SlideShare a Scribd company logo
Digging into Data: looking back –
looking forward
Catherine Grout/ Stuart Dempster
Montreal, Palais de Congres
13th October 2013
Introduction
• To add context to aid
discussion for next
phase of the meeting
• To highlight key findings
and achievements of
DiD 1 and 2
• To suggest some future
ideas about directions
and next steps
DiD 1 and the CLIR report
•

For Round One, the Digging into Data
(DiD) Challenge was sponsored by
four research funders
(NEH, NSF, SSHRC, Jisc)

•

Funded 8 international projects

•

Achieved impact and acclaim via a
range of publications e.g. e New York
Times, Nature, Times Higher
Education, Globe and Mai letc.

•

DiD was also the subject of a major
research report published by the
Council on Library and Information
Resources(CLIR).

• CLIR report found that we need to:
1) Expand our concept of research
2) Expand our concept of research data
and accept the challenges that digital
research data present
3) Embrace interdisciplinarity
4) Take a more inclusive approach to
collaboration
5) Address gaps in training and skills
6) Adopt models for sharing credit
7) Adopt models for sharing resources
8) Re-envision scholarly publication
9) Make greater, sustained investments
in human and cyber infrastructure
DiD 2
•

For Round Two, four additional
funders joined
(IMLS, AHRC, ESRC, NWO) and the
Netherlands joined as a fourth
country.

•

14 projects won awards, chosen by
our international peer reviewers.
These 14 presented their work in
Montreal yesterday at the Digging
into Data Conference

•

These fourteen projects represent a
very wide variety of exciting
research, among them the IMPACT
project which made the headlines
when their paper in the Lancet
revealed that clogged arteries
plagued the ancient world.

• Some outcomes from Did 2 so
far
1) Exploiting what open access and open data
has enabled
2) New ways of visualising and interpreting
existing data and resources
3) Development of tools that can then be
applied to more contexts and data
4) Unanticipated and important new insights.
Throwing up new research questions.
5) Enabling precision as well as speed of
performance over very large datasets (like
Amazon)
6) Challenging boundaries between disciplines
and how you do the research process
7) Can anyone be a historian or sociologist if
they have the right data?
DiD 3 and onwards
•

Two new funders have joined DiD (CFI and NSERC), bringing us to a total of ten.

•

The Round Three projects will be announced in January of 2014.

•

DiD demonstrates a unique and field-proven method for international
cooperation among research agencies. Proposals are reviewed by an international
peer review committee jointly selected

•

Each applicant team must represent at least two countries. Awards made using a
“fund-own” system under which funders only pay for their own researchers.
Allows each funder to participate with minimal paperwork.

•

Multiple funders from a single country can work together (e.g. NEH, NSF, IMLS)
which makes interdisciplinary projects easier to fund.
DiD achievements (Channelling Brett)
• Pioneered and legitimised big data based research in the humanities – for
computer scientists and others. (‘from zero to hero’)
• “Digital humanities”, “computational social sciences” and others working
together (‘breaking boundaries’)
• Engage GLAM sector and others to encourage them to make their data
available in forms useful to researchers and to work with them
(encourages joint data curation)
• Progress on the policy side toward reforming copyright and IP to allow for
big data research on cultural heritage materials. (more to do here)
• International & multidisciplinary cooperation had high impact (more than
anticipated). Increased visibility also strengthened research bringing new
teams together (‘breaking new ground’)
DiD achievements (Brett and others)
•

Brought knowledge to the funders themselves through working with other
agencies, improving and transforming ideas. How can these lessons be
highlighted for us within other collaborative endeavors like the Transatlantic
Platform?

•

How might expanding the range of Digging funders help researchers expand the
breadth of their work? To find new partners and new perspectives using big data
research as a catalyst?

•

Project spanning domains (humanities, social science, and library/information
science). Create a new kind of research that would not be funded because of
boundaries between research councils and funder

•
•

Societal value. Service to humanity – important new findings effect people’s lives
Economic value. Health, crime, legal issues, efficiency gains - supports economy
Funders responses to big challenges
•
•

•
•
•
•
•
•
•
•

How might funders help?
‘Not enough to just say ‘open data’, but policies and procedures need to add
‘utility’ to ensure interoperable data. Open data mandates but with a data
curation, data standards (DOI, APIs etc.) and credit (data citation e.g. Harvard)
needed
Develop common methodologies of checking and re-analysis to see the
cumulative value and quality of data
Encourage the availability and analysis of data in real or near time (John Willinsky)
Encourage computational scientists, SSH researchers and digital libraries to work
together (data preservation).
Encourage permissive ‘model licences’ for public domain and copyrighted data
Encourage ‘credit’ career progression/tenure amongst host institutions
Develop sustainable and extensible shared digital infrastructure (grid, cloud etc.)
Encourage ‘good practice’ in ethics and governance (privacy etc.)
Encourage model legal and rights management approaches for (IPR) issues
Discussion
1.

Reactions – what are the main highlights so far?
Do you agree with Brett?
Are there other points?

2.

Where should/could Digging go next led
New research/Themes/ issues to be considered?
(Taking forward grantees feedback)
What is now done and finished (Implementing/embedding?)
T-AP context?
Is bigger better?

More Related Content

PDF
African Open Science Platform
PPT
The Role of Automated Function Prediction in the Era of Big Data and Small Bu...
PPTX
UKRDDS 1st Workshop 20150423 - gathering requirements
PPTX
Business case and cost modelling for an end-to-end RDM service
PPT
Ask Not What the NIH Can Do For You; Ask What You Can Do For the NIH
PPTX
Rubrics for DMPs
PDF
CODATA: Open Data, FAIR Data and Open Science/Simon Hodson
PPTX
Introducing Data and Text Mining at DigiFest
African Open Science Platform
The Role of Automated Function Prediction in the Era of Big Data and Small Bu...
UKRDDS 1st Workshop 20150423 - gathering requirements
Business case and cost modelling for an end-to-end RDM service
Ask Not What the NIH Can Do For You; Ask What You Can Do For the NIH
Rubrics for DMPs
CODATA: Open Data, FAIR Data and Open Science/Simon Hodson
Introducing Data and Text Mining at DigiFest

What's hot (20)

PPTX
Rachel Bruce on DMP
PPTX
What is Open Science and what role does it play in Development?
PPTX
Perspectives from the African Open Science Platform/Susan Veldsman
PDF
Mejias "Making it work globally"
PPTX
Workshop humphrey watkins-boyko-dmp workshop
PPT
RDA - The Research Data Alliance in a Nutshell
PDF
Data education and skills initiatives
PPTX
Frances Burton on sensitive data
PPTX
RDM landscape in the Netherlands
PDF
Data coordination and the role of RDA
PPTX
Business cases and costs RDN
PPTX
A coordinated framework for open data open science in Botswana/Simon Hodson
PPTX
EPFL Open Research Data - a Jisc perspective
PPTX
Report from RDAPlenary 3 to DataCitation Community in Australia
PPTX
Text mining and machine learning
PDF
White paper for an Open Research Data Strategy in Botswana
PPTX
Measuring the costs and benefits of RDM to supporta a business case
PPTX
Lightning Talks - Intro
PPTX
FSCI Data management and data sharing
PDF
Open Science Governance and Regulation/Simon Hodson
Rachel Bruce on DMP
What is Open Science and what role does it play in Development?
Perspectives from the African Open Science Platform/Susan Veldsman
Mejias "Making it work globally"
Workshop humphrey watkins-boyko-dmp workshop
RDA - The Research Data Alliance in a Nutshell
Data education and skills initiatives
Frances Burton on sensitive data
RDM landscape in the Netherlands
Data coordination and the role of RDA
Business cases and costs RDN
A coordinated framework for open data open science in Botswana/Simon Hodson
EPFL Open Research Data - a Jisc perspective
Report from RDAPlenary 3 to DataCitation Community in Australia
Text mining and machine learning
White paper for an Open Research Data Strategy in Botswana
Measuring the costs and benefits of RDM to supporta a business case
Lightning Talks - Intro
FSCI Data management and data sharing
Open Science Governance and Regulation/Simon Hodson
Ad

Viewers also liked (8)

PPTX
Jif businessmodels draft
PPT
Orphan Works Presentation (2)
PPT
PPT
PPTX
Organisational change and sustainability
PPTX
Cilips Autumn 2011 Gathering
PPTX
Intellectual Property Rights (IPR)
PPTX
Intellectual Property Rights
Jif businessmodels draft
Orphan Works Presentation (2)
Organisational change and sustainability
Cilips Autumn 2011 Gathering
Intellectual Property Rights (IPR)
Intellectual Property Rights
Ad

Similar to Digging into Data Funders Forum (20)

PPTX
Open Access to Research Data: Challenges and Solutions
PDF
African Open Science Platform: Pilot Phase
PPTX
Practical Research Data Management: tools and approaches, pre- and post-award
PPTX
Pros and Cons of Open Data: A Global South Perspective
PPTX
2016 Ocean Sciences Meeting tutorial
PPTX
The FOSTER project - general overview
PPT
The Thinking Behind Big Data at the NIH
PPTX
Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)
PPTX
Implementing Open Access: Effective Management of Your Research Data
PDF
Open Data - strategies for research data management & impact of best practices
PDF
Digital Data Sharing: Opportunities and Challenges of Opening Research
PPTX
WikiRate - Data Liberation and Radical Transparency
PDF
NordForsk Open Access Reykjavik 14-15/8-2014:Finnish data-initiative
PPTX
Australia's Environmental Predictive Capability
PPTX
A VIVO VIEW OF CANCER RESEARCH: Dream, Vision and Reality
PDF
Di d dlf_handout
PPTX
Research Data Management: A Tale of Two Paradigms
PPTX
Research data management: a tale of two paradigms:
PPTX
Open Science Globally: Some Developments/Dr Simon Hodson
PDF
Rachel Bruce UK research and data management where are we now
Open Access to Research Data: Challenges and Solutions
African Open Science Platform: Pilot Phase
Practical Research Data Management: tools and approaches, pre- and post-award
Pros and Cons of Open Data: A Global South Perspective
2016 Ocean Sciences Meeting tutorial
The FOSTER project - general overview
The Thinking Behind Big Data at the NIH
Martin Donnelly - Digital Data Curation at the Digital Curation Centre (DH2016)
Implementing Open Access: Effective Management of Your Research Data
Open Data - strategies for research data management & impact of best practices
Digital Data Sharing: Opportunities and Challenges of Opening Research
WikiRate - Data Liberation and Radical Transparency
NordForsk Open Access Reykjavik 14-15/8-2014:Finnish data-initiative
Australia's Environmental Predictive Capability
A VIVO VIEW OF CANCER RESEARCH: Dream, Vision and Reality
Di d dlf_handout
Research Data Management: A Tale of Two Paradigms
Research data management: a tale of two paradigms:
Open Science Globally: Some Developments/Dr Simon Hodson
Rachel Bruce UK research and data management where are we now

Recently uploaded (20)

PPTX
Programs and apps: productivity, graphics, security and other tools
PPTX
Spectroscopy.pptx food analysis technology
PPTX
KOM of Painting work and Equipment Insulation REV00 update 25-dec.pptx
PDF
MIND Revenue Release Quarter 2 2025 Press Release
PDF
Review of recent advances in non-invasive hemoglobin estimation
PDF
Machine learning based COVID-19 study performance prediction
PPTX
20250228 LYD VKU AI Blended-Learning.pptx
PPTX
Big Data Technologies - Introduction.pptx
PPTX
sap open course for s4hana steps from ECC to s4
PDF
Peak of Data & AI Encore- AI for Metadata and Smarter Workflows
PDF
Electronic commerce courselecture one. Pdf
PDF
NewMind AI Weekly Chronicles - August'25 Week I
PPTX
Understanding_Digital_Forensics_Presentation.pptx
PDF
Empathic Computing: Creating Shared Understanding
PDF
Approach and Philosophy of On baking technology
PDF
Encapsulation_ Review paper, used for researhc scholars
PDF
Chapter 3 Spatial Domain Image Processing.pdf
PDF
Spectral efficient network and resource selection model in 5G networks
PPTX
Cloud computing and distributed systems.
PDF
Encapsulation theory and applications.pdf
Programs and apps: productivity, graphics, security and other tools
Spectroscopy.pptx food analysis technology
KOM of Painting work and Equipment Insulation REV00 update 25-dec.pptx
MIND Revenue Release Quarter 2 2025 Press Release
Review of recent advances in non-invasive hemoglobin estimation
Machine learning based COVID-19 study performance prediction
20250228 LYD VKU AI Blended-Learning.pptx
Big Data Technologies - Introduction.pptx
sap open course for s4hana steps from ECC to s4
Peak of Data & AI Encore- AI for Metadata and Smarter Workflows
Electronic commerce courselecture one. Pdf
NewMind AI Weekly Chronicles - August'25 Week I
Understanding_Digital_Forensics_Presentation.pptx
Empathic Computing: Creating Shared Understanding
Approach and Philosophy of On baking technology
Encapsulation_ Review paper, used for researhc scholars
Chapter 3 Spatial Domain Image Processing.pdf
Spectral efficient network and resource selection model in 5G networks
Cloud computing and distributed systems.
Encapsulation theory and applications.pdf

Digging into Data Funders Forum

  • 1. Digging into Data: looking back – looking forward Catherine Grout/ Stuart Dempster Montreal, Palais de Congres 13th October 2013
  • 2. Introduction • To add context to aid discussion for next phase of the meeting • To highlight key findings and achievements of DiD 1 and 2 • To suggest some future ideas about directions and next steps
  • 3. DiD 1 and the CLIR report • For Round One, the Digging into Data (DiD) Challenge was sponsored by four research funders (NEH, NSF, SSHRC, Jisc) • Funded 8 international projects • Achieved impact and acclaim via a range of publications e.g. e New York Times, Nature, Times Higher Education, Globe and Mai letc. • DiD was also the subject of a major research report published by the Council on Library and Information Resources(CLIR). • CLIR report found that we need to: 1) Expand our concept of research 2) Expand our concept of research data and accept the challenges that digital research data present 3) Embrace interdisciplinarity 4) Take a more inclusive approach to collaboration 5) Address gaps in training and skills 6) Adopt models for sharing credit 7) Adopt models for sharing resources 8) Re-envision scholarly publication 9) Make greater, sustained investments in human and cyber infrastructure
  • 4. DiD 2 • For Round Two, four additional funders joined (IMLS, AHRC, ESRC, NWO) and the Netherlands joined as a fourth country. • 14 projects won awards, chosen by our international peer reviewers. These 14 presented their work in Montreal yesterday at the Digging into Data Conference • These fourteen projects represent a very wide variety of exciting research, among them the IMPACT project which made the headlines when their paper in the Lancet revealed that clogged arteries plagued the ancient world. • Some outcomes from Did 2 so far 1) Exploiting what open access and open data has enabled 2) New ways of visualising and interpreting existing data and resources 3) Development of tools that can then be applied to more contexts and data 4) Unanticipated and important new insights. Throwing up new research questions. 5) Enabling precision as well as speed of performance over very large datasets (like Amazon) 6) Challenging boundaries between disciplines and how you do the research process 7) Can anyone be a historian or sociologist if they have the right data?
  • 5. DiD 3 and onwards • Two new funders have joined DiD (CFI and NSERC), bringing us to a total of ten. • The Round Three projects will be announced in January of 2014. • DiD demonstrates a unique and field-proven method for international cooperation among research agencies. Proposals are reviewed by an international peer review committee jointly selected • Each applicant team must represent at least two countries. Awards made using a “fund-own” system under which funders only pay for their own researchers. Allows each funder to participate with minimal paperwork. • Multiple funders from a single country can work together (e.g. NEH, NSF, IMLS) which makes interdisciplinary projects easier to fund.
  • 6. DiD achievements (Channelling Brett) • Pioneered and legitimised big data based research in the humanities – for computer scientists and others. (‘from zero to hero’) • “Digital humanities”, “computational social sciences” and others working together (‘breaking boundaries’) • Engage GLAM sector and others to encourage them to make their data available in forms useful to researchers and to work with them (encourages joint data curation) • Progress on the policy side toward reforming copyright and IP to allow for big data research on cultural heritage materials. (more to do here) • International & multidisciplinary cooperation had high impact (more than anticipated). Increased visibility also strengthened research bringing new teams together (‘breaking new ground’)
  • 7. DiD achievements (Brett and others) • Brought knowledge to the funders themselves through working with other agencies, improving and transforming ideas. How can these lessons be highlighted for us within other collaborative endeavors like the Transatlantic Platform? • How might expanding the range of Digging funders help researchers expand the breadth of their work? To find new partners and new perspectives using big data research as a catalyst? • Project spanning domains (humanities, social science, and library/information science). Create a new kind of research that would not be funded because of boundaries between research councils and funder • • Societal value. Service to humanity – important new findings effect people’s lives Economic value. Health, crime, legal issues, efficiency gains - supports economy
  • 8. Funders responses to big challenges • • • • • • • • • • How might funders help? ‘Not enough to just say ‘open data’, but policies and procedures need to add ‘utility’ to ensure interoperable data. Open data mandates but with a data curation, data standards (DOI, APIs etc.) and credit (data citation e.g. Harvard) needed Develop common methodologies of checking and re-analysis to see the cumulative value and quality of data Encourage the availability and analysis of data in real or near time (John Willinsky) Encourage computational scientists, SSH researchers and digital libraries to work together (data preservation). Encourage permissive ‘model licences’ for public domain and copyrighted data Encourage ‘credit’ career progression/tenure amongst host institutions Develop sustainable and extensible shared digital infrastructure (grid, cloud etc.) Encourage ‘good practice’ in ethics and governance (privacy etc.) Encourage model legal and rights management approaches for (IPR) issues
  • 9. Discussion 1. Reactions – what are the main highlights so far? Do you agree with Brett? Are there other points? 2. Where should/could Digging go next led New research/Themes/ issues to be considered? (Taking forward grantees feedback) What is now done and finished (Implementing/embedding?) T-AP context? Is bigger better?