Use and reuse: research data locally & globally #esipfed

USE AND REUSEResearch data locally and globally

Kevin Ashley Digital Curation Centre

www.dcc.ac.uk@kevingashley

[email protected]

Reusable with attribution: CC-BYThe DCC is supported by Jisc & FP7

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Why does this matter?

• Research quality– How close can we get to

the truth?

• Research speed– How quickly can we get

to the truth?

• Research finance– How much does the

truth cost?

• Improving one or more of these is of interest to all actors:

• Researchers as data creators

• Researchers as data reusers

• Research institutions• Funders – hence

government and society2014-01-08 Kevin Ashley – ESIP Winter 2014 - CC-BY

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The Data Deluge is upon us

2014-01-08 Kevin Ashley – ESIP Winter 2014 - CC-BY

Sensor’s ability to produce data outstrips IT’s ability to process it

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Funders are making demands


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http://www.epsrc.ac.uk/about/standards/researchdata/Pages/expectations.aspx

EPSRC expects all those institutions it fundsto develop a roadmap that aligns … with EPSRC’s expectations by 1st May 2012;to be fully compliant … by 1st May 2015.

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• Awareness of regulatory environment• Data access statement• Policies and processes• Data storage• Structured metadata descriptions• DOIs for data• Securely preserved for a minimum of 10 years

from last use

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Where are funders making demands?• USA – NSF, NEH, some philanthropic funders• UK• Germany – DFG• Europe – European Commission (H2020)

Often tied to requirements on open access to research publications – but not as common.


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To universities, that looks like a problem

• Funder requirements exist for a reason:– That data is valuable

• Value to funder, society from reuse• Value to the institution is there also


BIS business case: £1.5m investment in research data services pays back 2.5 times after 5 years

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Research Data Centres – the solution!


MANY AREAS OF RESEARCH HAVE NO

DATA CENTRE TO SERVE THEM

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Data centres deliver valueWant a 400% -> 1200% return on your investment?


Try BADC!

http://www.jisc.ac.uk/whatwedo/programmes/di_directions/strategicdirections/badc.aspx

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Data reuse from Hubble


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Don’t trust government


http://thetyee.ca/News/2013/12/23/Canadian-Science-Libraries/

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Commercial services


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Cloud – sorted!

• Sorry, but it isn’t.• High-use datasets and long tail present

different economic and technical challenges• See David Rosenthal’s analysis of the

economics of Amazon for preservation“Distributed digital preservation in the cloud”IJDC 8(1), 2013 doi:10.2218/ijdc.v8i1.248


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Cost of data for 100 years – local vs Amazon S3Data from blog.dshr.org/2013/01/talk-at-idcc2013.html © David Rosenthal, used under CC-BY-SA licence


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Cost of data for 100 years – local vs Amazon S3 AND GlacierData from blog.dshr.org/2013/01/talk-at-idcc2013.html © David Rosenthal, used under CC-BY-SA licence


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National responses – supporting universities

• USA – NSF initiatives (DataONE, SEAD, Data Conservancy et al)

• Australia – ANDS, RDSI• UK – DCC, Jisc ‘Managing Research Data’

programmes• Netherlands – Research Data Netherlands• Canada – Research Data Canada• Also grassroots or funder-led work in Finland,

Denmark, Germany2014-01-08 Kevin Ashley – ESIP Winter 2014 - CC-BY

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UK- Jisc acts through DCC to help


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DCC ‘institutional engagement’

Assess needs

Make the case

Develop support and

services

RDM policy development

Customised Data Management Plans

DAF & CARDIO assessments

Guidance and training

Workflow assessment

DCC support

team

Advocacy with senior management

Institutional data catalogues

Pilot RDM tools

…and support policy implementation2014-01-08

Kevin Ashley – ESIP Winter 2014 - CC-BY 20http://dataintelligence.3tu.nl/en/home/

http://www

.sheffield.

ac.uk/is/re

search/pro

jects/

rdmrose

Choice of RDM training materials for librarians

Up-skilling for data

http://datalib.edina.ac.uk/mantra/libtraining.html

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Australian National Data Service

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National Service, backed with university-level initiatives


Excuses – and responses• “People will ask questions”

– So use a data centre or repository• “It will be misinterpreted”

– Stuff happens. Also, openness encourages correction• “It’s not interesting”

– Let others be the judge – your noise is my signal• “I might get another paper out of it”

– Up to a point. We might get more research out of it• “I don’t have permission”

– A real problem. But solvable at senior level• “It’s too bad/complicated” –see above• “It’s not a priority”

– Unfortunately, funders are making it so. But if you looked at the evidence, it would be your priority as well

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See e.g. Carly Strasser’s blog: http://datapub.cdlib.org/2013/04/24/closed-data-excuses-excuses/


These excuses bear a strong resemblance to those used by

politicians and civil servants who argue against the release of government

records

This is not a group you want to be compared with

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Integrity

• Not everyone publishes here

• Almost all fraud connected to unavailable data

• People suffer & die due to research fraud

• When your research is reproducible – it gets cited


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Integrity – not without data

• Cyril Burt– Twin studies on intelligence.– Questioned 1976; now discredited

• Duke case– Data hiding leads to wasted treatments, clinical trials,

probable death & huge lawsuits• Dutch cases

– Stapel – 55 publications – “fictitious data”– Poldermans – fabricated data or negligence?


“The case for open data: the Duke Clinical Trials “– blog post, Kevin Ashley, http://www.dcc.ac.uk/news/case-open-data-duke-clinical-trials“Lies, Damned Lies and Research Data: Can Data Sharing Prevent Data Fraud?” – Doorn, Dillo, van Horik, IJDC 8(1); doi:10.2218/ijdc.v8i1.256

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Should all data be open?

• NO• Many reasons – most to do with human

subjects• But data existence should always be open• Allows discovery & negotiation on use• Avoids pointless replication


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Gentleman’s data centres

• Some data centres have club-like behaviour– Barriers to access– Only for contributors– Territorial

• Not without value, but barriers to progress


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Citability

• Making data available increases citations• Everyone – academic, funder, institution –

loves citations• Want evidence?

– Alter, Pienta, Lyle – 240%, social sciences *– Piwowar, Vision – 9% (microarray data)†– Henneken, Accomazzi – 20% (astronomy) #


† Piwowar H, Vision TJ. (2013) Data reuse & the open data citation advantage. PeerJ PrePrints 1:e1v1 http://dx.doi.org/10.7287/peerj.preprints.1v1

* Amy Pienta, George Alter, Jared Lyle, (2010) The Enduring Value of Social Science Research: The Use and Reuse of Primary Research Data.http://hdl.handle.net/2027.42/78307

# Edwin Henneken, Alberto Accomazzi, (2011) Linking to Data - Effect on Citation Rates in Astronomy. http://arxiv.org/abs/1111.3618


Can we find it?

• Data must be discoverable to be reused• Alone, or in conjunction with publication• Institutional catalogues, national data

registries, national and international domain-specific services

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Data discovery around the world

• Research Data Australia• UK data registry pilot &

Gateway2Research• Research Data

Netherlands• World Data System• re3data.org &

databib.org – discovering repositories



Repository finders

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A re3data record

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A databibrecord


Kevin Ashley – ESIP Winter 2014 - CC-BY 332014-01-08


Other global work of note

• Domain initiatives such as Belmont forum• International generic groups – RDA, CODATA• Problem-specific services – Datacite, EZID,…

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Idea

Develop

Fund

Plan

Record

Process

Publish

Read


Idea

Develop

Fund

Plan

Record

Process

Publish

Read

Idea

Develop

Fund

Plan

Record

Process

Publish

Read


Idea

Develop

Fund

Plan

Record

Process

Publish

Read

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Data reuse stories

• The palaeontologist who saved years of work with archaeological data

• The ‘noise’ from research radar that mapped dust from Eyjafjallajökull

• The 19th-century logs and photographs that help us model climate change


Often your data tells stories that your

publications do not

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3TU treasure chest2014-01-08 Kevin Ashley – ESIP Winter 2014 - CC-BY


Thanks for your attention

[email protected]@kevingashley

2014-01-08

Use and reuse: research data locally & globally #esipfed

Technology

Transcript of Use and reuse: research data locally & globally #esipfed