research information and related data but
it will be designed so that it can also include research
funded by others in due course. The Research Councils will
work with their partners and users to ensure information is
presented in a readily reusable form, using common
formats and open standards.
Government pressure/support
http://www.bis.gov.uk/assets/biscor
e/innovation/docs/i/11-1387-
innovation-and-research-strategy-
for-growth.pdf
Funder principles/expectations
1. Public good
2. Preservation
3. Discovery
4. Confidentiality
5. First use
6. Recognition
7. Public funding
Six of the seven RCUK
councils require data
management plans (or
equivalent), as do
Wellcome Trust, Cancer
Research UK, and more…
Meanwhile, in the USA…
(Aside: Open Data)
 Open Data is a philosophy, underpinned by
pragmatism… transparency + utility.
 “Open data is the idea that certain data should be
freely available to everyone to use and republish as
they wish, without restrictions from copyright, patents
or other mechanisms of control.” – Wikipedia
 Governments, cities etc are all getting onboard
 Open Knowledge Foundation is basically the political /
activist wing: http://okfn.org/
 From the government / industry side, we have the
Open Data Institute: http://theodi.org/
Controversial FOI requests to…
- University of East Anglia
- Queens University Belfast
- University of Stirling
Risk management
- Reinhart & Rogoff (2010) “Growth in a Time of Debt” - paper not peer-reviewed, data
not initially made available…
- Very influential and repeatedly cited by politicians to lend weight to economic strategy
- Multiple issues (selective exclusions, unconventional weightings, coding error)
identified by a postgrad researcher attempting to replicate the paper’s findings
- Widespread embarrassment, but at least the errors were discovered!
Research quality and integrity
3. BARRIERS AND CURRENT ACTIVITIES
Why don’t we live in a data sharing utopia?
 Four main reasons…
 Lack of understanding of the fundamental
issues
 Lack of joined-up thinking within
institutions, countries, internationally…
 Issues around ownership / privacy
 Technical/financial limitations and the need
for appraisal
What are UK HEIs doing about it?
 Three principal areas of focus
 Developing and integrating their technical
infrastructure (storage space, repositories/
CRIS systems, data catalogues, etc)
 Developing human infrastructure (creating
policies, assessing current data management
capabilities, identifying areas of good practice,
data management plan templates, tailoring
training and guidance materials…)
 Developing business plans for sustainable
services / roles
 Forming cross-function (hybrid) working groups,
advisory groups, task forces, etc…
http://blog.soton.ac.uk/keepi
t/2010/01/28/aida-and-
institutional-wobbliness/
Quick interactive session: data management
planning
 Checklist for a Data
Management Plan, v4.0
(2013)
www.dcc.ac.uk/resource
s/data-management-
plans
 Questions
 How confident would
you be about completing
each section?
 What help or advice is
available in the
university?
DMP SECTIONS
1. Administrative Data, e.g. project name,
description, PI, funder, etc
2. Data Collection, e.g. description, capture
methods, etc
3. Documentation and Metadata, e.g. what
information is needed for the data to be to be
accessed and understood in the future?
4. Ethics and Legal Compliance, e.g. consent,
sensitivity, copyright/IPR
5. Storage and Backup, e.g. where will data be
held and backed up? Security and access
issues
6. Selection and Preservation, e.g. keep it all or
just some? How long should it be kept?
7. Data Sharing, e.g. how will data be found and
accessed, any restrictions?
8. Responsibilities and Resources, e.g. who will
do it and who will pay?
Quick interactive session: data management
planning
 Outcomes
 It’s not necessary – or even desirable – for every researcher
to become expert in every aspect of data management
 Universities have an increasing obligation to provide
infrastructure and support
 Huddersfield have developed a dedicated web area at
https://www.hud.ac.uk/cls/researchdata/
 Specific expertise may also be available from the research
office, library, IT, departmental support staff, legal services,
etc…
4. SUPPORT
i. DCC resources
 Publications
The DCC publishes a series of themed Briefing Papers, How-To Guides
and Case Studies, pitched at different audiences / levels of detail
 http://www.dcc.ac.uk/resources/briefing-papers
 http://www.dcc.ac.uk/resources/how-guides
 http://www.dcc.ac.uk/resources/developing-rdm-services
 Training
 e.g. DC101 courses and Curation Reference Manual
 Advice
 e.g. Disciplinary metadata, www.dcc.ac.uk/resources/metadata-
standards
 Tools
 DMPonline, CARDIO, Data Asset Framework, DRAMBORA
 Events
 International Digital Curation Conference (most recent was in San
Francisco, February 2014)
 Research Data Management Forum (themed events – next one is
on Workflows and Lifecycle Models, London, 20 June 2014)
ii. Other resources
 Jisc services and resources
 RDM resources, www.jisc.ac.uk/guides/research-data-
management
 EDINA and Mimas (national data centres)
 JISCMRD projects – Phase 1 (2009-2011) and Phase 2 (2011-2013)
 1) Research Data Management Infrastructure (RDMI)
 2) Research Data Management Planning (RDMP)
 3) Support and Tools
 4) Citing, Linking, Integrating and Publishing Research Data (CLIP)
 5) Research Data Management Training Materials
 6) Enhancing DMPonline
 7) Events
 Universities
 Good materials are available from Edinburgh, Cambridge, Oxford,
Glasgow, Bristol, and many others
A few rules of thumb…
STORAGE
≠
MANAGEMENT
Greenhouse = storage
Horticulture = management
DATA
MANAGEMENT
≠
SHARING
But! You generally
need a reason NOT to
share, e.g.
- Commercial interests
- Ethical concerns
- Data Protection Act
So… don’t share it all
Why not?
1. We probably can’t afford the
costs of storage: increasing
volumes outpace declining
storage hardware costs
and
2. We probably can’t afford the
time it will take to ensure it
remains
accessible/discoverable
According to: John Gantz and David Reinsel 2011 Extracting
Value from Chaos, http://www.emc.com/digital_universe
And… don’t keep it all
http://blog.dshr.org/2012/05/lets-just-keep-everything-forever-in.html
“Keeping 2018’s data in S3 would
cost the entire global GDP”
How to decide?
1. Relevance to Mission – including any legal/funder
requirement to retain the data beyond its
immediate use.
2. Scientific or Historical Value – significance and
relationship to publications etc.
3. Uniqueness – can it be found elsewhere / if we
don’t preserve it, who will?
4. Potential for Redistribution – quality / IP / ethical
concerns are addressed.
5. Non-Replicability – either impossible to replicate
(e.g. atmospheric or social science data) or not
financially viable.
6. Economic Case – costs of managing and
preserving the resource stack up well against
potential future benefits.
7. Full Documentation – surrounding / contextual
information necessary to facilitate future
discovery, access, and reuse is adequate.
How to Appraise & Select Research Data
for Curation
Angus Whyte, Digital Curation Centre,
and Andrew Wilson, Australian National
Data Service (2010)
A few do’s and don’ts
DO DON’T
Have a plan for your data Make it up as you go along
Keep backups. Make this easy with automated
syncing services like Dropbox, provided your
data isn’t too sensitive
Carry the only copy around on a memory card,
your laptop, your phone, etc
Describe your data as you collect it. This
makes it possible for others to interpret it, and
for you to do the same a few years down the
line
Leave this till later. The quality of metadata
decreases with time, and the best metadata is
created at the moment of data capture
Save your work in open file formats, where
possible, and use accepted metadata
standards to enable like-with-like comparison
Invent new ‘standards’ where community
norms already exist
Deposit your data in a data centre or
repository, and link it to your publications
Be afraid to ask for help. This will exist both
within your institution, and via national
support organisations like the DCC
Last slide: take-home messages
 Research data management (RDM) is…
 An integral part of doing quality research in the 21st
century
 Increasingly expected / mandated by funders,
publishers and others
 An opportunity for new discoveries and different
approaches to research
 A safeguard against inappropriate data disclosure
 An activity that requires careful planning and
consideration, and – ideally – coordination and support
across many stakeholder types
Thank you
Questions?
Image credits
Slide 2 (forest) – http://assets.worldwildlife.org/photos/934/images/hero_small/forest-overview-HI_115486.jpg?1345533675
Slide 3 (dictionary) – http://www.flickr.com/photos/dougbelshaw/
Slide 12 (politics) – https://www.flickr.com/photos/junglearctic/
Slide 23 (barriers) – http://www.flickr.com/photos/thetrapezium/
Slide 24 (utopia) – http://www.flickr.com/photos/burningmax/
Slide 28 (Thierry) – https://twitter.com/AFC_Fisher/
Slide 33 (greenhouse) – http://www.flickr.com/photos/mykl/
Slide 41 (love note) – http://www.edawax.de/wp-content/uploads/2013/01/Metadata_love250.jpg
Thanks to Sarah Callaghan, PREPARDE, for the Rosse example
This work is licensed under the
Creative Commons Attribution
2.5 UK: Scotland License.
For more about DCC services see www.dcc.ac.uk
or follow us on twitter @digitalcuration and #ukdcc
Martin Donnelly
Digital Curation Centre
University of Edinburgh
martin.donnelly@ed.ac.uk
@mkdDCC

Weitere ähnliche Inhalte

Was ist angesagt?

Research Data in the Arts and Humanities: A Few Tricky Questions
Research Data in the Arts and Humanities: A Few Tricky QuestionsResearch Data in the Arts and Humanities: A Few Tricky Questions
Research Data in the Arts and Humanities: A Few Tricky QuestionsMartin Donnelly
 
Data, Science, Society - Claudio Gutierrez, University of Chile
Data, Science, Society - Claudio Gutierrez, University of ChileData, Science, Society - Claudio Gutierrez, University of Chile
Data, Science, Society - Claudio Gutierrez, University of ChileLEARN Project
 
Open science, open data - FOSTER training, Potsdam
Open science, open data - FOSTER training, PotsdamOpen science, open data - FOSTER training, Potsdam
Open science, open data - FOSTER training, PotsdamPlatforma Otwartej Nauki
 
Research data management: a tale of two paradigms:
Research data management: a tale of two paradigms: Research data management: a tale of two paradigms:
Research data management: a tale of two paradigms: Martin Donnelly
 
Studying the Use of Glasgow University's Digital Collections
Studying the Use of Glasgow University's Digital CollectionsStudying the Use of Glasgow University's Digital Collections
Studying the Use of Glasgow University's Digital Collectionstarastar
 
From Open Data to Open Science, by Geoffrey Boulton
 From Open Data to Open Science, by Geoffrey Boulton From Open Data to Open Science, by Geoffrey Boulton
From Open Data to Open Science, by Geoffrey BoultonLEARN Project
 
Open Access and Open Data: what do I need to know (and do)?
Open Access and Open Data: what do I need to know (and do)?Open Access and Open Data: what do I need to know (and do)?
Open Access and Open Data: what do I need to know (and do)?Martin Donnelly
 
Research Data Management at the University of Edinburgh
Research Data Management at the University of EdinburghResearch Data Management at the University of Edinburgh
Research Data Management at the University of EdinburghEDINA, University of Edinburgh
 
The Challenges of Making Data Travel, by Sabina Leonelli
The Challenges of Making Data Travel, by Sabina LeonelliThe Challenges of Making Data Travel, by Sabina Leonelli
The Challenges of Making Data Travel, by Sabina LeonelliLEARN Project
 
The Future of Open Science
The Future of Open ScienceThe Future of Open Science
The Future of Open SciencePhilip Bourne
 
Liberating facts from the scientific literature - Jisc Digifest 2016
Liberating facts from the scientific literature - Jisc Digifest 2016Liberating facts from the scientific literature - Jisc Digifest 2016
Liberating facts from the scientific literature - Jisc Digifest 2016Jisc
 
How can we ensure research data is re-usable? The role of Publishers in Resea...
How can we ensure research data is re-usable? The role of Publishers in Resea...How can we ensure research data is re-usable? The role of Publishers in Resea...
How can we ensure research data is re-usable? The role of Publishers in Resea...LEARN Project
 
How to overcome obstacles to data publication: Issues, requirements, and good...
How to overcome obstacles to data publication: Issues, requirements, and good...How to overcome obstacles to data publication: Issues, requirements, and good...
How to overcome obstacles to data publication: Issues, requirements, and good...ariadnenetwork
 
Research Data in an Open Science World - Prof. Dr. Eva Mendez, uc3m
Research Data in an Open Science World - Prof. Dr. Eva Mendez, uc3mResearch Data in an Open Science World - Prof. Dr. Eva Mendez, uc3m
Research Data in an Open Science World - Prof. Dr. Eva Mendez, uc3mLEARN Project
 
Workshop at Oxford on publishing for early career researchers - April 2011
Workshop at Oxford on publishing for early career researchers - April 2011Workshop at Oxford on publishing for early career researchers - April 2011
Workshop at Oxford on publishing for early career researchers - April 2011Jisc
 
Meeting the Research Data Management Challenge - Rachel Bruce, Kevin Ashley, ...
Meeting the Research Data Management Challenge - Rachel Bruce, Kevin Ashley, ...Meeting the Research Data Management Challenge - Rachel Bruce, Kevin Ashley, ...
Meeting the Research Data Management Challenge - Rachel Bruce, Kevin Ashley, ...Jisc
 
Open Data in a Big Data World: easy to say, but hard to do?
Open Data in a Big Data World: easy to say, but hard to do?Open Data in a Big Data World: easy to say, but hard to do?
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
 
Data management: The new frontier for libraries
Data management: The new frontier for librariesData management: The new frontier for libraries
Data management: The new frontier for librariesLEARN Project
 

Was ist angesagt? (20)

Research Data in the Arts and Humanities: A Few Tricky Questions
Research Data in the Arts and Humanities: A Few Tricky QuestionsResearch Data in the Arts and Humanities: A Few Tricky Questions
Research Data in the Arts and Humanities: A Few Tricky Questions
 
Data, Science, Society - Claudio Gutierrez, University of Chile
Data, Science, Society - Claudio Gutierrez, University of ChileData, Science, Society - Claudio Gutierrez, University of Chile
Data, Science, Society - Claudio Gutierrez, University of Chile
 
Open science, open data - FOSTER training, Potsdam
Open science, open data - FOSTER training, PotsdamOpen science, open data - FOSTER training, Potsdam
Open science, open data - FOSTER training, Potsdam
 
Research data management: a tale of two paradigms:
Research data management: a tale of two paradigms: Research data management: a tale of two paradigms:
Research data management: a tale of two paradigms:
 
Studying the Use of Glasgow University's Digital Collections
Studying the Use of Glasgow University's Digital CollectionsStudying the Use of Glasgow University's Digital Collections
Studying the Use of Glasgow University's Digital Collections
 
From Open Data to Open Science, by Geoffrey Boulton
 From Open Data to Open Science, by Geoffrey Boulton From Open Data to Open Science, by Geoffrey Boulton
From Open Data to Open Science, by Geoffrey Boulton
 
Open Access and Open Data: what do I need to know (and do)?
Open Access and Open Data: what do I need to know (and do)?Open Access and Open Data: what do I need to know (and do)?
Open Access and Open Data: what do I need to know (and do)?
 
Research Data Management at the University of Edinburgh
Research Data Management at the University of EdinburghResearch Data Management at the University of Edinburgh
Research Data Management at the University of Edinburgh
 
The Challenges of Making Data Travel, by Sabina Leonelli
The Challenges of Making Data Travel, by Sabina LeonelliThe Challenges of Making Data Travel, by Sabina Leonelli
The Challenges of Making Data Travel, by Sabina Leonelli
 
The Future of Open Science
The Future of Open ScienceThe Future of Open Science
The Future of Open Science
 
Liberating facts from the scientific literature - Jisc Digifest 2016
Liberating facts from the scientific literature - Jisc Digifest 2016Liberating facts from the scientific literature - Jisc Digifest 2016
Liberating facts from the scientific literature - Jisc Digifest 2016
 
How can we ensure research data is re-usable? The role of Publishers in Resea...
How can we ensure research data is re-usable? The role of Publishers in Resea...How can we ensure research data is re-usable? The role of Publishers in Resea...
How can we ensure research data is re-usable? The role of Publishers in Resea...
 
How to overcome obstacles to data publication: Issues, requirements, and good...
How to overcome obstacles to data publication: Issues, requirements, and good...How to overcome obstacles to data publication: Issues, requirements, and good...
How to overcome obstacles to data publication: Issues, requirements, and good...
 
Research Data in an Open Science World - Prof. Dr. Eva Mendez, uc3m
Research Data in an Open Science World - Prof. Dr. Eva Mendez, uc3mResearch Data in an Open Science World - Prof. Dr. Eva Mendez, uc3m
Research Data in an Open Science World - Prof. Dr. Eva Mendez, uc3m
 
Anita Eppelin: Open Access and Open Data in Germany: current political develo...
Anita Eppelin: Open Access and Open Data in Germany: current political develo...Anita Eppelin: Open Access and Open Data in Germany: current political develo...
Anita Eppelin: Open Access and Open Data in Germany: current political develo...
 
Workshop at Oxford on publishing for early career researchers - April 2011
Workshop at Oxford on publishing for early career researchers - April 2011Workshop at Oxford on publishing for early career researchers - April 2011
Workshop at Oxford on publishing for early career researchers - April 2011
 
Meeting the Research Data Management Challenge - Rachel Bruce, Kevin Ashley, ...
Meeting the Research Data Management Challenge - Rachel Bruce, Kevin Ashley, ...Meeting the Research Data Management Challenge - Rachel Bruce, Kevin Ashley, ...
Meeting the Research Data Management Challenge - Rachel Bruce, Kevin Ashley, ...
 
Open Data in a Big Data World: easy to say, but hard to do?
Open Data in a Big Data World: easy to say, but hard to do?Open Data in a Big Data World: easy to say, but hard to do?
Open Data in a Big Data World: easy to say, but hard to do?
 
Data management: The new frontier for libraries
Data management: The new frontier for librariesData management: The new frontier for libraries
Data management: The new frontier for libraries
 
The African Open Science Platform/Susan Veldsman
The African Open Science Platform/Susan VeldsmanThe African Open Science Platform/Susan Veldsman
The African Open Science Platform/Susan Veldsman
 

Ähnlich wie Research Data Management: a gentle introduction

Research Data Management: A Tale of Two Paradigms
Research Data Management: A Tale of Two ParadigmsResearch Data Management: A Tale of Two Paradigms
Research Data Management: A Tale of Two Paradigmstarastar
 
Research data management: definitions, drivers and resources
Research data management: definitions, drivers and resourcesResearch data management: definitions, drivers and resources
Research data management: definitions, drivers and resourcesMartin Donnelly
 
Digital Data Sharing: Opportunities and Challenges of Opening Research
Digital Data Sharing: Opportunities and Challenges of Opening ResearchDigital Data Sharing: Opportunities and Challenges of Opening Research
Digital Data Sharing: Opportunities and Challenges of Opening ResearchMartin Donnelly
 
Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)
Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)
Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)dri_ireland
 
UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...
UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...
UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...L Molloy
 
The FOSTER project - general overview
The FOSTER project - general overviewThe FOSTER project - general overview
The FOSTER project - general overviewMartin Donnelly
 
Gobinda Chowdhury
Gobinda ChowdhuryGobinda Chowdhury
Gobinda Chowdhurymaredata
 
Mind the Gap: Reflections on Data Policies and Practice
Mind the Gap: Reflections on Data Policies and PracticeMind the Gap: Reflections on Data Policies and Practice
Mind the Gap: Reflections on Data Policies and PracticeLizLyon
 
The Horizon 2020 Open Data Pilot
The Horizon 2020 Open Data PilotThe Horizon 2020 Open Data Pilot
The Horizon 2020 Open Data PilotMartin Donnelly
 
The Horizon2020 Open Data Pilot - OpenAIRE Webinar
The Horizon2020 Open Data Pilot - OpenAIRE WebinarThe Horizon2020 Open Data Pilot - OpenAIRE Webinar
The Horizon2020 Open Data Pilot - OpenAIRE WebinarMartin Donnelly
 
Introduction to digital curation
Introduction to digital curationIntroduction to digital curation
Introduction to digital curationMichael Day
 
Introduction to data support services and resources for public policy
Introduction to data support services and resources for public policyIntroduction to data support services and resources for public policy
Introduction to data support services and resources for public policyHistoric Environment Scotland
 
British Library Datasets Programme 2010
British Library Datasets Programme 2010British Library Datasets Programme 2010
British Library Datasets Programme 2010ALISS
 
Open Data - strategies for research data management & impact of best practices
Open Data - strategies for research data management & impact of best practicesOpen Data - strategies for research data management & impact of best practices
Open Data - strategies for research data management & impact of best practicesMartin Donnelly
 
Winning Horizon 2020 with Open Science
Winning Horizon 2020 with Open ScienceWinning Horizon 2020 with Open Science
Winning Horizon 2020 with Open ScienceMartin Donnelly
 
RDM LIASA webinar
RDM LIASA webinarRDM LIASA webinar
RDM LIASA webinarSarah Jones
 
Digital Resources for Open Science
Digital Resources for Open ScienceDigital Resources for Open Science
Digital Resources for Open ScienceMartin Donnelly
 
EOSC-hub: first steps towards realising EOSC vision
EOSC-hub: first steps towards realising EOSC visionEOSC-hub: first steps towards realising EOSC vision
EOSC-hub: first steps towards realising EOSC visionEUDAT
 
Moving OA to the scientific enterprise
Moving OA to the scientific enterpriseMoving OA to the scientific enterprise
Moving OA to the scientific enterpriseMichael Day
 
Services, policy, guidance and training: Improving research data management a...
Services, policy, guidance and training: Improving research data management a...Services, policy, guidance and training: Improving research data management a...
Services, policy, guidance and training: Improving research data management a...EDINA, University of Edinburgh
 

Ähnlich wie Research Data Management: a gentle introduction (20)

Research Data Management: A Tale of Two Paradigms
Research Data Management: A Tale of Two ParadigmsResearch Data Management: A Tale of Two Paradigms
Research Data Management: A Tale of Two Paradigms
 
Research data management: definitions, drivers and resources
Research data management: definitions, drivers and resourcesResearch data management: definitions, drivers and resources
Research data management: definitions, drivers and resources
 
Digital Data Sharing: Opportunities and Challenges of Opening Research
Digital Data Sharing: Opportunities and Challenges of Opening ResearchDigital Data Sharing: Opportunities and Challenges of Opening Research
Digital Data Sharing: Opportunities and Challenges of Opening Research
 
Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)
Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)
Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)
 
UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...
UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...
UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...
 
The FOSTER project - general overview
The FOSTER project - general overviewThe FOSTER project - general overview
The FOSTER project - general overview
 
Gobinda Chowdhury
Gobinda ChowdhuryGobinda Chowdhury
Gobinda Chowdhury
 
Mind the Gap: Reflections on Data Policies and Practice
Mind the Gap: Reflections on Data Policies and PracticeMind the Gap: Reflections on Data Policies and Practice
Mind the Gap: Reflections on Data Policies and Practice
 
The Horizon 2020 Open Data Pilot
The Horizon 2020 Open Data PilotThe Horizon 2020 Open Data Pilot
The Horizon 2020 Open Data Pilot
 
The Horizon2020 Open Data Pilot - OpenAIRE Webinar
The Horizon2020 Open Data Pilot - OpenAIRE WebinarThe Horizon2020 Open Data Pilot - OpenAIRE Webinar
The Horizon2020 Open Data Pilot - OpenAIRE Webinar
 
Introduction to digital curation
Introduction to digital curationIntroduction to digital curation
Introduction to digital curation
 
Introduction to data support services and resources for public policy
Introduction to data support services and resources for public policyIntroduction to data support services and resources for public policy
Introduction to data support services and resources for public policy
 
British Library Datasets Programme 2010
British Library Datasets Programme 2010British Library Datasets Programme 2010
British Library Datasets Programme 2010
 
Open Data - strategies for research data management & impact of best practices
Open Data - strategies for research data management & impact of best practicesOpen Data - strategies for research data management & impact of best practices
Open Data - strategies for research data management & impact of best practices
 
Winning Horizon 2020 with Open Science
Winning Horizon 2020 with Open ScienceWinning Horizon 2020 with Open Science
Winning Horizon 2020 with Open Science
 
RDM LIASA webinar
RDM LIASA webinarRDM LIASA webinar
RDM LIASA webinar
 
Digital Resources for Open Science
Digital Resources for Open ScienceDigital Resources for Open Science
Digital Resources for Open Science
 
EOSC-hub: first steps towards realising EOSC vision
EOSC-hub: first steps towards realising EOSC visionEOSC-hub: first steps towards realising EOSC vision
EOSC-hub: first steps towards realising EOSC vision
 
Moving OA to the scientific enterprise
Moving OA to the scientific enterpriseMoving OA to the scientific enterprise
Moving OA to the scientific enterprise
 
Services, policy, guidance and training: Improving research data management a...
Services, policy, guidance and training: Improving research data management a...Services, policy, guidance and training: Improving research data management a...
Services, policy, guidance and training: Improving research data management a...
 

Mehr von Martin Donnelly

Open Data: Strategies for Research Data Management (and Planning)
Open Data: Strategies for Research Data  Management (and Planning)Open Data: Strategies for Research Data  Management (and Planning)
Open Data: Strategies for Research Data Management (and Planning)Martin Donnelly
 
Open Data Strategies and Research Data Realities
Open Data Strategies and Research Data RealitiesOpen Data Strategies and Research Data Realities
Open Data Strategies and Research Data RealitiesMartin Donnelly
 
Horizon 2020 open access and open data mandates
Horizon 2020 open access and open data mandatesHorizon 2020 open access and open data mandates
Horizon 2020 open access and open data mandatesMartin Donnelly
 
Preparing your own data for future re-use: data management and the FAIR prin...
Preparing your own data for future re-use:  data management and the FAIR prin...Preparing your own data for future re-use:  data management and the FAIR prin...
Preparing your own data for future re-use: data management and the FAIR prin...Martin Donnelly
 
Developing a Data Management Plan
Developing a Data Management PlanDeveloping a Data Management Plan
Developing a Data Management PlanMartin Donnelly
 
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
 
Practical Research Data Management: tools and approaches, pre- and post-award
Practical Research Data Management:  tools and approaches, pre- and post-awardPractical Research Data Management:  tools and approaches, pre- and post-award
Practical Research Data Management: tools and approaches, pre- and post-awardMartin Donnelly
 
Data management plans and planning - a gentle introduction
Data management plans and planning - a gentle introductionData management plans and planning - a gentle introduction
Data management plans and planning - a gentle introductionMartin Donnelly
 
Open Access to Research Data: Challenges and Solutions
Open Access to Research Data: Challenges and SolutionsOpen Access to Research Data: Challenges and Solutions
Open Access to Research Data: Challenges and SolutionsMartin Donnelly
 
Open Science and Horizon 2020
Open Science and Horizon 2020Open Science and Horizon 2020
Open Science and Horizon 2020Martin Donnelly
 
Data Management Plans: a gentle introduction
Data Management Plans: a gentle introductionData Management Plans: a gentle introduction
Data Management Plans: a gentle introductionMartin Donnelly
 
Future agenda: repositories, and the research process
Future agenda: repositories, and the research processFuture agenda: repositories, and the research process
Future agenda: repositories, and the research process Martin Donnelly
 
'Found' and 'after' - a short history of data reuse in the arts
'Found' and 'after' - a short history of data reuse in the arts'Found' and 'after' - a short history of data reuse in the arts
'Found' and 'after' - a short history of data reuse in the artsMartin Donnelly
 
Data management planning: the what, the why, the who, the how
Data management planning: the what, the why, the who, the howData management planning: the what, the why, the who, the how
Data management planning: the what, the why, the who, the howMartin Donnelly
 

Mehr von Martin Donnelly (16)

The Roots of DMPonline
The Roots of DMPonlineThe Roots of DMPonline
The Roots of DMPonline
 
Open Data: Strategies for Research Data Management (and Planning)
Open Data: Strategies for Research Data  Management (and Planning)Open Data: Strategies for Research Data  Management (and Planning)
Open Data: Strategies for Research Data Management (and Planning)
 
Open Data Strategies and Research Data Realities
Open Data Strategies and Research Data RealitiesOpen Data Strategies and Research Data Realities
Open Data Strategies and Research Data Realities
 
Horizon 2020 open access and open data mandates
Horizon 2020 open access and open data mandatesHorizon 2020 open access and open data mandates
Horizon 2020 open access and open data mandates
 
Preparing your own data for future re-use: data management and the FAIR prin...
Preparing your own data for future re-use:  data management and the FAIR prin...Preparing your own data for future re-use:  data management and the FAIR prin...
Preparing your own data for future re-use: data management and the FAIR prin...
 
Developing a Data Management Plan
Developing a Data Management PlanDeveloping a Data Management Plan
Developing a Data Management Plan
 
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
 
Practical Research Data Management: tools and approaches, pre- and post-award
Practical Research Data Management:  tools and approaches, pre- and post-awardPractical Research Data Management:  tools and approaches, pre- and post-award
Practical Research Data Management: tools and approaches, pre- and post-award
 
Data management plans and planning - a gentle introduction
Data management plans and planning - a gentle introductionData management plans and planning - a gentle introduction
Data management plans and planning - a gentle introduction
 
Open Access to Research Data: Challenges and Solutions
Open Access to Research Data: Challenges and SolutionsOpen Access to Research Data: Challenges and Solutions
Open Access to Research Data: Challenges and Solutions
 
Open Science and Horizon 2020
Open Science and Horizon 2020Open Science and Horizon 2020
Open Science and Horizon 2020
 
Data Management Plans: a gentle introduction
Data Management Plans: a gentle introductionData Management Plans: a gentle introduction
Data Management Plans: a gentle introduction
 
Future agenda: repositories, and the research process
Future agenda: repositories, and the research processFuture agenda: repositories, and the research process
Future agenda: repositories, and the research process
 
'Found' and 'after' - a short history of data reuse in the arts
'Found' and 'after' - a short history of data reuse in the arts'Found' and 'after' - a short history of data reuse in the arts
'Found' and 'after' - a short history of data reuse in the arts
 
Data management planning: the what, the why, the who, the how
Data management planning: the what, the why, the who, the howData management planning: the what, the why, the who, the how
Data management planning: the what, the why, the who, the how
 
DMP Online: update 2013
DMP Online: update 2013DMP Online: update 2013
DMP Online: update 2013
 

Kürzlich hochgeladen

Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfSherif Taha
 
Graduate Outcomes Presentation Slides - English
Graduate Outcomes Presentation Slides - EnglishGraduate Outcomes Presentation Slides - English
Graduate Outcomes Presentation Slides - Englishneillewis46
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxRamakrishna Reddy Bijjam
 
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...pradhanghanshyam7136
 
Vishram Singh - Textbook of Anatomy Upper Limb and Thorax.. Volume 1 (1).pdf
Vishram Singh - Textbook of Anatomy  Upper Limb and Thorax.. Volume 1 (1).pdfVishram Singh - Textbook of Anatomy  Upper Limb and Thorax.. Volume 1 (1).pdf
Vishram Singh - Textbook of Anatomy Upper Limb and Thorax.. Volume 1 (1).pdfssuserdda66b
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfAdmir Softic
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxVishalSingh1417
 
Single or Multiple melodic lines structure
Single or Multiple melodic lines structureSingle or Multiple melodic lines structure
Single or Multiple melodic lines structuredhanjurrannsibayan2
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...ZurliaSoop
 
Dyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxDyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxcallscotland1987
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxDenish Jangid
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17Celine George
 
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin ClassesCeline George
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual  Proper...General Principles of Intellectual Property: Concepts of Intellectual  Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...Poonam Aher Patil
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Association for Project Management
 
Micro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfMicro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfPoh-Sun Goh
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentationcamerronhm
 

Kürzlich hochgeladen (20)

Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdf
 
Graduate Outcomes Presentation Slides - English
Graduate Outcomes Presentation Slides - EnglishGraduate Outcomes Presentation Slides - English
Graduate Outcomes Presentation Slides - English
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docx
 
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...Kodo Millet  PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
Kodo Millet PPT made by Ghanshyam bairwa college of Agriculture kumher bhara...
 
Vishram Singh - Textbook of Anatomy Upper Limb and Thorax.. Volume 1 (1).pdf
Vishram Singh - Textbook of Anatomy  Upper Limb and Thorax.. Volume 1 (1).pdfVishram Singh - Textbook of Anatomy  Upper Limb and Thorax.. Volume 1 (1).pdf
Vishram Singh - Textbook of Anatomy Upper Limb and Thorax.. Volume 1 (1).pdf
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
Unit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptxUnit-V; Pricing (Pharma Marketing Management).pptx
Unit-V; Pricing (Pharma Marketing Management).pptx
 
Single or Multiple melodic lines structure
Single or Multiple melodic lines structureSingle or Multiple melodic lines structure
Single or Multiple melodic lines structure
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
 
Dyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptxDyslexia AI Workshop for Slideshare.pptx
Dyslexia AI Workshop for Slideshare.pptx
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 
Spatium Project Simulation student brief
Spatium Project Simulation student briefSpatium Project Simulation student brief
Spatium Project Simulation student brief
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17
 
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17  How to Extend Models Using Mixin ClassesMixin Classes in Odoo 17  How to Extend Models Using Mixin Classes
Mixin Classes in Odoo 17 How to Extend Models Using Mixin Classes
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual  Proper...General Principles of Intellectual Property: Concepts of Intellectual  Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...
 
Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...Making communications land - Are they received and understood as intended? we...
Making communications land - Are they received and understood as intended? we...
 
Micro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfMicro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdf
 
SOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning PresentationSOC 101 Demonstration of Learning Presentation
SOC 101 Demonstration of Learning Presentation
 

Research Data Management: a gentle introduction

  • 1. Research Data Management: a gentle introduction Martin Donnelly, Digital Curation Centre, University of Edinburgh CLS Live, University of Huddersfield, 3 June 2014
  • 2. OVERVIEW 1. Introductions and definitions  The Digital Curation Centre  Research data management  What do we mean by ‘data’, exactly? 2. Data as a hot topic: politics and practical concerns 3. Barriers and current activities  Quick interactive session 4. Support and resources  A few rules of thumb / do’s and don’ts  Take-home messages
  • 3. 1. INTRODUCTIONS AND DEFINITIONS
  • 4. The Digital Curation Centre  The (est. 2004) is…  A UK centre of expertise in digital preservation, with a particular focus on research data management (RDM)  Based across three sites: Universities of Edinburgh, Glasgow and Bath  Working with a number of UK universities to identify gaps in RDM provision and raise capabilities across the sector  Also involved in a variety of international collaborations
  • 5. Working with UK universities
  • 6. DCC networks and partnerships
  • 7. What is RD(M)? “the active management and appraisal of data over the lifecycle of scholarly and scientific interest” Data management is a part of good research practice. - RCUK Policy and Code of Conduct on the Governance of Good Research Conduct
  • 8. The old way of doing things 1. Researcher collects data (information) 2. Researcher interprets/synthesises data 3. Researcher writes paper based on data 4. Paper is published (and preserved) 5. Data is left to benign neglect, and eventually ceases to be accessible
  • 9. The new way of doing things Plan Collect Assure Describe Preserve Discover Integrate Analyze SHARE …and RE-USE The DataONE lifecycle model
  • 10. Helicopter view:What are the benefits of RDM?  TRANSPARENCY: The data that underpins research can be made open for anyone to scrutinise, and attempt to replicate findings.  EFFICIENCY: Data collection can be funded once, and used many times for a variety of purposes.  RISK MANAGEMENT: A pro-active approach to data management reduces the risk of inappropriate disclosure of sensitive data, whether commercial or personal.  PRESERVATION: Lots of data is unique, and can only be captured once. If lost, it can’t be replaced.
  • 11.  Definitions vary from discipline to discipline, and from funder to funder…  Here’s a science-centric definition:  “The recorded factual material commonly accepted in the scientific community as necessary to validate research findings.” (US Office of Management and Budget, Circular 110)  [Addendum: This policy applies to scientific collections, known in some disciplines as institutional collections, permanent collections, archival collections, museum collections, or voucher collections, which are assets with long-term scientific value. (US Office of Science and Technology Policy, Memorandum, 20 March 2014)]  And another from the visual arts:  “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.” (Leigh Garrett, KAPTUR project: see http://kaptur.wordpress.com/ 2013/01/23/what-is-visual-arts-research-data-revisited/) Okay, but what is ‘data’ exactly?
  • 12. 2. POLITICS AND PRACTICAL CONCERNS
  • 13. Nature, 09/08 Economist, 02/10 Popular Science,Science, 02/11 Nature, 09/09ACM, 12/08 InformationWeek, 08/10 Computerworld, A hot topic: 5 years of front pages…
  • 14.  Developments in sensor technology, networking and digital storage enable new research and scientific paradigms  As costs also fall, possibilities for data sharing, citation and re-use become much more widespread  Journals dedicated solely to publishing data have even started to appear. That’s not to say it’s an entirely new thing: journals have always published data, just never before at such scale… Technology
  • 15. Rosse from Philosophical Transactions of the Royal Society, (MDCCCLXI) (or 1861 if you’d prefer)
  • 16. Repurposing /VfM via data re-use Ships’ log books build picture of climate change 14 October 2010 You can now help scientists understand the climate of the past and unearth new historical information by revisiting the voyages of First World War Royal Navy warships. Visitors to OldWeather.org will be able to retrace the routes taken by any of 280 Royal Navy ships. These include historic vessels such as HMS Caroline, the last survivor of the 1916 Battle of Jutland still afloat. By transcribing information about the weather and interesting events from images of each ship's logbook, web volunteers will help scientists build a more accurate picture of how our climate has changed over the last century. http://www.nationalarchives.gov.uk/news/503. htm Detail from Royal Navy Recruitment poster, RNVR Signals branch, 1917 (Catalogue reference: ADM 1/8331) Endeavour, 1768-71 (Captain Cook) HMS Beagle, 1830-34 HMS Torch, 1918
  • 17. 6.9 The Research Councils expect the researchers they fund to deposit published articles or conference proceedings in an open access repository at or around the time of publication. But this practice is unevenly enforced. Therefore, as an immediate step, we have asked the Research Councils to ensure the researchers they fund fulfil the current requirements. Additionally, the Research Councils have now agreed to invest £2 million in the development, by 2013, of a UK ‘Gateway to Research’. In the first instance this will allow ready access to Research Council funded research information and related data but it will be designed so that it can also include research funded by others in due course. The Research Councils will work with their partners and users to ensure information is presented in a readily reusable form, using common formats and open standards. Government pressure/support http://www.bis.gov.uk/assets/biscor e/innovation/docs/i/11-1387- innovation-and-research-strategy- for-growth.pdf
  • 18. Funder principles/expectations 1. Public good 2. Preservation 3. Discovery 4. Confidentiality 5. First use 6. Recognition 7. Public funding Six of the seven RCUK councils require data management plans (or equivalent), as do Wellcome Trust, Cancer Research UK, and more…
  • 20. (Aside: Open Data)  Open Data is a philosophy, underpinned by pragmatism… transparency + utility.  “Open data is the idea that certain data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control.” – Wikipedia  Governments, cities etc are all getting onboard  Open Knowledge Foundation is basically the political / activist wing: http://okfn.org/  From the government / industry side, we have the Open Data Institute: http://theodi.org/
  • 21. Controversial FOI requests to… - University of East Anglia - Queens University Belfast - University of Stirling Risk management
  • 22. - Reinhart & Rogoff (2010) “Growth in a Time of Debt” - paper not peer-reviewed, data not initially made available… - Very influential and repeatedly cited by politicians to lend weight to economic strategy - Multiple issues (selective exclusions, unconventional weightings, coding error) identified by a postgrad researcher attempting to replicate the paper’s findings - Widespread embarrassment, but at least the errors were discovered! Research quality and integrity
  • 23. 3. BARRIERS AND CURRENT ACTIVITIES
  • 24. Why don’t we live in a data sharing utopia?  Four main reasons…  Lack of understanding of the fundamental issues  Lack of joined-up thinking within institutions, countries, internationally…  Issues around ownership / privacy  Technical/financial limitations and the need for appraisal
  • 25. What are UK HEIs doing about it?  Three principal areas of focus  Developing and integrating their technical infrastructure (storage space, repositories/ CRIS systems, data catalogues, etc)  Developing human infrastructure (creating policies, assessing current data management capabilities, identifying areas of good practice, data management plan templates, tailoring training and guidance materials…)  Developing business plans for sustainable services / roles  Forming cross-function (hybrid) working groups, advisory groups, task forces, etc… http://blog.soton.ac.uk/keepi t/2010/01/28/aida-and- institutional-wobbliness/
  • 26. Quick interactive session: data management planning  Checklist for a Data Management Plan, v4.0 (2013) www.dcc.ac.uk/resource s/data-management- plans  Questions  How confident would you be about completing each section?  What help or advice is available in the university? DMP SECTIONS 1. Administrative Data, e.g. project name, description, PI, funder, etc 2. Data Collection, e.g. description, capture methods, etc 3. Documentation and Metadata, e.g. what information is needed for the data to be to be accessed and understood in the future? 4. Ethics and Legal Compliance, e.g. consent, sensitivity, copyright/IPR 5. Storage and Backup, e.g. where will data be held and backed up? Security and access issues 6. Selection and Preservation, e.g. keep it all or just some? How long should it be kept? 7. Data Sharing, e.g. how will data be found and accessed, any restrictions? 8. Responsibilities and Resources, e.g. who will do it and who will pay?
  • 27. Quick interactive session: data management planning  Outcomes  It’s not necessary – or even desirable – for every researcher to become expert in every aspect of data management  Universities have an increasing obligation to provide infrastructure and support  Huddersfield have developed a dedicated web area at https://www.hud.ac.uk/cls/researchdata/  Specific expertise may also be available from the research office, library, IT, departmental support staff, legal services, etc…
  • 29. i. DCC resources  Publications The DCC publishes a series of themed Briefing Papers, How-To Guides and Case Studies, pitched at different audiences / levels of detail  http://www.dcc.ac.uk/resources/briefing-papers  http://www.dcc.ac.uk/resources/how-guides  http://www.dcc.ac.uk/resources/developing-rdm-services  Training  e.g. DC101 courses and Curation Reference Manual  Advice  e.g. Disciplinary metadata, www.dcc.ac.uk/resources/metadata- standards  Tools  DMPonline, CARDIO, Data Asset Framework, DRAMBORA  Events  International Digital Curation Conference (most recent was in San Francisco, February 2014)  Research Data Management Forum (themed events – next one is on Workflows and Lifecycle Models, London, 20 June 2014)
  • 30. ii. Other resources  Jisc services and resources  RDM resources, www.jisc.ac.uk/guides/research-data- management  EDINA and Mimas (national data centres)  JISCMRD projects – Phase 1 (2009-2011) and Phase 2 (2011-2013)  1) Research Data Management Infrastructure (RDMI)  2) Research Data Management Planning (RDMP)  3) Support and Tools  4) Citing, Linking, Integrating and Publishing Research Data (CLIP)  5) Research Data Management Training Materials  6) Enhancing DMPonline  7) Events  Universities  Good materials are available from Edinburgh, Cambridge, Oxford, Glasgow, Bristol, and many others
  • 31. A few rules of thumb…
  • 35. But! You generally need a reason NOT to share, e.g. - Commercial interests - Ethical concerns - Data Protection Act So… don’t share it all
  • 36. Why not? 1. We probably can’t afford the costs of storage: increasing volumes outpace declining storage hardware costs and 2. We probably can’t afford the time it will take to ensure it remains accessible/discoverable According to: John Gantz and David Reinsel 2011 Extracting Value from Chaos, http://www.emc.com/digital_universe And… don’t keep it all
  • 38. How to decide? 1. Relevance to Mission – including any legal/funder requirement to retain the data beyond its immediate use. 2. Scientific or Historical Value – significance and relationship to publications etc. 3. Uniqueness – can it be found elsewhere / if we don’t preserve it, who will? 4. Potential for Redistribution – quality / IP / ethical concerns are addressed. 5. Non-Replicability – either impossible to replicate (e.g. atmospheric or social science data) or not financially viable. 6. Economic Case – costs of managing and preserving the resource stack up well against potential future benefits. 7. Full Documentation – surrounding / contextual information necessary to facilitate future discovery, access, and reuse is adequate. How to Appraise & Select Research Data for Curation Angus Whyte, Digital Curation Centre, and Andrew Wilson, Australian National Data Service (2010)
  • 39. A few do’s and don’ts DO DON’T Have a plan for your data Make it up as you go along Keep backups. Make this easy with automated syncing services like Dropbox, provided your data isn’t too sensitive Carry the only copy around on a memory card, your laptop, your phone, etc Describe your data as you collect it. This makes it possible for others to interpret it, and for you to do the same a few years down the line Leave this till later. The quality of metadata decreases with time, and the best metadata is created at the moment of data capture Save your work in open file formats, where possible, and use accepted metadata standards to enable like-with-like comparison Invent new ‘standards’ where community norms already exist Deposit your data in a data centre or repository, and link it to your publications Be afraid to ask for help. This will exist both within your institution, and via national support organisations like the DCC
  • 40. Last slide: take-home messages  Research data management (RDM) is…  An integral part of doing quality research in the 21st century  Increasingly expected / mandated by funders, publishers and others  An opportunity for new discoveries and different approaches to research  A safeguard against inappropriate data disclosure  An activity that requires careful planning and consideration, and – ideally – coordination and support across many stakeholder types
  • 41. Thank you Questions? Image credits Slide 2 (forest) – http://assets.worldwildlife.org/photos/934/images/hero_small/forest-overview-HI_115486.jpg?1345533675 Slide 3 (dictionary) – http://www.flickr.com/photos/dougbelshaw/ Slide 12 (politics) – https://www.flickr.com/photos/junglearctic/ Slide 23 (barriers) – http://www.flickr.com/photos/thetrapezium/ Slide 24 (utopia) – http://www.flickr.com/photos/burningmax/ Slide 28 (Thierry) – https://twitter.com/AFC_Fisher/ Slide 33 (greenhouse) – http://www.flickr.com/photos/mykl/ Slide 41 (love note) – http://www.edawax.de/wp-content/uploads/2013/01/Metadata_love250.jpg Thanks to Sarah Callaghan, PREPARDE, for the Rosse example This work is licensed under the Creative Commons Attribution 2.5 UK: Scotland License. For more about DCC services see www.dcc.ac.uk or follow us on twitter @digitalcuration and #ukdcc Martin Donnelly Digital Curation Centre University of Edinburgh martin.donnelly@ed.ac.uk @mkdDCC

Hinweis der Redaktion

  1. First cohort of institutional engagements, 2011-2013
  2. Painting in broad strokes here, of course…
  3. Share = deposit, link, publish, etc
  4. Will unpack these over the course of the presentation, but first
  5. Think about what you do in your own research
  6. …and as the worlds of business and academia continue to merge… Interest in data is not limited to academia: the business world sees data as a valuable and potentially lucrative resource, a real game-changer…
  7. Earliest academic scientific journal is Journal des sçavans, published on 5 Jan 1665
  8. We can now publish and re-use data in a much more structured way, automating the process and crunching more data via computers than we could when it was only available on paper.
  9. https://www.youtube.com/watch?v=n603rEnEGXA
  10. Philip Morris International vs University of Stirling (2011) - another example of unanticipated data re-use! There’s a delicate balance between the rights of researchers, of human research subjects, of funders, and other interested stakeholders to enable or prevent access to research data…
  11. So, those are the benefits, but there are still barriers to this utopia…
  12. Forming cross-function (hybrid) working groups, advisory groups, task forces, etc
  13. IT departments in particular tend to think of data management as primarily a hardware/technical problem. It’s not – the human side is bigger
  14. The two main goal of data management are (1) to make data more widely accessible, and (2) to prevent access to sensitive data
  15. 2. Prioritise based on relationship with publications, e.g. underpins scientific record (c.f. Sarah Callaghan, Preparde) 5. Privilege irreproducible data…
  16. A DMP is a basic statement of how you will create, manage, share and preserve your data Funders expect the decisions to be justified, particularly where it’s not in line with their policy (e.g. limits on data sharing)