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ETHICS AND CONSENT

ACCESS CONTROL

Under certain circumstances, sensitive and confidential

data can be safeguarded by regulating use of or

restricting access to such data, while at the same time

enabling data sharing for research and educational

purposes.

Data held at data centres and archives are not generally in

the public domain. Their use is restricted to specific

purposes after user registration. Users sign an End User

Licence in which they agree to certain conditions, e.g. not

to use data for commercial purposes or identify any

potentially identifiable individuals.

Data centres may impose additional access regulations for

confidential data such as:

• needing specific authorisation from the data owner to

access data

• placing confidential data under embargo for a given

period of time until confidentiality is no longer pertinent

• providing access to approved researchers only

• providing secure access to data through enabling

remote analysis of confidential data but excluding the

ability to download data

Mixed levels of access regulations may be put in place for

some data collections, combining regulated access to

confidential data with user access to non-confidential data.

Data centres typically liaise with the researchers who own

the data in selecting the most suitable type of access for

data. Access regulations should always be proportionate

to the kind of data and confidentiality involved.

OPEN ACCESS

The digital revolution has caused a strong drive towards

open access of information, with the internet making

information sharing fast, easy, powerful and empowering.

Scholarly publishing has seen a strong move towards open

access to increase the impact of research, with e-journals,

open access journals and copyright policies enabling the

deposit of outputs in open access repositories. The same

open access movement also steers towards more open

access to the underlying data and evidence on which

research publications are based. A growing number of

journals require for data that underpin research findings to

be published in open access repositories when

manuscripts are submitted.

ACCESS RESTRICTIONS VS. OPEN

ACCESS

Working with data owners, the

Secure Data Service provides

researchers with secure access to

data that are too detailed, sensitive or

confidential to be made available under

the standard licences operated by its sister service, the

Economic and Social Data Service (ESDS).31 The

service’ssecurity philosophy is based upon training and

trust, leading-edge technology, licensing and legal

frameworks (including the 2007 Statistics Act), and strict

security policies and penalties endorsed by both the

ONS and the ESRC.

The technical model shares many similarities with the

ONS Virtual Microdata Laboratory32 and the NORC

Secure Data Enclave.33 It is based around a Citrix

infrastructure which turns the end user’s computer into a

remote terminal. All data processing is carried out on a

central secure server; no data travels over the network.

Outputs for publication are only released subject to

Statistical Disclosure Control checks by trained Service

staff.

Secure Data Service data cannot be downloaded.

Researchers analyse the data remotely from their home

institution at their desktop or in a safe room. The Service

provides a ‘home away from home’ research facility with

familiar statistical software and MS Office tools to make

remote collaboration and analysis secure and convenient.

The clearing-house mechanism established following the

Convention on Biological Diversity to promote

information sharing, has resulted in an exponential

increase in openly accessible biodiversity and ecosystem

data since 1992.

The Forest Spatial Information Catalogue is a web-based

portal, developed by the Center for International Forestry

Research (CIFOR), for public access to spatial data and

maps.34 The catalogue holds satellite images, aerial

photographs, land usage and forest cover maps, maps of

protected areas, agricultural and demographic atlases

and forest boundaries. For example, forest cover maps

for the entire world, produced by the World

Conservation Monitoring Centre in 1997 can be

downloaded freely as digital vector data.

The Global Biodiversity Information Framework (GBIF)

strives to make the world’s biodiversity data accessible

everywhere in the world.35 The framework holds millions

of species occurrence records based on specimens and

observations, scientific and common names and

classifications of living organisms and map references for

species records. Data are contributed by numerous

international data providers. Geo-referenced records can

be mapped to Google Earth.

CASE

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KNOW

HOW DATA

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WHO OWNS COPYRIGHT?

Researchers creating data typically hold copyright in their

data. Most research outputs – including spreadsheets,

publications, reports and computer programs – fall under

literary work and are therefore protected by copyright.

Facts, however, cannot be copyrighted. The creator is

automatically the first copyright owner, unless there is a

contract that assigns copyright differently or there is

written transfer of copyright signed by the copyright owner.

If information is structured in a database, the structure

acquires a database right, alongside the copyright in the

content of the database. A database may be protected by

both copyright and database right. For database right to

apply, the database must be the result of substantial

intellectual investment in obtaining, verifying or

presenting the content.

For copyright to apply, the work must be original and

fixed in a material form, e.g. written or recorded. There is

no copyright in ideas or unrecorded speech. If researchers

collect data using interviews and make recordings or

transcriptions of the interviewee’s words, then the

researcher holds the copyright of those recordings. In

addition, each speaker is an author of his or her recorded

words in the interview.36

In the case of collaborative research or derived data,

institutions. Copyright should be assigned correctly,

especially if datasets have been created from a variety of

sources; for example those which have been bought or

‘lent’ by other researchers. When digitising paper-based

materials or images, or analogue recordings, attention

needs to be paid to the copyright of the original material.

In academia, in theory the employer is the owner of the

employment. Many academic institutions, however, assign

the researchers. Researchers should check how their

institutions assign copyright.

RE-USE OF DATA AND COPYRIGHT

Secondary users of data must obtain copyright clearance

from the rights holder before data can be reproduced.

Data can be copied for non-commercial teaching or

research purposes without infringing copyright, under the

fair dealing concept, providing that the owner of the data

is acknowledged. An acknowledgement should give credit

to the data source used, the data distributor and the

When data are shared through a data centre, the

researcher or data creator keeps the copyright over data

and licences the centre to process and provide access to

the data. A data centre cannot effectively hold data unless

all the rights holders are identified and give their

permission for the data to be archived and shared. Data

centres typically specify how data should be

acknowledged and cited, either within the metadata

record for a dataset or in a data use licence.

CREATOR, THAT PREVENTS UNAUTHORISED COPYING AND PUBLISHING OF AN ORIGINAL

WORK. COPYRIGHT APPLIES TO RESEARCH DATA AND PLAYS A ROLE WHEN CREATING,

SHARING AND RE-USING DATA.

A researcher has collated articles

about the Prime Minister from The

Guardianover the past ten years,

using the LexisNexis newspaper

database to source articles. They are

then transcribed/copied by the

researcher into a database so that content analysis can

be applied. The researcher offers a copy of the database

together with the original transcribed text to a data

centre.

Researchers cannot share either of these data sources as

they do not have copyright in the original material. A

data centre cannot accept these data as to do so would

be breach of copyright. The rights holders, in this case

The Guardianand LexisNexis, would need to provide

consent for archiving.

USING THIRD PARTY DATA

The Stockholm Environmental Institute (SEI) has created

an integrated spatial database, Social and Environmental

Conditions in Rural Areas (SECRA).37 This contains a wide

range of socio-economic and environmental

characteristics for all rural Census 2001 Super Output

Areas (SOAs) for England.

Multiple third party data sources were used, such as

Census 2001 data, Land Cover Map data and data from

the Land Registry, Environment Agency, Automobile

Association, Royal Mail and British Trust for Ornithology.

Derived data have been calculated and mapped onto

SOAs. The researchers would like to distribute the

database for wider use.

Whilst the database contains no original third party data,

only derived data, there is still joint copyright shared

between the SEI and the various copyright holders of the

third party data. The researchers have sought permission

from all data owners to distribute the data and the

documentation. The database can therefore be distributed.

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When research data are submitted to a journal to

supplement a publication, researchers need to verify

whether the publisher expects copyright transfer of

the data.

Some researchers may have come across the concept of

Creative Commons licences which allow creators to

communicate the rights which they wish to keep and the

rights which they wish to waive in order for other people

to make re-use of their intellectual properties more

straightforward. The Creative Commons licence is not

usually suitable for data. Other licences with similar

objectives are more appropriate, such as the Open Data

Commons Licence or the Open Government Licence.38

‘ELITES’

A researcher has interviewed five

retired cabinet ministers about their

careers, producing audio recordings

and full transcripts. The researcher then

analyses the data and offers the

recordings and transcripts to a data centre for

preserving. However the researcher did not get signed

words.

In this case it would be problematic for a data centre to

accept the data. Large extracts of the data cannot be

quoted by secondary users. To do so would breach the

interviewees’ copyright over their recorded words. This is

equally a problem for the primary researcher. The

researcher should have asked for transfer of copyright or

a licence to use the data obtained through interviews, as

the possibility exists that the interviewee may at some

point wish to assert the right over their words, e.g. when

publishing memoirs.

A researcher subscribes to access spatial AgCensus data

from the data centre EDINA. These data are then

integrated with data collected by the researcher. As part

of the ESRC research award contract the data has to be

offered for archiving at the UK Data Archive. Can such

integrated data be offered?

The subscription agreement on accessing AgCensus data

states that data may not be transferred to any other

person or body without prior written permission from

EDINA. Therefore, the UK Data Archive cannot accept the

integrated data, unless the researcher obtains permission

from EDINA. The researcher’s partial data, with the

AgCensus data removed, can be archived. Secondary users

could then re-combine these data with the AgCensus data,

if they were to obtain their own AgCensus subscription.

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PROVIDE A DATA MANAGEMENT FRAMEWORK FOR RESEARCHERS

STRATEGIES FOR

CENTRES

During 2010, the UK Data Archive worked closely with

selected ESRC research centres and programmes to

evaluate existing data management practices and develop

data management planning strategies. The

recommendations contained in this guide are based on

those real-case experiences.

Research hubs may operate a centralised or devolved

approach to data management, co-ordinating how data

are handled and organised or giving researchers all

authority and responsibility for handling their research

data. Factors that may influence which approach is taken

include the size of the research hub, whether it is a single

or cross-institutional entity and how much methodological

and discipline diversity the data exhibit.

Advantages of a centralised approach to data

management include:

• researchers can share good practice and data

management experiences, thereby building capacity for

the centre

• a uniform approach to data management can be

established as well as relevant central data policies

• data ownership can be identified and kept track of over

time, especially useful when researchers move

• data can be stored at a central location

• assurance that all researchers and staff are aware of

duties, responsibilities and funder requirements

regarding research data, with easy access to relevant

information

At the same time, researchers need to take responsibility

for managing their own data and a devolved approach to

data management may give more flexibility to adapt to

discipline requirements or may be needed to adapt data

management according to research methods.

Centralised data management is especially beneficial for

data formatting, storage and back-up. It also helps to

govern data sharing policies, establish copyright and IPR

over data and assign roles and responsibilities.

DATA MANAGEMENT RESOURCES LIBRARY

A research hub can centralise all relevant data

management and sharing resources for researchers and

staff in a single location: on an intranet site, website, wiki,

shared network drive or within a virtual research

environment.

This resources library may contain relevant data policy

and guidance documents, templates, tools and exemplars

developed by the centre, as well as external policy and

guidance resources or links to such resources. Resources

can be developed by the centre. Good practices used by

particular researchers or projects can be used as

exemplars for others, so that these good practices can be

shared.

A resources library might contain both locally created and

external documents.

Locally created documents:

• declaration on copyright of research data and outputs

• declaration of institutional IT data management and

existing back-up procedures

• statement on data sharing

• statement on retention and destruction of data

• file naming convention guidance

• version control guidance

• data inventory for individual projects

• template consent forms and information sheets which

take data sharing into account

• example ethical review forms

• data anonymisation guidelines

• transcription guidance

External documents:

• research funder data policies

• research ethics guidance of professional bodies

• codes of practice or professional standards relevant to

research data

• JISC Freedom of Information and research data:

Questions and answers (2010)

• Data Protection Act 1998 guidance

• Environmental Information Regulations 2004

information

• UK Data Archive’s Guidance on Managing and Sharing

Data

• Data Handling Procedures in Government

STRATEGIES FOR CENTRES

RESEARCH CENTRES AND PROGRAMMES CAN SUPPORT RESEARCHERS THROUGH A

CO-ORDINATED DATA MANAGEMENT FRAMEWORK OF SHARED BEST PRACTICES. THIS CAN

INCLUDE LOCAL GUIDANCE, TEMPLATES AND POINTERS TO KEY POLICIES.

To provide a data management framework, research

hubs can develop:

• the assignment of data management responsibilities

to named individuals

• standardised forms, e.g. for consent procedures,

ethical review, data management plans

• standards and protocols, e.g. data quality control

standards, data transcription standards,

confidentiality agreements for data handlers

• file sharing and storage procedures

• a security policy for data storage and transmission

• a data retention and destruction policy

• data copyright and ownership statements for the

centre and for individual researchers

• standard data format recommendations

• version control and file naming guidelines

• information on funder requirements or policies on

managing and sharing data that apply to projects or

the centre

• a research data sharing strategy, e.g. via an

institutional repository, data centre, website

DATA INVENTORY

A research centre can develop a data inventory to keep

track of all data that are being created or acquired by

various researchers within the centre.

The inventory can record what the data mean, how they

are created, where they were obtained, who owns them,

who has access, use and editing rights and who is

responsible for managing them.

It can at the same time be used as a data management

tool to plan management when research starts and then

keep track of management implementation during the

research cycle via a regular update strategy. The inventory

can record storage and back-up strategies, keep track of

versions and record quality control procedures. Data

management can be reviewed annually or alongside

research review such as during project progress meetings.

An inventory facilitates data sharing as it records data

ownership, permissions for data sharing and contains

basic descriptive metadata. It can be combined with the

recording of research outputs for research excellence

tracking purposes.

STRATEGIES FOR CENTRES

DATA MANAGING AND SHARING

STRATEGIES

ESRC centres and programmes have

a contractual responsibility to

manage and share their research data.

The Rural Economy and Land Use (Relu)

Programme undertakes interdisciplinary research

between social and natural sciences. When it started it

developed a programme-specific data management

policy and set up a cross council data support service.

The Relu data policy takes the view that publicly-funded

research data are a valuable, long-term resource with

usefulness both within and beyond the Relu programme.

Award holders are responsible for managing data

throughout their research and making them available for

archiving at established data centres after research.

Preparing a data management plan at the start of a

project helps in this respect, with pro-active advice and

training given by the data support service.

The research councils are responsible for the long-term

preservation and dissemination of the resulting data.

The Third Sector Research Centre (TSRC) is an ESRC-

funded centre primarily shared between the Universities

of Birmingham and Southampton.

The TSRC employs a centre manager to provide an

organisational lead in its operation, including data

management aspects such as co-ordinating ethical

review of research, consent procedures and data re-use.

The centre has a data management committee of deputy

director, selected research staff and centre manager, to

devise and implement administrative aspects of data

management throughout the centre’s research.

Administration staff help implement data management

by providing transcription management services and

data organisation support to projects.

CASE

STUDY

REFERENCES

All online literature references retrieved 8 April 2011.

1Organisation for Economic Co-operation and Development

(2007) OECD principles and guidelines for access to research data

from public funding. www.oecd.org/dataoecd/9/61/38500813.pdf

Rural Economy and Land Use Programme (2004) Relu data

management policy.

relu.data-archive.ac.uk/relupolicy.asp

3 Publishing Network for Geoscientific and Environmental Data

(2005) Policy for the data library PANGAEA.

www.pangaea.de/curator/files/pangaea-data-policy.pdf

4Nature Publishing Group (2009) Nature journals’ policy on

availability of materials and data.

www.nature.com/authors/policies/availability.html

Biotechnology and Biological Sciences Research Council (2010)

BBSRC data sharing policy.

www.bbsrc.ac.uk/organisation/policies/position/policy/data-

sharing-policy.aspx

6 Economic and Social Research Council (2010) ESRC research

data policy.

www.esrc.ac.uk/about-esrc/information/data-policy.aspx

Medical Research Council (n.d.) MRC policy on data sharing and

preservation.

www.mrc.ac.uk/Ourresearch/Ethicsresearchguidance/Datasharin

ginitiative/Policy/index.htm

8 Natural Environment Research Council (2011) NERC data policy.

www.nerc.ac.uk/research/sites/data/policy.asp

9 Wellcome Trust (2010) Wellcome Trust policy on data

management and sharing. www.wellcome.ac.uk/About-

us/Policy/Policy-and-position-statements/WTX035043.htm

Van den Eynden, V., Bishop, L., Horton, L. and Corti, L. (2010)

Data management practices in the social sciences. www.data-

archive.ac.uk/media/203597/datamanagement_socialsciences.pdf

11 Rural Economy and Land Use Programme (n.d.). Project

communication and data management plan. relu.data-

archive.ac.uk/DMP2010.doc

12 Rural Economy and Land Use Programme Data Support Service

(2011) Example data management plans. relu.data-

archive.ac.uk/DMPexample.asp

UK Data Archive (2011) Activity-based data management

costing tool for researchers. www.data-

archive.ac.uk/media/257647/ukda_jiscdmcosting.pdf

14 Digital Curation Centre (2010) DMP Online.

www.dcc.ac.uk/dmponline

15 SomnIA (n.d.) www.somnia.surrey.ac.uk/

EDINA (n.d.) Go-Geo! GeoDoc metadata creator tool.

www.gogeo.ac.uk/cgi-bin/cauth.cgi?context=editor

UK Location (2011) UK Location Metadata Editor.

location.defra.gov.uk/resources/discovery-metadata-

service/metadata-editor/

18 Association for Geographic Information (2010) UK GEMINI

specification for discovery metadata for geospatial data

resources,v.2.1, Cabinet Office, London.

www.agi.org.uk/storage/standards/uk-

gemini/GEMINI2_1_published.pdf

19 Li, C. et al. (2010) ‘BioModels Database: a database of

annotated published models’, BMC Systems Biology, 4(92).

www.ebi.ac.uk/biomodels-main/

Grimm, J. (2008) Wessex Archaeology Metric Archive Project

(WAMAP).

ads.ahds.ac.uk/catalogue/resources.html?abmap_grimm_na_2008

21 Avondo, J. (2010) BioformatsConverter.

cmpdartsvr1.cmp.uea.ac.uk/wiki/BanghamLab/index.php/Bioform

atsConverter

22 Defra, ODPM, NAW, ONS and Countryside Agency (2004) Rural

and Urban Area Classification 2004.

www.statistics.gov.uk/geography/rudn.asp

The London School of Economics and Political Science Library

(2008) Versions Toolkit for authors, researchers and repository

staff.

http://www2.lse.ac.uk/library/versions/VERSIONS_Toolkit_v1_fina

l.pdf

Finch, L. and Webster, J. (2008) Caring for CDs and DVDs. NPO

Preservation Guidance, Preservation in Practice Series, London:

National Preservation Office. www.bl.uk/blpac/pdf/cd.pdf

25 JISC (2004) Virtual research environment programme.

www.jisc.ac.uk/whatwedo/programmes/vre.aspx

26 UK Data Archive (2009) Research ethics and legislation

relevant to data sharing. www.data-archive.ac.uk/create-

manage/consent-ethics/legal

27 UK Data Archive (2009) Consent forms. www.data-

archive.ac.uk/create-manage/consent-ethics/consent

28 Biological Records Centre (n.d.) www.brc.ac.uk

29 UK Data Archive (2009) Anonymisation. www.data-

archive.ac.uk/create-manage/consent-ethics/anonymisation

30 UK Biobank (2007) UK Biobank ethics and governance

framework. www.ukbiobank.ac.uk/docs/EGFlatestJan20082.pdf

31 Secure Data Service (n.d.) securedata.data-archive.ac.uk/

Office for National Statistics (n.d.). Virtual Microdata

Laboratory. www.ons.gov.uk/about/who-we-are/our-services/vml

National Opinion Research Center (n.d.).. Technical assistance

on metadata documentation. www.norc.org/DataEnclave

CIFOR (2005). Forest Spatial Information Catalogue. Available

at gislab.cifor.cgiar.org/fsic/index.htm

Global Biodiversity Information Framework (n.d.) GBIF Data

Portal. data.gbif.org/welcome.htm

managers,4th ed., London: Facet Publishing.

Social and Environmental Conditions in Rural Areas (SECRA)

(n.d.) www.sei.se/relu/secra/

Ball, A (2011) How to Licence Research data. Digital Curation

Centre. www.dcc.ac.uk/resources/how-guides/license-research-

data

39 Charlesworth, A. and Rusbridge, C. (2010) Freedom of

Information and research data: questions and answers.

www.jisc.ac.uk/publications/programmerelated/2010/foiresearch

data.aspx

Cabinet Office (2008) Data handling procedures in

Government: final report.

www.cabinetoffice.gov.uk/sites/default/files/resources/final-

report.pdf

DATA MANAGEMENT CHECKLIST



Are you using standardised and consistent procedures to collect, process, check, validate

and verify data?



Are your structured data self-explanatory in terms of variable names, codes and

abbreviations used?



Which descriptions and contextual documentation can explain what your data mean,

how they were collected and the methods used to create them?



How will you label and organise data, records and files?



Will you apply consistency in how data are catalogued, transcribed and organised, e.g.

standard templates or input forms?



Which data formats will you use? Do formats and software enable sharing and long-term

validity of data, such as non-proprietary software and software based on open

standards?



When converting data across formats, do you check that no data or internal metadata

have been lost or changed?



Are your digital and non-digital data, and any copies, held in a safe and secure location?



Do you need to securely store personal or sensitive data?



If data are collected with mobile devices, how will you transfer and store the data?



If data are held in various places, how will you keep track of versions?



Are your files backed up sufficiently and regularly and are back-ups stored safely?



Do you know what the master version of your data files is?



Do your data contain confidential or sensitive information? If so, have you discussed data

sharing with the respondents from whom you collected the data?



Are you gaining (written) consent from respondents to share data beyond your

research?



Do you need to anonymise data, e.g. to remove identifying information or personal data,

during research or in preparation for sharing?



Have you established who owns the copyright of your data? Might there be joint



Who has access to which data during and after research? Are various access regulations

needed?



Who is responsible for which part of data management?



Do you need extra resources to manage data, such as people, time or hardware?

UK Data Archive

University of Essex

Wivenhoe Park

Colchester, CO4 3SQ

Email: datasharing@data-archive.ac.uk

Telephone: +44 (0)1206 872974

www.data-archive.ac.uk/create-manage

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