Griffith university s journey in data c itation
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Natasha Simons Senior Data Management Specialist Australian National Data Service Located at: Griffith University, Brisbane, Australia http:// orcid.org /0000-0003-0635-1998 Tw: @ n_simons. Griffith University’s Journey in Data C itation. ANDS Webinar 5 June 2014.

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Griffith University’s Journey in Data C itation

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Griffith university s journey in data c itation

Natasha Simons

Senior Data Management Specialist

Australian National Data Service

Located at: Griffith University, Brisbane, Australia

http://orcid.org/0000-0003-0635-1998

Tw: @n_simons

Griffith University’s Journey in Data Citation

ANDS Webinar 5 June 2014


About griffith university

About Griffith University

  • Established in 1971 and opened in 1975

  • Now has five South-East Queensland campuses

  • Around 43,000 students and 4,300 staff

  • 26 schools and departments in four academic groups:

    • Arts, Education and Law

    • Business

    • Health

    • Science, Environment, Engineering and Technology

Image credit: Danny Munnerley, http://www.flickr.com/photos/munnerley/6381877583/


Griffith s research profile

Griffith’s research profile

  • 32 research centresand institutes

  • Priority areas

    • Water science

    • Drug discovery and infectious diseases

    • Asian politics, security and development

    • Climate change adaptation

    • Criminology and crime prevention

    • Music, the arts and the Asia Pacific

    • Sustainable tourism

    • Chronic disease prevention

    • Physical sciences

    • Environmental sciences

    • Nursing

    • Education

Image credit: Anne Ruthmann, http://www.flickr.com/photos/annemarlow/8392238157/


Research infrastructure and data management

Research infrastructure and data management

  • Strong commitment from University leaders to improving data management

  • Staff resources – operational and project related

  • Successful in seeking funding from ANDS and NeCTAR to build national and local infrastructure

  • Strong emphasis on seeking internal funds and working with researchers on grants for funds to develop, enhance and support institutional tools

  • Policy frameworks and service models for data management support under discussion


What does a data citation look like

What does a data citation look like?


What does a data citation look like1

What does a data citation look like?


What does a data citation look like2

What does a data citation look like?


What does a data citation look like3

What does a data citation look like?


How is data cited

How is data cited?


How is data cited1

How is data cited?


What do you need to pack for your data citation journey

What do you need to pack for your data citation journey?

There are really only two things you need before you start on a data citation journey:

Some research data collections at your institution that have open, embargoed or mediated access.

A publically available metadata record that describes each of these collections and provides access to them.

Image credit: http://www.peregrineadventures.com/blog/13/02/2012/great-packing-debate


Packing for the journey

Packing for the journey

At Griffith, we have:

Research Data Repository - http://equella.rcs.griffith.edu.au/research/logon.do

Research Hub (metadata store/researcher profile system) - http://research-hub.griffith.edu.au


Packing for the journey1

Packing for the journey

On your journey, you may also need:

Management support:

2. Technical support:

Malcolm Wolski

Director,

eResearchServices & Scholarly Application Development

Division of Information Services

Griffith University

ArveSolland

Senior Developer,

eResearchServices & Scholarly Application Development

Division of Information Services

Griffith University


When and why doi

When and why, DOI?

2011

August –‘PIDs for data’ options paper, recommended DOIs

August – ANDS launched Cite My Data service pilot

September to December – signed up; developed m-2-m scripts, minted DOIs

2012

c.May - Put ‘Cite this collection’ feature in Griffith Research Hub

October - Commenced data citation project

2013

May - Concluded data citation project

September – produced DOI guidelines; developed roadmap


When and why doi1

When and why, DOI?

  • Griffith needed a persistent identifier that would:

  • Fill gaps in persistent identifiers for scholarly works

  • Replace long and incomprehensible URLs for metadata

  • Signal long-term management of our research data collections

  • Contribute to the semantic vision for data in the Research Hub

  • Later: foundation for data citation.


When and why doi2

When and why, DOI?

  • We chose DOIs to meet our needs because they:

    • Are a global persistent identifier, already used for many scholarly publications

    • Can be assigned to research data, theses, grey lit and even software code

    • Improve visibility of, and access to, research data

    • Gave us responsibility for managing persistent access to our data collections

    • Won’t break when IR software is re-indexed (as handles sometimes do)

    • Later, because they:

    • Facilitate data citation

    • Greatly assist tracking impact of data sets through collection of metrics and altmetrics based on DOI


When and why doi3

When and why, DOI?

  • The ANDS Cite My Data service provided:

    • Partnership with international DOI registration agency: DataCite

    • Minting DOIs for metadata records about open, mediated or embargoed research data, theses, grey literature (even software code)

    • Machine-to-machine workflow

    • Easily achieved kernel metadata

    • Trial in safe test environment

    • High level documentation for the M-2-M provided by ANDS

    • High level information on data citation on the ANDS website

    • Free!

  • And so we became the first guinea pigs of the Cite My Data Service….


Cite my data how does it work

Cite My Data – how does it work?

Sign agreement to use the service

ANDS give you an institutional id

Prepare your m-2-m script (includes required metadata for each DOI: title, creator, publisher, publication year, identifier)

Execute script against Cite My Data service

Cite My Data service returns DOIs

Store DOIs in own system

Create citation element

Make citation element avail in RIF-CS feed for ANDS harvester

DOI scipts: https://github.com/gu-eresearch/ANDSDOIScripts


Decisions decisions

Decisions, decisions…

  • What’s the criteria for assigning a DOI to a research data collection?

  • At what level of granularity should a DOI be applied?

  • Should the DOI link to the landing page or the actual data? Which landing page?

  • What if the data is changed e.g. updated? Should a new DOI be issued?

  • Should researchers be able to mint the DOI or should we mint it for them?

  • How are DOIs assigned if the research data is the result of a collaboration between various institutions?

  • What happens to the DOIs we have minted if ANDS closes shop?

  • Can you cite data without a DOI?

  • Implementing DOIs for Research Data D-Lib article http://dx.doi.org/10.1045/may2012-simons


Developing guidelines

Developing guidelines

We found answers to our questions and wrote them up in guidelines:

Digital Object Identifiers (DOIs): Introduction and Management Guide

Available for download from the ANDS website:

http://ands.org.au/cite-data/griffith_doi_guidelines-4.pdf

ANDS DOI FAQs http://ands.org.au/cite-data/doi_q_and_a.html

Documented our experiences in the Gold Standard Project @ Griffith blog: http://ands-gold-griffith.blogspot.com.au/


Data citation

Data Citation


Discovery

Discovery


Data citation engagement experiences

Data Citation engagement experiences

  • Established a blog - http://data-citation-griffith.blogspot.com.au/

  • Spoke with librarians about citation practices in different disciplines

  • Included data citation as part of standard consultations with a group in Health & an individual in environmental economics

  • Notifications workflows

    • Investigated Dryad automated notifications workflows

    • Modified their depositor notification

    • Manually emailed collections owners of new collections

    • Notifications added to technical requirements for data deposit

  • Reviewed existing information and workflows

    • Griffith policies and procedures

    • Academic style guides

    • Training materials and guides

  • Included data citation in new Best practice guidelines for researchers: managing research data and primary materials


Lesson 1 one size will not fit all

Lesson #1: One size will not fit all

  • Disciplines

    • Citation practices

    • Style guides

    • Publishing protocols

    • Target audiences

    • Types of research output

    • Usage of metrics

  • Age and career stage

    • Attitudes to open access

    • Motivations

    • Technical know-how

Image credit: TakiSteve, http:[email protected]/1380483002/


Lesson 2 choose your time

Lesson #2: Choose your time

  • Find ‘hooks’ in the researchers’ workflows

    • e.g. point of data deposit

    • e.g. final report on funded research

    • e.g. through data planning

  • Long term goal should be to get in early - improving the training and supporting artefacts (style guides, bibliographic management software) that introduce new students and researchers to the principles of citation

Image credit: Todd Lappin, http://www.flickr.com/photos/telstar/433029904/


Lesson 3 need to know basis

Lesson #3: Need-to-know basis

  • A depositor shouldn’t have to know what a DOI is or where it comes from, or be asked to make a decision about whether they want one or not

  • Minting DOIs should be done automatically for collections that meet the rules defined by the ‘publisher’ of the deposited data (in this case, Griffith University) and the DOI registration agency

Image credit: TakiSteve, http:[email protected]/1380483002/


Lesson 4 be honest and realistic with researchers

Lesson #4: Be honest and realistic with researchers

  • Be honest about the evidence base – they’re researchers so they will ask!

  • Be honest about the lack of rewards within the current system and have empathy – researchers know better than us what they do and don’t get rewarded for


Lesson 5 not everything can be solved now or by you alone

Lesson #5 :Not everything can be solved now or by you alone

Collective action is needed for change in these areas

We’re investigating these now and in the near future

We mostly know what we are doing with these


Data citation experiences

Data citation experiences

D-Lib article: Growing Institutional Support for Data Citation: Results of a Partnership between Griffith University and the Australian National Data Service

http://dx.doi.org/10.1045/november2013-simons

What Griffith University are doing to establish a culture of data citation:

https://www.youtube.com/watch?v=jDsD5cbIeZU


On the to do list

On the ‘to do’ list

  • But we didn’t conquer the world…

  • On the ‘to do’ list:

  • Embedding DOIs into automated data collection workflows

  • Minting DOIs for grey literature: theses, reports, discussion papers etc.

  • Improving links between research publications and underlying data

  • Reviewing DOI guidelines, rules and workflows at future points in time

  • Embedding types of metadata, such as COINS, into the landing pages to assist import into citation tools


Reflections

Reflections

  • Easy lessons learnt:

  • Do what you can with what you have available

  • Technical minting and maintaining of DOIs is relatively easy

  • Cite My Data service is straight forward

  • Getting citation element is also relatively easy

  • There are a lot of materials available now on DOIs (infrastructure) and on data citation (researchers) so don’t reinvent the wheel

  • You could decide to set up an administrator interface for minting and maintaining the DOIs (e.g. the way TERN have done this). This would run over the top of the m-2-m scripts.


Reflections1

Reflections

  • Hard lessons learnt:

  • Establishing workflows for DOIs and data citation is not easy if you don’t know when researchers are going to publish their data and if data publication is not routine

  • Data citation is not (yet) common practice but there is a large international community supporting data citation as a principle and to encourage practice

  • There is a growing body of evidence on a positive link between open data and citation counts


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