The document summarizes findings from a survey on research data management practices. Some key findings include:
- 17% of researchers had lost data due to issues like hardware failure and human error.
- 68% of researchers currently share or plan to share their data. Main motivations for sharing include funder requirements and increasing citation/impact.
- Only 16% of researchers currently use university research data management support services, indicating a need to improve outreach and support.
- 41% of researchers hold some type of sensitive data like patient or personal information, underscoring the need for secure data storage and sharing policies.
Show me the money - the long path to a sustainable RDM FacilityJisc RDM
Show me the money - the long path to a sustainable RDM Facility
A presentation by Marta Teperek from Cambridge University about the challenges encountered in developing business case and costing models for managing research data. Session held at Cardiff University for the Research Data Network event in May 2016.
Grampian safe haven, research data networkJisc RDM
Safe havens" should be developed as an environment for population-based research where the risk of identifying individuals is minimized. Researchers in safe havens are bound by strict confidentiality codes preventing disclosure of personally identifying information and providing sanctions for breaches of confidentiality.
The document discusses Frictionless Data, an initiative by the Open Knowledge Foundation to make research data easier to share, consume, and analyze. It aims to introduce standards and tools to "containerize" datasets using simple specifications like Tabular Data Package. This would make data easier to integrate into tools and platforms, find, maintain quality for, and analyze. It discusses problems like lack of standards, tools to validate datasets are presented. Examples of early implementations that integrate validation checks and continuous validation are also provided.
Gold, silver, bronze - research data networkJisc RDM
This document discusses the development of a scalable data model to meet researcher metadata requirements. It describes conceptual and practical processes used, including aligning with standards and popular data models. An example shows over 1500 lines of metadata XML for one data package. A research data shared service is proposed to provide bronze, silver, or gold ratings for metadata completeness. Focus groups with researchers are evaluating metadata fields and use cases to test the infrastructure. Exercises are used to gather information about researchers' metadata production and needs at different research lifecycle stages.
Standardising research data policies, research data networkJisc RDM
The document discusses standardizing research data policies across journals. It describes an expert group working to develop templates and guidance for data policies. It also discusses a collaboration to implement the Joint Declaration of Data Citation Principles. The group is working with Springer Nature to help standardize their data policies across journals into four main types. The goal is to improve data sharing, citation and reuse.
Show me the money - the long path to a sustainable RDM FacilityJisc RDM
Show me the money - the long path to a sustainable RDM Facility
A presentation by Marta Teperek from Cambridge University about the challenges encountered in developing business case and costing models for managing research data. Session held at Cardiff University for the Research Data Network event in May 2016.
Grampian safe haven, research data networkJisc RDM
Safe havens" should be developed as an environment for population-based research where the risk of identifying individuals is minimized. Researchers in safe havens are bound by strict confidentiality codes preventing disclosure of personally identifying information and providing sanctions for breaches of confidentiality.
The document discusses Frictionless Data, an initiative by the Open Knowledge Foundation to make research data easier to share, consume, and analyze. It aims to introduce standards and tools to "containerize" datasets using simple specifications like Tabular Data Package. This would make data easier to integrate into tools and platforms, find, maintain quality for, and analyze. It discusses problems like lack of standards, tools to validate datasets are presented. Examples of early implementations that integrate validation checks and continuous validation are also provided.
Gold, silver, bronze - research data networkJisc RDM
This document discusses the development of a scalable data model to meet researcher metadata requirements. It describes conceptual and practical processes used, including aligning with standards and popular data models. An example shows over 1500 lines of metadata XML for one data package. A research data shared service is proposed to provide bronze, silver, or gold ratings for metadata completeness. Focus groups with researchers are evaluating metadata fields and use cases to test the infrastructure. Exercises are used to gather information about researchers' metadata production and needs at different research lifecycle stages.
Standardising research data policies, research data networkJisc RDM
The document discusses standardizing research data policies across journals. It describes an expert group working to develop templates and guidance for data policies. It also discusses a collaboration to implement the Joint Declaration of Data Citation Principles. The group is working with Springer Nature to help standardize their data policies across journals into four main types. The goal is to improve data sharing, citation and reuse.
Business case and cost modelling for an end-to-end RDM serviceJisc RDM
Presentation by Frances Madden and Dave Cobb on the Royal Holloway business case and cost modelling for RDM. Cardiff, May 2016, research data network event.
What I wish I’d known at the start! What I wish I’d known at the start! Lessons learned the hard way when setting up RDM services;
Stephen Grace, London South Bank University, Sarah Jones, DCC; Research Data Network
EC Open Access Co-ordination workshop - 4th May 2011Jisc
This document discusses open scholarship and the value of open access to scholarly works. It notes that opening up the scholarly record through open access, open bibliography, open citation, and open data can help researchers. It discusses ensuring quality in open scholarship through peer review, citations, and other measures. The document also highlights studies that demonstrate the cost-benefits of open access. Finally, it discusses how open scholarship can help power the knowledge economy and support areas like health care and science policy.
Implementing figshare, research data networkJisc RDM
Implementing figshare and engaging researchers,
Research data network, September 2016, Georgina Parsons, Cranfield University and Megan Hardeman, figshare.
This document discusses supporting data sharing through publisher policies and services. It summarizes that over 40 research funders globally require data archiving as a condition for grants. While funder policies motivate researchers to share data, complying with these policies is challenging for over half of researchers. The document then discusses Springer Nature's efforts to standardize and harmonize research data policies across journals, provide related support services to help with compliance, and lessons learned from their implementation progress.
Infrastructure requirements for open scholarship – Jisc and CNI conference 10...Jisc
1. The document discusses the infrastructure requirements for open scholarship and open access. It outlines various stakeholders and events in the research process like authorship, publishing, and accessing published works.
2. It also maps the various systems, standards, and services needed to support open scholarship like repositories, identifiers, licenses, and usage statistics. Ensuring the sustainability of critical infrastructure services is an ongoing challenge given differences between regional and national organizations.
3. Coordination between services may help address sustainability by consolidating functionality and presenting funders with coordinated offers based on common use cases.
Strand 1: Connecting research and researchers: An introduction to ORCID by Ed...OAbooks
ORCID is an open, non-profit organization that provides a registry of unique researcher identifiers and aims to link researchers to their professional activities such as publications, datasets, and more. The presentation discusses the problems ORCID aims to address like linking researchers across databases and improving discoverability. It outlines ORCID's mission, benefits to the research community, how the ORCID registry works, privacy considerations, integration opportunities, growth since launch, international usage, members, support available, and how to join ORCID.
HESA data, describing research activity and #REF2021Jisc RDM
Research Data Network
Dan Cook, Head of Data Policy & Development at HESA;
An update on the work Hesa is doing in relation to research data, especially in the context of the forthcoming REF.
Lorraine Beard RDM at the University of ManchesterJisc
The University of Manchester has established a Research Data Management service and policy to support researchers in managing their research data. The RDM service was launched in 2011 and is a collaboration between the University Library and IT Services. It aims to provide guidance, tools, and infrastructure to help researchers comply with funder data sharing requirements and best practices for data management, storage, and preservation. Key challenges for the future include developing metadata standards, tools for data sharing and publishing, coordinating expertise across departments, and adapting to a changing research environment and funder landscape.
Certifying and Securing a Trusted Environment for Health Informatics Research...Jisc
The document discusses the certification and securing of a trusted environment for health informatics research data at the University of Dundee. It provides an overview of the Health Informatics Centre, its research data management platform, safe haven architecture, and ISO27001 certification. The platform standardizes data extraction and release, adds metadata and quality checks. A safe haven uses pseudonymized data and virtual environments prevent data from leaving. ISO27001 certification provides governance and reduces documentation through standardized information security practices.
The document summarizes a workshop on interoperability between grant funding systems. Key points discussed include:
- Desire to reduce duplication by allowing data to be shared between research organization and funding council systems.
- Initial outcomes from the workshop on possible ways to share data on costs, people, students, spending, and outcomes.
- Barriers to interoperability include the diversity of research organization systems and incomplete adoption of standards.
- The new grants system will take an agile approach, gradually introducing functionality based on user research and testing.
Opening up data – Jisc and CNI conference 10 July 2014Jisc
The document discusses research data management and open data. It notes that Creative Commons tools can be used to make data openly available, and have been successfully implemented in various disciplines. It also discusses requirements and guidelines from funders like NIH and NSF to share data. Trends in data sharing policies from journals in different fields over time are shown. Challenges to sharing research data are presented. The development of infrastructure to support open data is discussed.
Martin Lewis and Stephen Pinfield Research Data Management - where should col...Jisc
This document discusses where collaboration on research data management (RDM) should occur. It describes potential spaces for RDM collaboration at the interplanetary, international, national, regional, and institutional levels. At the institutional level, the key components of an RDM program are identified as strategies, policies, guidelines, processes, technologies, and services. Drivers for RDM, influencing factors, and stakeholders are also discussed. Challenges to collaboration mentioned include developing a shared national vision to avoid a divided support system, and overcoming territorial and identity issues within institutions.
Building a collaborative RDM community, research data networkJisc RDM
This document summarizes Dr. Marta Teperek's presentation on building a collaborative research data management (RDM) community. The presentation covered how not to start RDM services by mandating data sharing, and instead focusing on the benefits of sharing. It discussed Cambridge University's democratic approach to developing RDM services by empowering researchers, and the positive feedback received. Collaboration, open communication, and shaping services and policies with researchers were emphasized as key to success.
This document provides an overview and agenda for a research data network event focusing on research data management. The event aims to discuss latest developments in RDM tools and services, share ideas and practices, and network. Presentations from the event will be shared online. Logistics like wifi access and note sharing are provided. The document also includes an agenda item on business case and costing for RDM that will discuss pain points around tracking costs, cost recovery, and evaluating benefits of RDM. It will share outputs from a Jisc project on developing business cases and costing models for RDM.
Implementing Archivematica, research data networkJisc RDM
This presentation discusses implementing Archivematica for preserving research data at the University of York and Hull. It covers background on the project, challenges implementing Archivematica, issues with identifying unknown file formats in research data, and future plans to move from proof of concept to production. The project tested pulling metadata from systems into Archivematica for ingest and explored packaging data for long-term preservation and access. A major challenge was the large number of unidentified file formats, which the project is addressing by developing new file format signatures.
TrunkDB is the new cloud-based version of ORDs (Oxford Research Database Service), which was originally designed to provide database hosting and manipulation services for researchers. TrunkDB allows researchers to create multiple versions of databases, share data with colleagues, and access data securely from anywhere through an online interface. It aims to support researchers by treating their data, rather than just the database, as the primary object and allowing various ways of organizing, updating, and viewing data over time through a versioning system. TrunkDB is currently in private beta testing with plans to launch publicly in June.
Business case and cost modelling for an end-to-end RDM serviceJisc RDM
Presentation by Frances Madden and Dave Cobb on the Royal Holloway business case and cost modelling for RDM. Cardiff, May 2016, research data network event.
What I wish I’d known at the start! What I wish I’d known at the start! Lessons learned the hard way when setting up RDM services;
Stephen Grace, London South Bank University, Sarah Jones, DCC; Research Data Network
EC Open Access Co-ordination workshop - 4th May 2011Jisc
This document discusses open scholarship and the value of open access to scholarly works. It notes that opening up the scholarly record through open access, open bibliography, open citation, and open data can help researchers. It discusses ensuring quality in open scholarship through peer review, citations, and other measures. The document also highlights studies that demonstrate the cost-benefits of open access. Finally, it discusses how open scholarship can help power the knowledge economy and support areas like health care and science policy.
Implementing figshare, research data networkJisc RDM
Implementing figshare and engaging researchers,
Research data network, September 2016, Georgina Parsons, Cranfield University and Megan Hardeman, figshare.
This document discusses supporting data sharing through publisher policies and services. It summarizes that over 40 research funders globally require data archiving as a condition for grants. While funder policies motivate researchers to share data, complying with these policies is challenging for over half of researchers. The document then discusses Springer Nature's efforts to standardize and harmonize research data policies across journals, provide related support services to help with compliance, and lessons learned from their implementation progress.
Infrastructure requirements for open scholarship – Jisc and CNI conference 10...Jisc
1. The document discusses the infrastructure requirements for open scholarship and open access. It outlines various stakeholders and events in the research process like authorship, publishing, and accessing published works.
2. It also maps the various systems, standards, and services needed to support open scholarship like repositories, identifiers, licenses, and usage statistics. Ensuring the sustainability of critical infrastructure services is an ongoing challenge given differences between regional and national organizations.
3. Coordination between services may help address sustainability by consolidating functionality and presenting funders with coordinated offers based on common use cases.
Strand 1: Connecting research and researchers: An introduction to ORCID by Ed...OAbooks
ORCID is an open, non-profit organization that provides a registry of unique researcher identifiers and aims to link researchers to their professional activities such as publications, datasets, and more. The presentation discusses the problems ORCID aims to address like linking researchers across databases and improving discoverability. It outlines ORCID's mission, benefits to the research community, how the ORCID registry works, privacy considerations, integration opportunities, growth since launch, international usage, members, support available, and how to join ORCID.
HESA data, describing research activity and #REF2021Jisc RDM
Research Data Network
Dan Cook, Head of Data Policy & Development at HESA;
An update on the work Hesa is doing in relation to research data, especially in the context of the forthcoming REF.
Lorraine Beard RDM at the University of ManchesterJisc
The University of Manchester has established a Research Data Management service and policy to support researchers in managing their research data. The RDM service was launched in 2011 and is a collaboration between the University Library and IT Services. It aims to provide guidance, tools, and infrastructure to help researchers comply with funder data sharing requirements and best practices for data management, storage, and preservation. Key challenges for the future include developing metadata standards, tools for data sharing and publishing, coordinating expertise across departments, and adapting to a changing research environment and funder landscape.
Certifying and Securing a Trusted Environment for Health Informatics Research...Jisc
The document discusses the certification and securing of a trusted environment for health informatics research data at the University of Dundee. It provides an overview of the Health Informatics Centre, its research data management platform, safe haven architecture, and ISO27001 certification. The platform standardizes data extraction and release, adds metadata and quality checks. A safe haven uses pseudonymized data and virtual environments prevent data from leaving. ISO27001 certification provides governance and reduces documentation through standardized information security practices.
The document summarizes a workshop on interoperability between grant funding systems. Key points discussed include:
- Desire to reduce duplication by allowing data to be shared between research organization and funding council systems.
- Initial outcomes from the workshop on possible ways to share data on costs, people, students, spending, and outcomes.
- Barriers to interoperability include the diversity of research organization systems and incomplete adoption of standards.
- The new grants system will take an agile approach, gradually introducing functionality based on user research and testing.
Opening up data – Jisc and CNI conference 10 July 2014Jisc
The document discusses research data management and open data. It notes that Creative Commons tools can be used to make data openly available, and have been successfully implemented in various disciplines. It also discusses requirements and guidelines from funders like NIH and NSF to share data. Trends in data sharing policies from journals in different fields over time are shown. Challenges to sharing research data are presented. The development of infrastructure to support open data is discussed.
Martin Lewis and Stephen Pinfield Research Data Management - where should col...Jisc
This document discusses where collaboration on research data management (RDM) should occur. It describes potential spaces for RDM collaboration at the interplanetary, international, national, regional, and institutional levels. At the institutional level, the key components of an RDM program are identified as strategies, policies, guidelines, processes, technologies, and services. Drivers for RDM, influencing factors, and stakeholders are also discussed. Challenges to collaboration mentioned include developing a shared national vision to avoid a divided support system, and overcoming territorial and identity issues within institutions.
Building a collaborative RDM community, research data networkJisc RDM
This document summarizes Dr. Marta Teperek's presentation on building a collaborative research data management (RDM) community. The presentation covered how not to start RDM services by mandating data sharing, and instead focusing on the benefits of sharing. It discussed Cambridge University's democratic approach to developing RDM services by empowering researchers, and the positive feedback received. Collaboration, open communication, and shaping services and policies with researchers were emphasized as key to success.
This document provides an overview and agenda for a research data network event focusing on research data management. The event aims to discuss latest developments in RDM tools and services, share ideas and practices, and network. Presentations from the event will be shared online. Logistics like wifi access and note sharing are provided. The document also includes an agenda item on business case and costing for RDM that will discuss pain points around tracking costs, cost recovery, and evaluating benefits of RDM. It will share outputs from a Jisc project on developing business cases and costing models for RDM.
Implementing Archivematica, research data networkJisc RDM
This presentation discusses implementing Archivematica for preserving research data at the University of York and Hull. It covers background on the project, challenges implementing Archivematica, issues with identifying unknown file formats in research data, and future plans to move from proof of concept to production. The project tested pulling metadata from systems into Archivematica for ingest and explored packaging data for long-term preservation and access. A major challenge was the large number of unidentified file formats, which the project is addressing by developing new file format signatures.
TrunkDB is the new cloud-based version of ORDs (Oxford Research Database Service), which was originally designed to provide database hosting and manipulation services for researchers. TrunkDB allows researchers to create multiple versions of databases, share data with colleagues, and access data securely from anywhere through an online interface. It aims to support researchers by treating their data, rather than just the database, as the primary object and allowing various ways of organizing, updating, and viewing data over time through a versioning system. TrunkDB is currently in private beta testing with plans to launch publicly in June.
Clipper is a web annotation toolkit created by a consortium including City of Glasgow College and The Open University to enable annotation and analysis of audiovisual media without copying large files. It allows users to create "virtual clips" from media sources and annotate them using text and share the clips via URIs. Clipper aims to make audiovisual media as easy to work with as text. It demonstrates potential benefits for research including open data, reproducibility, collaboration, and impact. The toolkit is built using MEAN stack technologies and aligns with emerging W3C annotation standards.
Measuring the costs and benefits of RDM to supporta a business caseJisc RDM
Graham Hay of Cambridge Econometrics on measuring the costs and benefits of RDM to support a business case for the Research Data Network event in May 2016, Cardiff University.
Managing sensitive data at the University of BristolJisc RDM
Presentation on managing sensitive data at the University of Bristol by Kellie Snow, Research Data Librarian for the Research Data Network event, May 2016, Cardiff University.
UK Research Data Discovery Service metadata schemaJisc RDM
An overview of the metadata schema being developed for the UK research data discovery service. Dom Fripp at the Research Data Network event at Cardiff University, May 2016.
Stop press: should embargo conditions apply to metadata?Jisc RDM
Sarah Middle of Cambridge University discusses whether embargo conditions should apply to metadata. Session held at the Research Data Network event in May 2016, Cardiff University.
Demonstration of the 4C cost comparison toolJisc RDM
The document discusses a demonstration of the 4C Cost Comparison Tool, which allows organizations to map asset types, activities, purchases, and staff to create cost sets for research data management. It describes the process of creating an organization profile, cost set, and activity mapping in the tool. The presentation concludes with a live demo of the tool and links to related projects for assessing the costs of research data management.
A demo by Matthew Addis of Arkivum on using Archivematica with ownCloud on a Mac. Session held at Cardiff University for the Research Data Network event in May 2016.
Why does research data matter to librariesJisc RDM
- Research data matters to libraries because it is increasingly being produced and collected by researchers, and there are growing requirements to manage and preserve it.
- A survey found that while most researchers currently manage their own data, there is a trend toward using institutional repositories and libraries more for long-term preservation.
- Libraries are well-suited to help with research data management because of their experience organizing and describing information over long periods of time, but there are also challenges due to differences across disciplines in how data is defined and treated.
- As funders and journals require better data sharing practices, libraries have an opportunity to take a more active role in helping researchers and institutions capture, describe, and manage research data over
This document summarizes challenges and efforts around managing research data in the arts and humanities. It discusses how "data" is not clearly defined in these domains as it is in STEM fields. Universities like UAL and GSA are working to educate researchers on identifying, organizing, and sharing their diverse research outputs and formats. This includes developing data repositories, training, and communities of practice to establish best practices and support researchers in meeting new data management policies and obligations. While there are fewer external funder requirements compared to STEM, these universities are using collaborative approaches to engage arts and humanities researchers in responsible research data management.
The document discusses managing digital object identifiers (DOIs) across their lifecycles and the challenges associated with aligning DOIs with the publishing lifecycle. It outlines the DOI lifecycle including minting, persistence of identified objects, and withdrawal. The publishing lifecycle is also described involving placeholders, peer review, access, and embargoes. Issues with managing DOIs outside repositories and setting expectations through DOI policies are mentioned.
Researcher data management shared service for the UK – John Kaye, Jisc
Hydra - Tom Cramer, Stanford University and Chris Awre, University of Hull
Addressing the preservation gap at the University of York - Jenny Mitcham, University of York
Emulation developments - David Rosenthal, Stanford University
Jisc and CNI conference, 6 July 2016
Towards an integrated UK national research data infrastructureJisc RDM
Jisc seminar at Science and Innovation 2016 conference.
Daniela Duca, Martin Hamilton, Fiona Murphy, Athanasios Velios.
Slides include: overview of Jisc, research data shared service, research data discovery service, giving researchers credit for their data and recording research data for artists.
The document discusses a leaders conference on UK data management environments and support. It provides information on the current UK research data management policy environment, systems used, and challenges. It introduces Jisc's proposed Research Data Shared Service as a sector-wide approach to address these issues by providing a single, integrated solution for research data management across the UK. Key benefits identified include optimizing costs, growing the value of research data, and increasing compliance with funder requirements for data preservation and sharing. The development history and features of the proposed shared service are outlined.
Jisc is a UK organization that supports digital technology use in education and research. There is growing pressure on universities to better manage research data due to funder policies requiring data sharing. Jisc is working with universities to build research data management capacity through infrastructure projects, training programs, and developing best practices. Barriers to progress include low researcher priority for data management and lack of funding and resources.
Rachel Bruce UK research and data management where are we nowJisc
The document discusses the state of research data management in UK universities. It finds that while areas like data cataloguing and access/storage systems are progressing, governance of data access/reuse and digital preservation/planning are lagging. Barriers to progress include low researcher priority, funding availability, and lack of staff/infrastructure. Gaps include defining responsibilities, standards, costs, and tools. Coordination and sharing resources across institutions is needed to help universities advance research data management.
This document provides an overview of a webinar on digital curation and research data management for universities. The webinar covers an introduction to digital curation, the benefits and drivers for research data management, current initiatives in UK universities, and the role of libraries in supporting research data management. Libraries are increasingly involved in developing institutional policies, providing training, and advising researchers on writing data management plans and sharing data. The webinar highlights training opportunities for librarians to develop skills in research data management and digital curation.
Is democracy the right system? Building an engaged RDM community - Marta Tepe...Mari Tinnemans
This document summarizes Dr. Marta Teperek's presentation on building an engaged research data management (RDM) community at the University of Cambridge. It describes how the initial top-down approach to mandating RDM policies faced resistance from researchers. An alternative approach involved understanding researchers' perspectives, collaborating across the university, and empowering researchers to help shape RDM services and policies. This led to increased data sharing and positive feedback on training. While time-consuming, taking a democratic approach helped build trust and engagement from the research community.
RD shared services and research data springJisc RDM
Daniela Duca's presentation at the DataVault workshop on 29 June. An overview of research at risk, research data shared service and research data spring.
The Research Data Alliance: Opportunities for Public/Private Partnerships in...Research Data Alliance
The document discusses the Research Data Alliance (RDA), an international organization focused on reducing barriers to data sharing and exchange. It provides information on:
- What RDA is and its goals of openly sharing data across technologies, disciplines and countries.
- RDA's activities including working groups and interest groups focused on developing infrastructure, standards, and best practices.
- Benefits of RDA membership for individuals, researchers, enterprises/businesses, and policymakers.
- Examples of RDA recommendations and outputs like data citation standards and metadata directories.
- RDA community size and composition, including over 4,000 members from 110 countries in academia, government, and private industry.
This document summarizes an event about organizational identifiers (OrgIDs) for UK research. It discusses Jisc's role in supporting the UK research sector through shared digital infrastructure and services. It also outlines Jisc's work with CASRAI to pilot the use of OrgIDs and other research data standards through several working groups. One such working group examined key OrgID candidates and produced recommendations for a hybrid approach relying on ISNI as the backbone standard. The document provides context on related areas like funder reporting requirements and the need for better integration across research systems in the UK.
Managing data behind creative masterpiecesJisc RDM
The document discusses research data in creative fields and Jisc's Research Data Shared Service (RDSS) to help manage such data. RDSS aims to enable open science through efficient capture, preservation and reuse of research data. It will provide core functions like deposit, description, storage, publication and preservation of data, as well as reporting and advisory services. RDSS addresses key issues in research data management to help reduce costs and risks for researchers and institutions.
Research Data Management - Gaps and OpportunitiesMartin Hamilton
Slides from my talk with Rachel Bruce on challenges and opportunities for research data management at the EPSRC / Digital Curation Centre event "Assessing institutional awareness & readiness for compliance with EPSRC Policy Framework" in Glasgow on 8th May 2014. For more information see http://www.dcc.ac.uk/events/other-dcc-events/assessing-institutional-readiness
Data sharing lessons learnt at Cambridge: the whys and howsMarta Teperek
This document summarizes a presentation about lessons learned from implementing data sharing services at the University of Cambridge. It discusses how not to initially approach researchers by focusing on compliance, and instead emphasizing the benefits of sharing. Cambridge developed resources and advocacy to support sharing, and took a democratic approach to involve researchers. This engagement led to increased early data sharing and positive feedback from researchers. The key lessons are to collaborate with researchers and communicate openly about data management and sharing.
The document summarizes a project at the University of Southampton to develop an institutional data management blueprint. It discusses conducting a user survey of researchers to understand current practices and needs. It also describes preliminary feedback identifying quick wins, dreams, and issues regarding data management. The project aims to produce guidelines and implement pilot infrastructure and training to help researchers better manage their research data.
Mind the Gap: Reflections on Data Policies and PracticeLizLyon
UKOLN is supported by the Mind the Gap project which reflects on data policies and practices. The document discusses the current state of data practices in institutions, challenges around open science and data sharing, and the need for improved data policies, planning tools, and codes of conduct to help researchers with issues like data storage, sharing, and long-term preservation. It also explores how emerging technologies and areas like genomics, personalized medicine, and citizen science will impact future data practices and policies.
The document summarizes a workshop hosted by the NIH Associate Director for Data Science to discuss charting the future of data science at NIH. The workshop goals were to get input from all stakeholders, identify strategic directions, policies, and funding initiatives, and have participants leave as advocates and supporters. The agenda included providing background, open discussion, identifying topics for breakout groups, subgroup discussions, and reporting back. The document provides context on current NIH data science efforts and examples of collaborators in building a biomedical research digital enterprise.
This presentation was provided by Tim McGeary of Duke University during the NISO virtual conference, Open Data Projects, held on Wednesday, June 13, 2018.
Similar to DAF Survey Results, research data network (20)
Recent national and international mandates and reports seek to promote an open research infrastructure which facilitates easy access to knowledge and information for all. For example, The UK Open Research Data Task Force report, released in February 2019, recommends user-friendly services for research data management and infrastructure to maximise interoperability and discoverability.
Jisc has built the Open Research Hub (JORH), which integrates a repository, preservation, reporting and storage platform. This cloud-based service is a community governed, multi-tenant solution for universities and other research institutions to manage, store, preserve and share their published research data. Based on existing open standards, the service’s open and extensive data model incorporates best practice from across the sector, including DataCite, CrossRef, CERIF, Dublin Core and PREMIS.
While the Hub was built to address the needs of research data curation, its adoption of open, best practice standards means it has the potential to allow the service to handle a much wider range of digital research objects, including Open Access articles, theses and software. The data model, rich messaging layer and an open API facilitate interoperability with other institutional and scholarly communications systems. This provides the potential for the Hub to underpin infrastructure capable of meeting the requirements of an ever-evolving open research agenda.
This talk will introduce some of the key initiatives seeking to shape open research infrastructure and discuss how the Hub’s current and future development is directed towards facilitating open research best practice. Consideration will be given to how the Hub either meets or can meet recent recommendations such as FAIR, Plan S, ORDTF and the COAR’s Next Generation Repositories.
Jisc Research Data Shared Service Open Repositories 2018 PaperJisc RDM
The document discusses Jisc's plans to develop a national research data shared service in the UK. It provides context on open science policies and the need for research data management and preservation. It then summarizes Jisc's proposal to create a multi-tenant research repository with integrated preservation systems. This would provide a scalable, sustainable platform to help universities meet requirements for managing and preserving research outputs including data, software, and publications. The service is currently in development with pilots planned, and would offer repositories, preservation, or an end-to-end solution to members.
Jisc Research Data Shared Service Open Repositories 2018 24x7Jisc RDM
This document discusses the Jisc Research Data Shared Service (RDSS) and its priorities and developments. The RDSS aims to provide a scalable, sustainable, and intuitive shared research data service. It offers three standard service options - an end-to-end service, repository service, and preservation service. The RDSS is working on developing a multi-tenant research repository and integrating with other Jisc services to support the full research lifecycle from publication to preservation. Further developments include preservation action registries and a potential national shared research platform.
Jisc Research Data Shared Service - a Samvera case studyJisc RDM
As part of its Research Data Shared Service (RDSS), Jisc has been developing a repository component as part of its core architecture . Through making an integrated research data management platform available to UK Universities, there is a growing demand from small to medium HEIs for the RDSS to provide a single repository solution that fits their needs for publications and data with workflows for Open Access and REF submissions. To achieve this, the repository must be integrated with other Jisc Open Access services such as Sherpa, Jisc Monitor and Publications router, along with those provided by external stakeholders such as ORCID, Crossref, DataCite and OpenAIRE.
This presentation is a case study in evaluating Samvera for this role, and its suitability as a multi-tenanted, sustainable hybrid repository that is both attractive to researchers and universities and aligns with the broader international objectives of the community, the FAIR agenda and open science.
Building a national Data Repository Data ModellingJisc RDM
This document outlines an agenda for a Jisc workshop on data modelling. The workshop will cover StarUML for data modelling, the Jisc Research Data Shared Service conceptual architecture, the canonical data model on GitHub, modelling for interoperability, making data FAIR according to metadata principles, a recent FAIR practices report, content modelling and content models, mapping between the canonical data model and CERIF standard, and an exercise for participants to build their own content model.
Building a national Data Repository System Integration Architecture OverviewJisc RDM
This document discusses publish-subscribe (pub-sub) messaging and how it was implemented for RDSS integration architecture. Pub-sub messaging uses asynchronous and decoupled integration mechanisms like files, databases or APIs to transmit messages. It outlines the lifecycle of a message and why pub-sub messaging provides benefits like operability, architectural compliance, and reliability. Finally, it provides references to the message specification, structure, transport and application behavior used for the pub-sub implementation.
Building a National Data Service Open Repositories 2018Jisc RDM
This document outlines the agenda and introductory information for a workshop on building a national research data service in the UK. The agenda covers introducing the Jisc Research Data Shared Service (RDSS) and demonstrating its data modeling and system integration architecture. Participants will have interactive sessions on workflows, events, and integrations. Speakers will include representatives from Jisc, Figshare, and Digirati discussing their experiences with RDSS. Jisc aims to create a shared, interoperable research data infrastructure for UK universities to better manage research data across institutions.
The Jisc RDMToolkit document discusses the development of a Research Data Management (RDM) toolkit by Jisc and Research Consulting. It provides a sneak peek of the toolkit, which gathers over 100 RDM resources and arranges them using a research data lifecycle model. The toolkit is built on a WordPress template for easy editing and will be maintained by a working group. It will undergo a thorough review after three years.
Stories from the Field: Data are Messy and that's (kind of) okJisc RDM
This document introduces Jude Towers and David Ellis, who are lecturers focused on quantitative methods and computational social science. They discuss how data can be messy, including inconsistencies in concepts and definitions, difficulties in data collection, and the politics of data cleaning. They argue that while data is imperfect, it is still useful for understanding society when the signal is distinguished from the noise. They provide two examples of working with messy real-world data: administrative health records from the NHS and social science replication problems. Their overall goal is to help people critically engage with quantitative data.
'Making the case for a research data shared service' in the Measuring Success and Changing Culture session Presented during the National RDM Strategies session of the Göttingen-CODATA RDM Symposium 2018
Research Data Shared Service update at DPCJisc RDM
The document discusses the Jisc Research Data Shared Service (RDSS) and its role in coordinating the preservation and sharing of research data. RDSS aims to provide core functionality for researchers to deposit, describe, store, publish, and ensure the integrity of their research data. It will also offer advice and best practices for research data management. The service coordinates efforts across universities and involves partnerships with other organizations to develop shared technology solutions for preserving UK research outputs.
The webinar discussed Jisc's proposal for a Research Data Shared Service (RDSS) to address issues with research data management across UK higher education institutions. The RDSS would provide cost-effective solutions for depositing, describing, storing, publishing, and preserving research data through standardized technology and shared expertise. An alpha version was being piloted with 16 institutions and would include repository, preservation, and advisory services. The goal was to increase access to and reuse of research data while reducing costs and risks for institutions.
This document provides an agenda for a lightning talks session taking place on June 27th, 2017. It lists 8 presenters, their institutions, and the titles of their short presentations. Topics will include the role of archivists in research data management, the HYDRA and SAMVERA platforms, open research at the University of Leeds, the THOR project, shared data center services, monitoring institutional compliance with RDM policy, and understanding what constitutes research data. The document also provides contact information for the session organizer.
Title: Monitoring institutional compliance with RDM policy
database that is used by the team to monitor compliance.
Research Data Network
University of Strathclyde
How to Make a Field Mandatory in Odoo 17Celine George
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Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
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DAF Survey Results, research data network
1. 06/09/2016
Research Data Network Meeting
Understanding researchers’ needs
2016 DAF survey findings – Rob Johnson (ResearchConsulting) @rschconsulting
2. The DAFToolkit
The Data Asset Framework (DAF) toolkit allows institutions
to:
»Identify, Locate, and Describe digital assets
»Assess how they are managed
06/09/2016 Jisc Shared Research Data Pilot Meeting
3. Towards a refined DAF survey
Research Consulting was tasked with the development of a refined version of the DAF survey.
06/09/2016 Jisc Shared Research Data Pilot Meeting
2016
Today
Apr May Jun Jul Aug
Analysis of existing DAF surveys
from pilot institutions
1/4/2016
Begin development of a
refined DAF survey
25/4/2016 Pilot institution
feedback
26/5/2016
Final version of the refined DAF survey
28/6/2016
Launch of the DAF survey at 6
pilot institutions
4/7/2016
Analysis of the survey results
and reporting
5/8/2016
5. Profile of respondents by Institution
06/09/2016 Jisc Shared Research Data Pilot Meeting
»The survey gathered a total of 1,185 responses.
37%
25%
21%
10%
5% 1%
The University of Cambridge
St Andrews University
Plymouth University
Lancaster University
CREST
The Royal College of Music (RCM)
7. »Full anonymised dataset is now online:
» Johnson, Rob; Chiarelli, Andrea; Parsons,Tom (2016): Data asset
framework (DAF) survey results 2016. figshare.
»http://dx.doi.org//10.6084/m9.figshare.3796305
»Or just google it!
Jisc Shared Research Data Pilot Meeting06/09/2016
8. Top 10 types of digital research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
0% 10% 20% 30% 40% 50% 60% 70% 80%
Audio files (e.g. interviews, music)
Models/algorithms
Simulation data, models & software code
Observational data
Text files (e.g. .txt)
Digital photographs and other images
Data collected from sensors/instruments (e.g. microscopes)
Data automatically generated from or by computer programs
Spreadsheets
Documents or reports (e.g., Word, PDF, etc.)
Percentage of respondents
9. Research Data Management
06/09/2016 Jisc Shared Research Data Pilot Meeting
40%
37%
23%
No
Yes
Not sure
»Do researchers have a research data management plan?
10. Sensitive research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»What types of sensitive data do researchers hold?
0% 5% 10% 15% 20% 25%
Patient identifiable data
Other types of confidential/restricted data
Commercially sensitive data
Sensitive personal data
Personal data about identifiable living
individuals
Percentage of respondents
11. Sensitive research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
“It would be helpful to clarify the rules for storing
anonymised data on cloud services. My departmental rules
say this is never OK, however this seems to contradict
University rules.”
12. Location of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»Professors vs. PGR Students
0% 20% 40% 60% 80% 100%
University-managed network
storage
Cloud service – Dropbox
Hard disk drive of a computer
owned by the University
Hard disk drive of a privately-
owned computer
External hard drive or
memory stick/USB/Flash drive
Percentage of respondents
PGR Students (N=443)
0% 20% 40% 60% 80% 100%
Hard disk drive of a privately-
owned computer
University-managed network
storage
Cloud service – Dropbox
External hard drive or
memory stick/USB/Flash drive
Hard disk drive of a computer
owned by the University
Percentage of respondents
Professors (N=105)
13. University services to support RDM
“Support is woeful in the university currently, in particular
long-term data archiving is critically required. Most of my
non-current data is rotting on CD's and hard-drives.”
06/09/2016 Jisc Shared Research Data Pilot Meeting
14. Impacts of research data loss
06/09/2016 Jisc Shared Research Data Pilot Meeting
»17% of respondents had lost data, resulting in…
0% 10% 20% 30% 40% 50% 60% 70% 80%
Failure to meet regulatory requirements
Failure to meet funder requirements
Reputational damage
Reduction in quality of research outputs
Delay to publication
Wasted research effort
Percentage of respondents with lost data
15. Preservation of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»How much data has long-term value?
0% 10% 20% 30% 40%
Not sure
More than 1 TB
501GB-1TB
101 GB- 500 GB
51-100 GB
<50 GB
Percentage of respondents
Data owned at present
Data expected to have long term
value
16. Preservation of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»How would respondents expect to preserve their data?
0% 10% 20% 30% 40% 50% 60% 70% 80%
General data repository
Discipline-specific data repository
Other - Please specify:
Institutional data repository
Percentage of respondents
17. Preservation of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
“I currently spend about £1,200 pa on data storage from my
own salary. I have the highest data needs in my School, and
there is no plan in place for storing my data.”
18. Preservation of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»For how long do respondents expect their data to be
preserved?
5-10 years
>10 years
I don't know
1-5 years
0% 5% 10% 15% 20% 25% 30% 35% 40% 45%
Percentage of respondents
5-10 years
>10 years
I don't know
1-5 years
19. Preservation of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»Do you follow guidelines for metadata?
48%
34%
18%
No
Not sure
Yes
20. Sharing research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»68% of respondents either already share data or expect
to do so in the future.What motivates them?
0% 10% 20% 30% 40% 50% 60% 70% 80%
University Research Data Policy
Saves time and effort of sharing results with individuals
My funder requires data sharing
Safeguards research integrity
Increases citation and impact
Verification of research findings
Potential for others to re-use the data
Research is a public good and should be open to all
Percentage of respondents
21. University services to support RDM
06/09/2016 Jisc Shared Research Data Pilot Meeting
»Do researchers use university services to support data
management and sharing?
35%
29%
16%
10%
10% 0%
I don't know what services are
available
I don't currently use these services,
but I expect to in future
I already use these services
I don't expect to use these services
Not sure
There are no services available
22. Training needs on Research Data Management
06/09/2016 Jisc Shared Research Data Pilot Meeting
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Technical support for data processing, e.g. database design, High Performance
Computing (HPC)
Ethics, consent and legal issues with research data
Copyright and intellectual property rights within a data context
Funder requirements for research data management
Guidance on costing data management in grant applications
Publishing research data
Security of data
Collaboration and sharing of data
Developing a research data management plan for a funding application
Long-term storage of your data
Percentage of respondents
23. University services to support RDM
06/09/2016 Jisc Shared Research Data Pilot Meeting
“Please, individualise the support.Workshop are useless,
emails with information are useless, brochures are useless,
posters are useless.”
24. Lessons learned
06/09/2016 Jisc Shared Research Data Pilot Meeting
»Incentives
› voucher for first N respondents +
draw for the rest of the respondents
› higher amount of smaller vouchers
»Dissemination
› direct emails
› weekly staff newsletter
› library blog
› library tweets
› research office/research staff blog
› staff portal
› PGR portal
› link on RDM guidance page/newsletter
› targeted reminders to “missing” departments
26. Focus groups
06/09/2016 Jisc Shared Research Data Pilot Meeting
1. To allow researchers to make Jisc aware of their issues
and concerns
2. To collect use cases for the RDSS
3. To inform and stimulate discussion on important data
and metadata issues
»What are the aims of the focus groups?
27. »Timeline of focus groups
Focus groups
06/09/2016 Jisc Shared Research Data Pilot Meeting
2016
Today
May Jun Jul Aug Sep Oct
Oct/NovTBC
University of Surrey
Lancaster University
St George's Hospital Medical School
University ofYork
University of St Andrews
Cardiff University
28. Focus groups
06/09/2016 Jisc Shared Research Data Pilot Meeting
Business development managers
“I want to create news stories around the data sets, so as to use them as impact case studies.“
»Sample use cases:
Researchers
“I want to be able to encrypt data uploaded to the repository, so sensitive or commercial data can be
safely stored.“
“I want to know who is reusing my data, so that I can collaborate and learn more about their use.“
Reusers of data
“I want to know licence and policy for reuse, so that I am clear what I can do with the data. “
29. Conclusions
06/09/2016 Jisc Shared Research Data Pilot Meeting
Filling a gap
75% of respondents look first
to their institution to preserve
their data
Advocacy
Only 16% of respondents are
currently accessing university
RDM support services
Public datasets
>70% recognise that research
is a public good and should be
publicly released
Metadata
Only 18% of respondents say
they follow established
metadata guidelines
Sensitive data
41% of respondents have
some form of sensitive data
Uptake of RDM
Only 40% of respondents
have a Research Data
Management plan
30. The DAF dataset
»The data used for this analysis is available as a csv
dataset at:
»http://dx.doi.org//10.6084/m9.figshare.3796305
Contact: rob.johnson@researchconsulting.co.uk
@rschconsulting
06/09/2016 Jisc Shared Research Data Pilot Meeting
31. 06/09/2016
Shared Research Data Pilot Meeting
Additional slides
2016 DAF survey findings – Rob Johnson (ResearchConsulting) @rschconsulting
32. Profile of respondents by Role
06/09/2016 Jisc Shared Research Data Pilot Meeting
»The survey respondents had 9 different roles.
38%
18%
16%
9%
9%
4%
4% 1% 1%
Postgraduate student (e.g. MA,
MSc, MEng, PhD, etc.)
Lecturer/Research Fellow
Research Assistant/Post Doc
Senior Lecturer/Senior Research
Fellow
Professor
Assistant/Associate Professor
Other
Administrative/Professional
Technician
33. Volume of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»How much data do researchers hold?
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Not sure
More than 1 TB
501GB-1TB
101 GB- 500 GB
51-100 GB
<50 GB
Professors (N=105)
PGR students (N=442)
All respondents
34. Location of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»Where is research data stored (Top 5)?
0% 10% 20% 30% 40% 50% 60% 70% 80%
Cloud service – Dropbox
University-managed network storage
Hard disk drive of a privately-owned computer
External hard drive or memory stick/USB/Flash
drive
Hard disk drive of a computer owned by the
University
Percentage of respondents
All respondents
35. Loss of research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»Have researchers ever lost data?
83%
17%
No
Yes
Top 3 causes for loss of data
1. Hardware failure
2. Human error
3. Equipment stolen
36. Sharing research data
06/09/2016 Jisc Shared Research Data Pilot Meeting
»How do you share data with other researchers?
0% 10% 20% 30% 40% 50% 60% 70% 80%
By upload to a web site or FTP server accessible
to that researcher
Institutional file-sharing service
Share it on an academic social network (e.g.
Academia, ResearchGate, Mendeley)
Using portable storage such as CDs, DVDs,
memory sticks etc.
Using a cloud storage service e.g. Dropbox,
Google Drive etc.
By emailing data files
Percentage of respondents
Editor's Notes
DAF surveys
Pilot focus groups
The Data Asset Framework has been developed with JISC funding in a project led by HATII at the University of Glasgow in conjunction with the Digital Curation Centre.
Response rates – Plymouth 12.4%
Cambridge – 11%
Lancaster – 10.3%
St Andrews – 15%
RCM – 33%
Mixture of career stages – 38% Postgrad students, but good mix of postdocs, lecturers, profs
SOPs, genomic data, videos etc
TOP REASONS FOR YES (N=100)
72% Good research practice
53% Required by project funder
TOP REASONS FOR NO (N=171)
47% Not required/appropriate to field of research
45% Not required by project funder
32% Lack of knowledge or experience on creating data management plan
25% Unaware of any tools or guidance that can help create data management plan
59% of 1167 respondents said none of the above.
Charts represent locations where at least SOME data is stored.
All the same across career
Qualitative analysis from FREE TEXT responses:
Hardware failure 43%
Human error 33%
Stolen hardware (e.g. laptop) 6%
Do researchers expect to move their data when a project ends?
44% Yes
39% No
15% Unsure
2% Would delete
Most mentioned repositories:
NCBI Sequence Read Archive (SRA)
GenBank
EMBL Nucleotide Sequence Database (ENA)
Open Science Framework
GitHub
Dryad Digital Repository
OTHER – PLEASE SPECIFY (most common responses)
external hard drive
cloud storage
lab drive
university backup
own backup solution
Period over which the data was collected (All respondents):
32% 1-3 years
26% Within the last 12 months
20% 3-5 years
11% 5-10 years
MORE THAN 1 TB: Most are between 1TB and 10 TB. There are also peaks of 100 TB, 300 TB, 500 TB.
Chart represents locations where at least SOME data is stored.
Use of cloud services (Dropbox, Box, Google Drive, OneDrive)
63% Personal account
22% Combination of personal and institutional cloud services
13% Institutional account
Qualitative analysis from FREE TEXT responses:
Hardware failure 43%
Human error 33%
Stolen hardware (e.g. laptop) 6%
These are the approaches with at least 15% of responses.