Introduction to Research Data Management at Lancaster University

Introduction to Research Data Management

8 October 2014Hardy Schwamm & Masud Khokhar

1. What is Research Data Management (RDM)?– What is data?– Data lifecycle

2. Why does the University engage in RDM?– Funder requirements– Lancaster’s RDM Policy– Current RDM practices and researcher attitudes– What do other universities do?– N8 RDM

3. What RDM services is Lancaster University going to offer?– Storage– Role of Pure– Advocacy & Governance– Metadata– Training & Support– Data Management Plans– Data Preservation– JISC

Overview

• Facts, observations or experiences on which an argument, theory or test is based. Data may be numerical, descriptive or visual. Data may be raw or analysed, experimental or observational.

• Data can be “analogue” (hardcopy) or digital.• Digital data can be:

– created in a digital form ("born digital")– converted to a digital form (digitised)

• Very much discipline specific

1. What is RDM?

What are data?

Data

Data Lifecycle & Data Management Plans

4.Publication& Deposit

5.Preservation

& Re-Use

1.Create

2.Active Use

3.Documentation

1. What data will you produce?

2. How will you organise the data?

3. Can you/others understand the data

4. What data will be deposited and where?

5. Who will be interested in re-using the data?

• Research Data Management involves maintaining, preserving and adding value to digital research data throughout its lifecycle.

What is RDM?

• Open Data part of the “Open” movement which gathered momentum in the early 2000s.

• Funders' Data Policies draw on key documents such as the OECD Principles and Guidelines for Access to Research Data from Public Funding (2007)and the Toronto Statement (2009).

• Perception of data as a public good. Data as research output created with tax-payer’s money.

• Research Integrity: accurate and efficient collection of data and its storage in order to reproduce research results.

• Compliance with Data Protection and Freedom of Information legislation

2. Why does the University engage in RDM?

The bigger picture. Drivers include:

Summary of Research Councils UK - Common Principles on Data Policy• Public good: Publicly funded research data are produced in the public interest should be

made openly available with few restrictions• Planning for preservation: Institutional and project specific data management policies and

plans needed to ensure valued data remains usable• Discovery: Metadata should be available and discoverable; Published results should

indicate how to access supporting data• Confidentiality: Research organisation policies and practices to ensure legal, ethical and

commercial constraints assessed; research process not damaged by inappropriate release• First use: Provision for a period of exclusive use, to enable research teams to publish

results• Recognition: Data users should acknowledge data sources and terms & conditions of

access• Public funding: Investment is appropriate and must be efficient and cost-effective.

RCUK Common Principles on Data Policy

• RCUK released its Common Principles on Data Policy in April 2011• The EPSRC issued their Policy Framework on Research Data in April 2011,

setting out nine expectations concerning the management and provision of access to EPSRC-funded research data. – V. Research organisations will ensure that appropriately structured metadata

describing the research data they hold is published (normally within 12 months of the data being generated) and made freely accessible on the internet

– Vii: Research organisations will ensure that EPSRC-funded research data is securely preserved for a minimum of 10 years from the date that any researcher ‘privileged access’ period expires

• Funder requirements made universities develop “roadmaps” towards RDM compliance.

• Deadline of compliance with EPSRC’s Policy is May 2015.

Funding requirements

Funder requirements: overview of data policies

Table from DCC

• Projects must “aim to deposit the research data needed to validate the results presented in the deposited scientific publications, known as “underlying data".

• Any Horizon 2020 project is invited to submit a DMP as an early project deliverable if it is relevant to their research.

• All projects submitting a research proposal to ‘Research and Innovation Actions’ and ‘Innovation Actions’ are required to include a short outline of their general data management policy.

• All projects which are successfully funded under the Pilot on Open Research Data are expected to produce an initial DMP deliverable within the first six months of the project.

Horizon 2020 Guidelines on Data Management

Horizon 2020 data policy

• Approved by Senate in March2013 (SEC/2013/2/0776)• “Management of data is an essential part of good research practice and all researchers in

the University have an obligation to record, store and archive their data appropriately.”• Expectations include:

– “Each project will have a data management plan”.– “All research data will be stored in either electronic or paper form for a minimum of

10 years”– “Research data will be submitted to national or international data services and

repositories where available or required by either funders or publishers and this will replace the need for local archiving”

• The University will – “aim to provide mechanisms whereby research data […] can be archived

appropriately”– “provide guidance and training where necessary”

Lancaster University’s Research Data Policy

• We have talked to some Associate Deans for Research.• Informal discussions with selected researchers show diverse

data management practices.• Example: Department of Linguistics and English Language run

the University Centre for Computer Corpus Research on Language (UCREL).– UCREL research is data heavy, often uses copyrighted texts– Local solution of data storage & sharing is

Corpus Query Processor

But what is current RDM practice at Lancaster?

• Disciplines have very different attitudes towards data sharing.• In some research fields - such as genetics and physics - data

sharing is well-established.Attitudes vary:“Yet one more thing that gets in the way of doing actual research!” “My data is confidential and I can’t share it anyway.”“I’d welcome your help in managing our data.”

Researcher attitudes

• Jisc had 2 Managing Research Data Programmes (JISCMRD) 2009-2013, including infrastructure, planning & training

• Infrastructure: data.bris Research Data Repository, Databank (Oxford)

• Data Management Planning: DMPonline (Digital Curation Centre)

• Training: Mantra (University of Edinburgh)• Extensive RDM websites: Bath, Leeds, Leicester• But also very basic RDM support/websites: York, Warwick

What do other universities do?

Example from Exeter data audit

How do you currently archive the important elements of your research data once you have finished with it?”

Taken from University of Exeter DAF, p. 33

• N8 Partners: Durham, Lancaster, Leeds, Liverpool, Manchester, Newcastle, Sheffield and York

• Collaboration on topics like:– N8 data catalogue– Resource discovery metadata for ‘published’ data sets– Storage options for research data– RDM training– Case studies of current data practices

N8 Research Data Management Group

RDM policies

Archive

Preserve

& Share

Advocacy (senior mgmt & researcher)

£

Storage

Back-up

Access Training

and

guides

Support staff & services

Research

environment&

systems

Tools

Metadata and documentation

DCC

3. What services is Lancaster University going to offer?

• At the moment, ISS provides Research data storage where large-scale data sets can be securely stored and archived.– On demand only– Data sharing only among Lancaster colleagues

• University cloud storage (Box.com) is being investigated• Collaboration with external researchers?

Storage

• Pure will remain data entry point for research outputs, including datasets.

• Pure User Group has developed data specification that is now being implemented.

• Pure is not a preservation tool so we need additional service.

Research environment: Pure

Role of Pure in RDM

• Liaising with Academic Deans for Research• Investigating current data practices with recommended

researchers• Collaborating with other research-intense universities: N8• Formation of a Research, Open Access, Data Management and

Pure (ROADMaP) steering group incl. RDM Working Group

Advocacy & Governance

• RDM website with guidance for researchers developed• Working together with OED on training

– DCC Workshop “Introduction to RDM” on 8 December as part of Research Development Programme

• Similar events to follow• RDM input to ResearchBites with shorter “How to” sessions• “On demand” training sessions in departments

Training & Support

DMPs vary but they tend to include the following elements:1. Description of the data to be collected / created2. Standards / methodologies for data collection and

management3. Ethics and Intellectual Property considerations4. Plans for data sharing and access5. Strategy for long-term preservation

Data Management Plans

What is a Data Management Plan (DMP)?

• DMPonline is a free web-based tool developed by the DCC which helps researchers create their DMPs according to funder context.

• There are a number of templates within the tool that represent the requirements of 11 different funders (RCUK, Wellcome Trust, Horizon 2020 etc.) and institutions.

• We will create Lancaster custom DMP for research that is not externally funded

DMPonline

Data storage & publication

Data centre supported by

funder

No

University Data Archive

Pure / Hydra

External Data Centre

Disciplinary: GoGeo

General Repository:

Figshare

Yes!

NERC Data Centre UK Data Servi

ce

Testing Hydra

• RDM is an issue with many sometimes conflicting view points (“wicked problem”)

• RDM is high on agenda of policy makers, funders and the University. It won’t go away.

• A cultural shift is needed if we want to be successful (in a similar way as Open Access).

• Establishing a RDM service needs close collaboration of ISS, RSO, Library and Departments.

Conclusions

• RSO staff will be crucial for successful research data management practices at the University.

• Support us talking to researchers. Who are the data producers in different departments?

• Help the information flow. We need to know what RDM needs researchers (academic staff, PhD students, postdocs) have.

• By communicating effectively between stakeholders on the topic of research data management.

How can you help?