This document discusses managing research data for open science based on the UK experience. It outlines key aspects of open science such as making research more open, global, collaborative and closer to society. The document discusses mandates for open research data from funding bodies in the UK and EU, including stipulations in Horizon 2020 and requirements from EPSRC. It defines what constitutes research data and examines challenges around research data management, including technology issues, people issues, policy issues and resources. The importance of data skills training for researchers and data professionals is also covered.
the OpenAIRE Research graph is a massive collection of metadata and links connecting research entities such as articles, datasets, software, and other research outputs
The OpenAIRE project, in the vanguard of the open access and open data movements in Europe was commissioned by the EC to support their nascent Open Data policy by providing a catch-all repository for EC funded research. CERN, an OpenAIRE partner and pioneer in open source, open access and open data, provided this capability and Zenodo was launched in May 2013.
In support of its research programme CERN has developed tools for Big Data management and extended Digital Library capabilities for Open Data. Through Zenodo these Big Science tools could be effectively shared with the long-tail of research.
Big Data Europe SC6 WS 3: Ron Dekker, Director CESSDA European Open Science A...BigData_Europe
Slides for keynote talk at the Big Data Europe workshop nr 3 on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference by Ron Dekker, Director CESSDA: European Open Science Agenda: where we are and where we are going?
OpenAIRE2020, the latest project phase of the OpenAIRE initiative, ends in mid-2018. Yet OpenAIRE will live on as a sustainable legal entity and anticipates continuing to shape the conversation on Open Science implementation in Europe and beyond. This talk will briefly present OpenAIRE's achievements since 2008 and lay out our future priorities for Open Science, including: continued expansion of services from Open Access to Open Science and from Publications to all research artefacts; services for research data management at all levels from local to global; Open Science monitoring and research analytics; engaging researchers and research infrastructures with personalisable services.
Big Data Europe SC6 WS 3: Where we are and are going for Big Data in OpenScie...BigData_Europe
Where we are and are going for Big Data in OpenScience
Keynote talk at the Big Data Europe SC6 Workshop on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017: The perspective of European official statistics by Fernando Reis, Task-Force Big Data, European Commission (Eurostat).
the OpenAIRE Research graph is a massive collection of metadata and links connecting research entities such as articles, datasets, software, and other research outputs
The OpenAIRE project, in the vanguard of the open access and open data movements in Europe was commissioned by the EC to support their nascent Open Data policy by providing a catch-all repository for EC funded research. CERN, an OpenAIRE partner and pioneer in open source, open access and open data, provided this capability and Zenodo was launched in May 2013.
In support of its research programme CERN has developed tools for Big Data management and extended Digital Library capabilities for Open Data. Through Zenodo these Big Science tools could be effectively shared with the long-tail of research.
Big Data Europe SC6 WS 3: Ron Dekker, Director CESSDA European Open Science A...BigData_Europe
Slides for keynote talk at the Big Data Europe workshop nr 3 on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference by Ron Dekker, Director CESSDA: European Open Science Agenda: where we are and where we are going?
OpenAIRE2020, the latest project phase of the OpenAIRE initiative, ends in mid-2018. Yet OpenAIRE will live on as a sustainable legal entity and anticipates continuing to shape the conversation on Open Science implementation in Europe and beyond. This talk will briefly present OpenAIRE's achievements since 2008 and lay out our future priorities for Open Science, including: continued expansion of services from Open Access to Open Science and from Publications to all research artefacts; services for research data management at all levels from local to global; Open Science monitoring and research analytics; engaging researchers and research infrastructures with personalisable services.
Big Data Europe SC6 WS 3: Where we are and are going for Big Data in OpenScie...BigData_Europe
Where we are and are going for Big Data in OpenScience
Keynote talk at the Big Data Europe SC6 Workshop on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017: The perspective of European official statistics by Fernando Reis, Task-Force Big Data, European Commission (Eurostat).
Big Data Europe: SC6 Workshop 3: The European Research Data Landscape: Opport...BigData_Europe
Slides of the keynote at the 3rd Big Data Europe SC6 Workshop co-located at SEMANTiCS2018 in Amsterdam (NL) on: The European Research Data Landscape: Opportunities for CESSDA by Peter Doorn, Director DANS, Chair, Science Europe W.G. on Research Data. Chair, CESSDA ERIC General Assembly
Open AIRE - The use of an Open Science e-Infrastructure for research analysis and impact measurement
Inge Van Nieuwerburgh (Ghent University), Natalia Manola (University of Athens)
Developing a research data centre for Germany: IANUS and its IT-guidelinesariadnenetwork
Presentation by Dr. Felix F. Schäfer,
German Archaeology Institute (DAI), Berlin
Full-day session on archaeological infrastructures and services at the 18th Cultural Heritage and New Technologies (CHNT) conference
Vienna, Austria
11th -13th November 2013
Research data discovery in OpenAIRE (Presentation by Paolo Manghi at DI4R2018)OpenAIRE
"Research data discovery in OpenAIRE".
Presentation by Paolo Manghi from CNR-ISTI, at the Digital Infrastructures Conference 2018, Lisbon. Session: Building better collaborative national networks to support Open Science (Oct. 11, 2018)
Connecting the dots - e-Infra services for open scienceOpenAIRE
Starting from Open access towards services for open science, we present OpenAIRE, OpenMinTeD and OpenUP, three EU projects that build services to facilitate and accelerate open science.
What is an archaeological research infrastructure and why do we need it? Aims...ariadnenetwork
Presentation by:
Edeltraud Aspöck, OREA (Institute for Rriental and European Archaeology)
and
Guntram Geser, Salzburg Research
Full-day session on archaeological infrastructures and services at the 18th Cultural Heritage and New Technologies (CHNT) conference
Vienna, Austria
11th -13th November 2013
The Dutch Approach to Research Data Infrastructurepkdoorn
The Dutch Approach to Research Data Infrastructure
Peter Doorn (DANS), Marc Dupuis (SURF), Maurice Vanderfeesten (SURF)
ANDS Invitational Research Data Infrastructure Workshop, Prato, April 11-13, 2011
Slides accompanying the OpenAIRE Research Graph consultation webinar as held on Janyary 30th 2020.
Presenter: Andrea Mannocci
Recording: https://youtu.be/PCwXMDQb3r8
Presentació a càrrec de Mireia Alcalá, tècnica de Recursos d'Informació al CSUC, duta a terme al workshop en línia "Research Data Management & Open Science" organitzat per l'IDIBELL el 2 de novembre de 2020.
Big Data Europe: SC6 Workshop 3: The European Research Data Landscape: Opport...BigData_Europe
Slides of the keynote at the 3rd Big Data Europe SC6 Workshop co-located at SEMANTiCS2018 in Amsterdam (NL) on: The European Research Data Landscape: Opportunities for CESSDA by Peter Doorn, Director DANS, Chair, Science Europe W.G. on Research Data. Chair, CESSDA ERIC General Assembly
Open AIRE - The use of an Open Science e-Infrastructure for research analysis and impact measurement
Inge Van Nieuwerburgh (Ghent University), Natalia Manola (University of Athens)
Developing a research data centre for Germany: IANUS and its IT-guidelinesariadnenetwork
Presentation by Dr. Felix F. Schäfer,
German Archaeology Institute (DAI), Berlin
Full-day session on archaeological infrastructures and services at the 18th Cultural Heritage and New Technologies (CHNT) conference
Vienna, Austria
11th -13th November 2013
Research data discovery in OpenAIRE (Presentation by Paolo Manghi at DI4R2018)OpenAIRE
"Research data discovery in OpenAIRE".
Presentation by Paolo Manghi from CNR-ISTI, at the Digital Infrastructures Conference 2018, Lisbon. Session: Building better collaborative national networks to support Open Science (Oct. 11, 2018)
Connecting the dots - e-Infra services for open scienceOpenAIRE
Starting from Open access towards services for open science, we present OpenAIRE, OpenMinTeD and OpenUP, three EU projects that build services to facilitate and accelerate open science.
What is an archaeological research infrastructure and why do we need it? Aims...ariadnenetwork
Presentation by:
Edeltraud Aspöck, OREA (Institute for Rriental and European Archaeology)
and
Guntram Geser, Salzburg Research
Full-day session on archaeological infrastructures and services at the 18th Cultural Heritage and New Technologies (CHNT) conference
Vienna, Austria
11th -13th November 2013
The Dutch Approach to Research Data Infrastructurepkdoorn
The Dutch Approach to Research Data Infrastructure
Peter Doorn (DANS), Marc Dupuis (SURF), Maurice Vanderfeesten (SURF)
ANDS Invitational Research Data Infrastructure Workshop, Prato, April 11-13, 2011
Slides accompanying the OpenAIRE Research Graph consultation webinar as held on Janyary 30th 2020.
Presenter: Andrea Mannocci
Recording: https://youtu.be/PCwXMDQb3r8
Presentació a càrrec de Mireia Alcalá, tècnica de Recursos d'Informació al CSUC, duta a terme al workshop en línia "Research Data Management & Open Science" organitzat per l'IDIBELL el 2 de novembre de 2020.
Susanna Sansone's talk at the "Beyond Open" Knowledge Dialogues/Open Data Hong Kong event on research data, hosted at the Hong Kong Innocentre on Monday 20 November 2017.
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
Presentation during the 14th Association of African Universities (AAU) Conference and African Open Science Platform (AOSP)/Research Data Alliance (RDA) Workshop in Accra, Ghana, 7-8 June 2017.
UK Research Data Management: overview to ADBU congress, 19 Sep 2013 by Laura ...L Molloy
Research data management in the UK: interventions by the Jisc Managing Research Data programme and the Digital Curation Centre. Specifies the importance of academic librarians for RDM. Includes links to openly available training resources. Presentation by L Molloy to ABDU congress, 19 Sep 2013 in Le Havre.
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
Trust and Accountability: experiences from the FAIRDOM Commons Initiative.Carole Goble
Presented at Digital Life 2018, Bergen, March 2018. In the Trust and Accountability session.
In recent years we have seen a change in expectations for the management and availability of all the outcomes of research (models, data, SOPs, software etc) and for greater transparency and reproduciblity in the method of research. The “FAIR” (Findable, Accessible, Interoperable, Reusable) Guiding Principles for stewardship [1] have proved to be an effective rallying-cry for community groups and for policy makers.
The FAIRDOM Initiative (FAIR Data Models Operations, http://www.fair-dom.org) supports Systems Biology research projects with their research data, methods and model management, with an emphasis on standards and sensitivity to asset sharing and credit anxiety. Our aim is a FAIR Research Commons that blends together the doing of research with the communication of research. The Platform has been installed by over 30 labs/projects and our public, centrally hosted FAIRDOMHub [2] supports the outcomes of 90+ projects. We are proud to support projects in Norway’s Digital Life programme.
2018 is our 10th anniversary. Over the past decade we learned a lot about trust between researchers, between researchers and platform developers and curators and between both these groups and funders. We have experienced the Tragedy of the Commons but also seen shifts in attitudes.
In this talk we will use our experiences in FAIRDOM to explore the political, economic, social and technical, social practicalities of Trust.
[1] Wilkinson et al (2016) The FAIR Guiding Principles for scientific data management and stewardship Scientific Data 3, doi:10.1038/sdata.2016.18
[2] Wolstencroft, et al (2016) FAIRDOMHub: a repository and collaboration environment for sharing systems biology research Nucleic Acids Research, 45(D1): D404-D407. DOI: 10.1093/nar/gkw1032
Modelos para publicar, consumir y medir la reutilización de los datos derivad...maredata
Modelos para publicar, consumir y medir la reutilización de los datos derivados de la investigación: más allá de las fronteras institucionales y geográficas por Fernanda Peset (UPV), Antonia Ferrer (UPV), Rafael Aleixandre (CSIC), Antonio Vidal-Infer (UV), Adolfo Alonso-Arroyo (UV), Lourdes Castelló-Cogollos, Rut Lucas Domínguez, Andrea Sixto Costoya
Sharpen existing tools or get a new toolbox? Contemporary cluster initiatives...Orkestra
UIIN Conference, Madrid, 27-29 May 2024
James Wilson, Orkestra and Deusto Business School
Emily Wise, Lund University
Madeline Smith, The Glasgow School of Art
0x01 - Newton's Third Law: Static vs. Dynamic AbusersOWASP Beja
f you offer a service on the web, odds are that someone will abuse it. Be it an API, a SaaS, a PaaS, or even a static website, someone somewhere will try to figure out a way to use it to their own needs. In this talk we'll compare measures that are effective against static attackers and how to battle a dynamic attacker who adapts to your counter-measures.
About the Speaker
===============
Diogo Sousa, Engineering Manager @ Canonical
An opinionated individual with an interest in cryptography and its intersection with secure software development.
Acorn Recovery: Restore IT infra within minutesIP ServerOne
Introducing Acorn Recovery as a Service, a simple, fast, and secure managed disaster recovery (DRaaS) by IP ServerOne. A DR solution that helps restore your IT infra within minutes.
This presentation by Morris Kleiner (University of Minnesota), was made during the discussion “Competition and Regulation in Professions and Occupations” held at the Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found out at oe.cd/crps.
This presentation was uploaded with the author’s consent.
Have you ever wondered how search works while visiting an e-commerce site, internal website, or searching through other types of online resources? Look no further than this informative session on the ways that taxonomies help end-users navigate the internet! Hear from taxonomists and other information professionals who have first-hand experience creating and working with taxonomies that aid in navigation, search, and discovery across a range of disciplines.
Obesity causes and management and associated medical conditions
Gobinda Chowdhury
1. Managing Research Data
for Open Science: the
UK experience
Professor Gobinda Chowdhury
Chair, iSchool@Northumbria
Northumbria University, Newcastle, UK
Chair elect, iSchools (www.ischools.org)
2. Open Science
In 2015 European Commissioner Moedas
identified three strategic priorities,
described in Open innovation, Open science,
Open to the world (the 3Os strategy)
Open Science aims at transforming science
through ICT tools, networks and media, to
make research more open, global,
collaborative, creative and closer to society
Open science is about the way research is
carried out, disseminated, deployed and
transformed by digital tools, networks and
media. It relies on the combined effects of
technological development and cultural
change towards collaboration and openness
in research. https://ec.europa.eu/digital-
single-market/en/news/open-innovation-
open-science-open-world-vision-europe
3. Open Science and Data Sharing: why?
Open science makes scientific processes more efficient, transparent and
effective by offering new tools for scientific collaboration, experiments and
analysis and by making scientific knowledge more easily accessible
(https://ec.europa.eu/digital-single-market/en/open-science)
Societal benefits from making research data open are potentially very
significant; including economic growth, increased resource efficiency, securing
public support for research funding and increasing public trust in research
(http://www.rcuk.ac.uk/documents/documents/concordatopenresearchdata-pdf/ )
Estimated that the $13 billion in government spending on the Human Genome
project and its successors has yielded a total economic benefit of about $1 trillion
A British study of its public economic and social research database found that for
every £1 invested by the government, an economic return of £5.40 (The Data
Harvest, 2014… An RDA Europe Report. https://rd-
alliance.org/sites/default/files/attachment/The%20Data%20Harvest%20Final.pdf
4. Open Research Data : Mandates
Stipulated under Article 29.3 of the Horizon 2020 Model Grant Agreement
(including the creation of a Data Management Plan)
EPSRC, UK:
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
in each case the metadata must be sufficient to allow others to understand what
research data exists, why, when and how it was generated, and how to access
Where the research data referred to in the metadata is a digital object it is
expected that the metadata will include use of a robust digital object identifier
(For example as available through the DataCite organisation ‐ http://datacite.org).
5. Open Research Data Management:
EPSRC, UK Mandate for Universities
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 or,
If others have accessed the data, from last date on which access to the data
was requested by a third party;
All reasonable steps will be taken to ensure that publicly‐funded data is not
held in any jurisdiction where the available legal safeguards provide lower
levels of protection than are available in the UK
Research organisations will ensure that effective data curation is provided
throughout the full data lifecycle, with ‘data curation’ and ‘data lifecycle’
being as defined by the Digital Curation Centre.
https://epsrc.ukri.org/files/aboutus/standards/clarificationsofexpectationsre
searchdatamanagement/
6. What is Research Data
Data is “glue of a collaboration” and the “lifeblood of research”
Data includes:
text, sound, still images, moving images, models, games, simulations ….
statistics, collections of digital images, sound recordings, transcripts of interviews,
survey data and fieldwork observations with appropriate annotations, an interpretation,
an artwork, archives, found objects, published texts or a manuscript (Concordat on Open
Research Data, https://www.ukri.org/files/legacy/documents/concordatonopenresearchdata-pdf/)
various types of laboratory data including spectrographic, genomic sequencing, and
electron microscopy data; observational data, such as remote sensing, geospatial, and
socioeconomic data, numerical data and other forms of data either generated or
compiled by humans or machines
(Borgman, C.L. (2012). The conundrum of sharing research data. Journal of the American Society for Information Science
and Technology, 63(6), 1059–1078.
Borgman, C.L., Wallis, J.C., & Mayernik, M.S. (2012). Who’s got the data? Interdependencies in science and technology
collaborations. Computer Supported Cooperative Work, 21(6), 485-523.)
7. Research Data Management
Good data management is fundamental to all stages of the research process
and should be established at the outset
“The careful management of data throughout the research process is crucial
if the data arising from research projects is to be rendered openly
discoverable, accessible, intelligible, assessable and usable.”
(https://www.ukri.org/files/legacy/documents/concordatonopenresearchdata-pdf/)
FAIR (Findable, Accessible, Interoperable and Reusable) guidelines
(http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-
mgt_en.pdf)
A DMP should include a description of all types of data, a description of all
types of metadata and policies used, plans for archiving and preservation, and
a description of resources required for data management (Strasser, C. (2015). Research
data management: a primer publication of the National Information Standards organization. Baltimore, MD: NISO)
8. RDM Challenges and Stakeholders
Good data management is fundamental to all stages of the research process
and should be established at the outset (Researchers + Data Librarian + Inst.)
Data management for Open Sc. (Data Librarian + Researchers + Institutions)
Data curation (Data Librarian/Curator + Institution + Govt./Funding Bodies)
Data Sharing Policies (Govt., Funding bodies, Institutions, Prof. Bodies)
9. RDM Technologies and Systems
National e.g. ANDS (https://www.ands.org.au/)
In-house/Institutional, e.g. Research data Oxford (http://researchdata.ox.ac.uk/);
RDS Edinburgh University (https://www.ed.ac.uk/information-services/research-
support/research-data-service) Not-for profit e.g. DataCite
(https://www.datacite.org/ )
Subject/Discipline, e.g. UK Data Archive (http://www.data-archive.ac.uk); Github
(https://github.com/) ………..
Commercial e.g. Figshare (https://figshare.com/)
Aggregator portal: Jisc research Data Discovery Service
(http://researchdiscoveryservice.jisc.ac.uk/dataset)
Whichever option is chosen RDM is resource-intensive and hence requires a
sustainable business model and supporting policies
10. A big question: Do researchers want to
share data?
Does every researcher want to share data?
Do the researchers have the necessary awareness and data management
skills?
Are there specific sharing practices and culture in specific disciplines?
Do the researchers have any concerns around data sharing?
What are the incentives of data sharing?
....... And many more related questions
11. RDM Training Policies
Support for the development of appropriate data skills is recognised as a responsibility for all
stakeholders (Principle 9 of the Concordat on Open Research Data, 2016
(http://www.rcuk.ac.uk/documents/documents/concordatopenresearchdata-pdf/)
Researchers:
For research institutions this should include the provision of researcher training opportunities provided in an
organised and professional manner.
It is imperative also that funding organisations, alongside research institutions, support the provision of such
training through appropriate funding routes.
Individual researchers must also ensure their own data skills are at a level sufficient to meet their own
obligations whilst understanding the benefits to themselves of a higher level of understanding.
Data Scientists:
“The specialised skills of data scientists are crucial in supporting the data management needs of researchers
and institutions
Research institutions and funders should work together to help build underpinning capacity and capability in
this area, and to attract and retain such specialists by developing well designed and sustainable career paths
for them”
12. Key RDM Challenges
Technology
ICT infrastructure for storage, management, curation
Software, metadata, interoperability
Access and reuse
People
Researchers: culture, data literacy, training requirements
Data Scientists: data management, data curation, training
Users: researchers, businesses, governments, policy-makers, general public ….
Policy
Governments, Funding agencies, Institutions, Professional bodies ….
Resources
Financial, human, legal
13. RDM: Technology Issues
Volume, variety & growth of data
Software dependence of data
Multiple file formats
Data curation
Retrieval issues
14. Is Data Retrieval = Information
Retrieval?
Most data retrieval services are based on the text retrieval paradigm
The key difference between IR and DR arises from the data elements
Using datasets often requires a no. of associated files
Search output in DR is often very large
Search output in DR requires downloading before access
Very little research has been undertaken on data seeking behaviour
No reliable data seeking and retrieval model exists
15. Discipline Keywords Data Retrieval
Average File
Size
Information
Retrieval
Average File Size
Arts &
Humanities
art museums 5.708 MB 0.820 MB
nineteenth century 2.537 MB 1.042 MB
“world war” 5.766 MB 0.508 MB
medieval 5.053 MB 1.091 MB
popular music 8.353 MB 1.000 MB
Social Sciences unemployment 3.059 MB 0.455 MB
cognition 11.681 MB 1.612 MB
imprisonment 1.837 MB 0.503 MB
“labour law” 1.667 MB 0.410 MB
“trade union” 2.073 MB 0.748 MB
Natural Sciences marine life 15.707 MB 1.491 MB
“climate change” 1.655 MB 2.497 MB
“renewable energy” 758.000 MB 3.606 MB
“ultraviolet light” 495.900 MB 1.991 MB
“oxidative phosphorlyation” 40.242 MB 1.895 MB
Computer &
Information
Science
search behaviour 656.000 MB 0.731 MB
face recognition 1.391 GB 1.535 MB
computer vision 1.330 GB 2.782 MB
research data sharing 1.014 MB 0.521 MB
social media data 16.329 MB 1.078 MB
16. Metadata for RDM
Tools:
DCC Metadata for Research disciplines
(http://www.dcc.ac.uk/resources/metadata-standards)
RDA (https://www.rd-alliance.org/groups/metadata-standards-catalog-working-
group.html)
Key questions:
How much metadata is required?
Who will do the tagging?
Who will check for consistency and standards?
How will it be used?
17. Data sharing: Researchers’ culture,
awareness, concerns…
Findings from a study on researchers from three countries:
nearly 80% of researchers do not want to share data with anyone
Less than 25% researchers agree that their university encourages OA data sharing
Only 31% researchers are familiar with the OA requirements of the funding bodies
Nearly 95% of researchers are either uncertain or do not know whether their
university has a prescribed metadata set
the key concerns for OA and data sharing include: legal and ethical issues, misuse
and misinterpretation of data, and fear of losing the scientific edge
only a third of the researchers have a unique researcher ID
Over 70% of researchers did not have any formal training in DMP, metadata,
consistent file naming and version control or data citation
18. TULIP: Information Management
Research to address RDM Challenges
Technology
Research data repository/services: Local vs. National repository services
Research data management: standards & practices -- ORCID, DOI, Metadata, Citation, Quality, Version Control…
Research data discovery & access -- from IR paradigm to DR paradigm: user-centred & discipline-specific design
Research data sharing/reuse: data quality metrics
Users: research culture, training
Data Literacy and RDM training and advocacy across all disciplines
Librarians
Education and training programmes for data librarians
Industries
New research data service industries; Public-private partnership; Sustainability
Policies
OA mandates; Incentives for researchers; Data quality; Ethics, Curation…
19. Resources
Bugaje, M. and Chowdhury, G. (2018). Data Retrieval = Text Retrieval?
iConference2018. In Chowdhury, G., McLeod, J., Gillet, V. and Willett, P.
(eds). Transforming digital worlds: proceedings of the iConference2018.
March 25-28, Sheffield, LNCS 10766, Springer, pp. 253-262.
Chowdhury, G. Boustany, J., Kurbanoglu, S., Unal, Y. and Walton, G. (2017).
Preparedness for Research Data Sharing: A Study of University Researchers in
Three European Countries, ICADL2017, Bangkok, 13-15 November, 2017,
LNCS10647, pp. 104-116
DCC Checklist for DMP:
http://www.dcc.ac.uk/sites/default/files/documents/resource/DMP/DMP_Ch
ecklist_2013.pdf
DCC Curation Lifecycle model (http://www.dcc.ac.uk/resources/curation-
lifecycle-model)