reasons to select research data and where to start

What's the data? Where’s the (re)use?

Visual Arts Data Service (VADS) DCC

and KAPTUR project

Managing the Material:

Tackling Visual Arts as

Research DataLondon

Friday, 14 September

2012

This work is licensed under a Creative Commons Attribution 2.5 UK: Scotland License

Pablo PicassoBottle of Vieux Marc, Glass, Guitar and Newspaper 1913

Reasons to select and where to start

Angus Whyte

The Digital Curation Centre

• Consortium of 3 units in Universities of Bath (UKOLN), Edinburgh (DCC Centre) and Glasgow (HATII)

• Funded by JISC, plus HEFCE funding from 2011

• challenges in digital curation

• across institutions or disciplines

• support to JISC e.g. MRD

• targeted institutional development

• Including University of the Arts London

DCC Mission

“Helping to build capacity, capability and skills in data management and curation across the UK’s higher education

research community”DCC Phase 3 Business Plan

Aims today

• Help gather thoughts on the need to be selective

• Suggest 7 things on which we might agree

• Focus on practical implications of scoping “research data”

• Consider kinds of data for reuse

• Triage – levels of care and how to decide

Selection Strategies

1. Keep everything, dispose by natural wastage

Practitioners

2. Select the significant, dispose of the rest

Traditional records mgmt

3. Select and prioritise effort, review cost benefits, dispose as last resort

Practical?

Why not keep it all?

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Increasing volumes outpacing declining storage hardware costs Increasing care costs

According to: John Gantz and David Reinsel 2011 Extracting Value from Chaos http://www.emc.com/digital_universe.

We can’t afford it all

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“Keeping 2018’s data in S3 would cost the entire global GDP”

http://blog.dshr.org/2012/05/lets-just-keep-everything-forever-in.html

We can’t share it all

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Steven Harnad “Open Access Evangelism”

http://openaccess.eprints.org/index.php?/archives/2010/05.html

“ Researchers' unwillingness to make their laboriously gathered data immediately OA is not just out of fear of misuse and misappropriation. It is much closer to the reason that a sculptor does not do the hard work of mining rock for a sculpture only in order to put the raw rock on craigslist for anyone to buy and sculpt for themselves, let alone putting it on the street corner for anyone to take home and sculpt for themselves. That just isn't what sculpture is about. And the same is true of research …

But…a better example?

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bus routes data sculpture

• “a 3D data sculpture of the Sunday Minneapolis / St. Paul public transit system, where the horizontal axes represent directional movement and the vertical represents time. the piece titled "bus structure 2am-2pm" is constructed of 47 horizontal layers, each forming a map of the bus routes that run during a given interval of time. looking down from the top, one sees the Sunday bus map of the Twin Cities, while looking from the side, the times appears as strata building upwards. within each layer, every transit route that operates at that time is represented by wood balls placed at its scheduled stops, connected by the horizontal copper rods. each route moves through time and space differently, carving out its own trail that may or may not meet conveniently with other routes.

• in total 42 routes, 47 intervals of time & 296 bus stops are depicted by about a half-mile of copper rod & 6,000 wood balls, suspended in the air by hundreds of blue threads

http://infosthetics.com/archives/2008/05/bus_routes_data_sculpture.html

Reusingpublicdata to create an object with reuse value?

Things we might agree on?

1. Digital material becoming more pervasive

2. Research Councils want more transparency in use of public funding, planning for digital resources , ongoing access to ‘significant electronic resources or datasets’

3. Artists, researchers, audiences influence what is ‘significant’

4. We can track what’s significant online, as will they

Things we might agree on?

1. Digital material becoming more pervasive

2. Research Councils want more transparency in use of public funding, planning for digital resources , ongoing access to ‘significant electronic resources or datasets’

3. Artists, researchers, audiences influence what is ‘significant’

4. We can track what’s significant online, as will they

Things we might agree on?

4. Digital material is at risk e.g. from tech obsolescence or loss of knowledge; researchers need advice on how to mitigate risks, which they already get …

Things we might agree on?

5. Digital material is at risk e.g. from tech obsolescence or loss of knowledge; researchers need advice on how to mitigate risks, which they already get …

Things we might agree on?

5. Digital material is at risk e.g. from tech obsolescence or loss of knowledge; researchers need advice on how to mitigate risks, which they already get …

Things we might agree on?

5. Digital material is at risk e.g. from tech obsolescence or loss of knowledge; researchers need advice on how to mitigate risks, which they already get …

Things we might agree on?

6. Characterising ‘research data’ in the visual arts can help get materials our institution has a ‘duty of care’ towards

(E.g. it arises out of and evidences any research or practice for which it shares responsibility)

….into the hands of those who can help care for it

(wherever they are)

7. If their producers know there is a demand and earn credit

(e.g. citations, impact case studies)

…and everyone has clear expectations and examples

Things we might agree on?

6. Characterising ‘research data’ in the visual arts can help get materials our institution has a ‘duty of care’ towards

(E.g. it arises out of and evidences any research or practice for which it shares responsibility)

….into the hands of those who can help care for it

(wherever they are)

7. If their producers know there is a demand and earn credit

(e.g. citations, impact case studies)

…and everyone has clear expectations and examples

Then a definition does not need to do much more!“Example moves the world more than doctrine” Henry Miller

Clarify expectations

What kinds of “data” are wanted

For what kinds of reuse

Examples of what?

Institutions can follow research communities and data centres’ lead in establishing collections policies and preservation models through consultation

• What kinds of material

• What kinds of reuse

• What do we have ‘duty of care’ for

• What levels of preservation

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e.g. High Energy Physics community

e.g. High Energy Physics community

Levels of data to preserve Use case

1) Additional documentation(e.g. wikis, news forums)

Publication-related information search

2) Data in a simplified format Outreach, simple training analyses

3) Analysis level software and the data format

Full scientific analysis based on existingreconstruction

4) Reconstruction and simulation software and basic level data

Full potential of the experimental data

Adapted from: DPHEP Study Group: Towards a Global Effort for Sustainable Data Preservation in High Energy Physics, May 2012 . http://arxiv.org/abs/1205.4667

e.g. Archaeology Data Service

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http://archaeologydataservice.ac.uk/advice/collectionsPolicy

“The ADS expects to collect all of the following archaeological data types…”

A triage process

What levels of care & ground rules to decide

Clarify expectations

What ground rules will you use to prioritise care?

What kinds of data?

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Data?

Conceptualise

Create or Collect

Assemble and Interpret

Disseminate

A/V collections

Sketchbooks

Prototypes

Performances