This document provides an overview and update on Jisc's Research Data Shared Service. It discusses the vision, goals, and key requirements of creating a shared research data infrastructure. It also provides details on the supplier framework, consultant support, pilot engagements, and strategic view of the service. The service aims to make research data management easier for researchers and help institutions meet requirements in a cost-effective, interoperable manner.
Jisc Research Data Discovery Service ProjectJisc RDM
This document summarizes the UK Research Data Discovery Service (UKRDDS) project run by Jisc from 2013-2016. The project had two phases: an initial pilot to evaluate options for a research data registry and a second phase to build a test service based on the CKAN platform. The project engaged universities and data centers to pilot the service and provide feedback. It focused on developing a core metadata schema and getting stakeholder input to define requirements and priorities through an advisory group structure. The timeline outlines milestones like prototyping the service, implementing pilots, and developing plans to transition the service to ongoing operations.
The document outlines the mission and aims of establishing a business case and costing process for research data management (RDM) in a more efficient and effective manner. It discusses commissioning work from Research Consulting to deliver a high-level business case for RDM and from Cambridge Econometrics to analyze methods to quantify the economic benefits of RDM. The next steps include publishing the commissioned reports and resources in May 2016 to provide RDM costing schemas, budgets, templates, and awareness materials.
The document outlines Research Data Spring, a program that supports partnerships to improve the research data lifecycle. It aims to find new tools and solutions for researchers' data management and use. The program has funded several phases of projects, with Phase II including 11 projects and Phase III focusing on 7 continued projects. Upcoming work includes developing the projects into robust solutions and services and showcasing results in autumn 2016.
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.
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.
Rachel Bruce, deputy chief innovation officer at Jisc talking about the feedback from the research data shared service pilots on DMP. Research Data Network, York
Jisc Research Data Discovery Service ProjectJisc RDM
This document summarizes the UK Research Data Discovery Service (UKRDDS) project run by Jisc from 2013-2016. The project had two phases: an initial pilot to evaluate options for a research data registry and a second phase to build a test service based on the CKAN platform. The project engaged universities and data centers to pilot the service and provide feedback. It focused on developing a core metadata schema and getting stakeholder input to define requirements and priorities through an advisory group structure. The timeline outlines milestones like prototyping the service, implementing pilots, and developing plans to transition the service to ongoing operations.
The document outlines the mission and aims of establishing a business case and costing process for research data management (RDM) in a more efficient and effective manner. It discusses commissioning work from Research Consulting to deliver a high-level business case for RDM and from Cambridge Econometrics to analyze methods to quantify the economic benefits of RDM. The next steps include publishing the commissioned reports and resources in May 2016 to provide RDM costing schemas, budgets, templates, and awareness materials.
The document outlines Research Data Spring, a program that supports partnerships to improve the research data lifecycle. It aims to find new tools and solutions for researchers' data management and use. The program has funded several phases of projects, with Phase II including 11 projects and Phase III focusing on 7 continued projects. Upcoming work includes developing the projects into robust solutions and services and showcasing results in autumn 2016.
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.
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.
Rachel Bruce, deputy chief innovation officer at Jisc talking about the feedback from the research data shared service pilots on DMP. Research Data Network, York
This document describes Spotlight Data, a company that uses text mining, machine learning, and data visualization to help with research data management. It introduces key members of Spotlight Data's team and describes some of their current projects, including work with the UK government and Durham University applying text mining and machine learning to large datasets. It also provides an overview of Spotlight Data's Nanowire system for ingesting, processing, and analyzing both structured and unstructured data at scale using a microservices architecture.
1. Metrics are being developed to track downloads and reuse of research data to understand impact and reassure researchers. A new service called IRUS for Data will provide metrics for data repositories across different platforms.
2. There is debate around what data citations mean and how they should be used and understood. Projects are working to develop best practices and encourage responsible use of citation metrics for data.
3. Ensuring research data sharing is recognized in existing systems like journal policies is challenging due to lack of standards. Initiatives are working with publishers and repositories to develop guidance and implement principles for data citation.
This document summarizes a webinar for the Research Data Discovery Service Phase 3 project. The webinar agenda included project updates, a review of the latest system status including harvesting and requirements, a discussion of metadata, an overview of next steps for Phase 3, and time for questions. Participants were encouraged to provide feedback and help test the beta version of the system as it is further developed into a production research data discovery service.
Research at risk: developing a shared research data management service for UK...Jisc RDM
Rachel Bruce presented on Jisc's plans to develop a shared research data management service for UK universities. The service aims to help universities meet research funder requirements for data management and sharing in a cost effective way. It will provide services such as storage, metadata, and tools to help with data discovery and reuse. Jisc conducted surveys that found universities wanted services for preservation, automation, integration, and reducing their IT burden. The shared service is being developed through 2017 based on requirements identified.
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.
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.
National data services lightening talk at the RDAJisc RDM
Our slides for the lightening talk at the annual RDA in Tokyo. All about the national shared services to support research data infrastructure. March 2016.
Northumbria University is working to implement a robust research data management (RDM) solution. It has engaged in several activities to assess current RDM practices and infrastructure needs, including interviews with grant holders, a survey of researchers, and workshops with the Digital Curation Centre. Through these workshops, the university used the RISE model to evaluate its capabilities for data ingest, access, preservation, and more across several potential repository platforms. This helped provide evidence to secure budget and staffing to pilot and roll out a new RDM system starting in 2018. The university aims to go to procurement in September 2017 after finalizing business requirements and an options appraisal.
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.
The document provides an overview of the UK research data discovery service, which aggregates research data from universities and national data centers to enable discovery of UK research data. It describes the pilot and development of the service, including participating organizations, requirements gathering, and next steps to transition the beta service into a production service. The demonstration shows the search capabilities of the beta discovery service platform.
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 Research Data Discovery Service Project aims to build a UK research data discovery service that enables discovery of UK research data and meets requirements. Phase 2 will build on previous pilot work to lay foundations for the future delivery of the service, including developing use cases, agreeing metadata standards, and creating a business case. The project team is working with participating universities and data centers to ingest metadata and gather feedback to develop an effective solution.
This document describes Spotlight Data, a company that uses text mining, machine learning, and data visualization to help with research data management. It introduces key members of Spotlight Data's team and describes some of their current projects, including work with the UK government and Durham University applying text mining and machine learning to large datasets. It also provides an overview of Spotlight Data's Nanowire system for ingesting, processing, and analyzing both structured and unstructured data at scale using a microservices architecture.
1. Metrics are being developed to track downloads and reuse of research data to understand impact and reassure researchers. A new service called IRUS for Data will provide metrics for data repositories across different platforms.
2. There is debate around what data citations mean and how they should be used and understood. Projects are working to develop best practices and encourage responsible use of citation metrics for data.
3. Ensuring research data sharing is recognized in existing systems like journal policies is challenging due to lack of standards. Initiatives are working with publishers and repositories to develop guidance and implement principles for data citation.
This document summarizes a webinar for the Research Data Discovery Service Phase 3 project. The webinar agenda included project updates, a review of the latest system status including harvesting and requirements, a discussion of metadata, an overview of next steps for Phase 3, and time for questions. Participants were encouraged to provide feedback and help test the beta version of the system as it is further developed into a production research data discovery service.
Research at risk: developing a shared research data management service for UK...Jisc RDM
Rachel Bruce presented on Jisc's plans to develop a shared research data management service for UK universities. The service aims to help universities meet research funder requirements for data management and sharing in a cost effective way. It will provide services such as storage, metadata, and tools to help with data discovery and reuse. Jisc conducted surveys that found universities wanted services for preservation, automation, integration, and reducing their IT burden. The shared service is being developed through 2017 based on requirements identified.
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.
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.
National data services lightening talk at the RDAJisc RDM
Our slides for the lightening talk at the annual RDA in Tokyo. All about the national shared services to support research data infrastructure. March 2016.
Northumbria University is working to implement a robust research data management (RDM) solution. It has engaged in several activities to assess current RDM practices and infrastructure needs, including interviews with grant holders, a survey of researchers, and workshops with the Digital Curation Centre. Through these workshops, the university used the RISE model to evaluate its capabilities for data ingest, access, preservation, and more across several potential repository platforms. This helped provide evidence to secure budget and staffing to pilot and roll out a new RDM system starting in 2018. The university aims to go to procurement in September 2017 after finalizing business requirements and an options appraisal.
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.
The document provides an overview of the UK research data discovery service, which aggregates research data from universities and national data centers to enable discovery of UK research data. It describes the pilot and development of the service, including participating organizations, requirements gathering, and next steps to transition the beta service into a production service. The demonstration shows the search capabilities of the beta discovery service platform.
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 Research Data Discovery Service Project aims to build a UK research data discovery service that enables discovery of UK research data and meets requirements. Phase 2 will build on previous pilot work to lay foundations for the future delivery of the service, including developing use cases, agreeing metadata standards, and creating a business case. The project team is working with participating universities and data centers to ingest metadata and gather feedback to develop an effective solution.
Davor Meersman gave a presentation about his current research and a COST International Network. Regarding his research, he completed a PhD on domain-driven innovation using action research and design science across several domains. He is now a researcher at iMinds iLab.o living lab, focusing on smart cities, eHealth, future internet, and other areas. The COST network aims to establish integrated service perspectives across software, processes, hardware, humans and platforms to support user-centric service innovation and education in service science across Europe. Contact information was provided at the end.
The document summarizes presentations from three perspectives on progress towards open and interoperable research data service workflows:
1) Angus Whyte of the Digital Curation Centre discussed new DCC guidance and design principles for integrating research data service workflows.
2) Rory Macneil of Research Space discussed integrating their ELN with University of Edinburgh's DataShare and Harvard's Dataverse repositories using open standards.
3) Stuart Lewis of University of Edinburgh discussed their DataVault prototype for packaging data to be archived from a Jisc Research Data Spring project. The case studies illustrate challenges and opportunities for improving integration between active data management and long-term preservation services.
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.
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.
A Jisc perspective of digital notebooks including a summary of work on e-Lab notebooks, VREs, the next generation research environment and the research data shared service. How might ELNs be incorporated into a future open science shared service? Presented at "Digital Notebooks - how to provide solutions for researchers?" workshop in TU Delft (16 March 2018)
Implementing Open Access: Effective Management of Your Research DataMartin Hamilton
This document discusses research data management and support available from Jisc and the Digital Curation Centre (DCC). It provides background on policy drivers for research data management, outlines support offered by the DCC including capability studies, data management planning tools, and training. It also summarizes results from a 2014 survey of UK higher education institutions which found most progress in policy development and plans, but challenges around staffing, funding, and engagement of researchers. The document concludes with feedback on future priorities such as compelling services, engaging researchers, and shared infrastructure solutions.
The document discusses competency frameworks for roles in research data infrastructure, including researchers, statisticians, data scientists, librarians, data curators, and engineers. It outlines the scope of skills and knowledge required in science/research, curation/stewardship, and engineering/infrastructure. It also discusses considerations around research data infrastructure communities, open science, identity and identifiers, and interoperability. Key challenges identified include the need for multi-disciplinary skills and defining career pathways to attract talent. Solutions proposed include developing cloud and open source frameworks, education, and establishing trust to address human resource shortfalls.
Multi-faceted Classification of Big Data Use Cases and Proposed Architecture ...Geoffrey Fox
Keynote at Sixth International Workshop on Cloud Data Management CloudDB 2014 Chicago March 31 2014.
Abstract: We introduce the NIST collection of 51 use cases and describe their scope over industry, government and research areas. We look at their structure from several points of view or facets covering problem architecture, analytics kernels, micro-system usage such as flops/bytes, application class (GIS, expectation maximization) and very importantly data source.
We then propose that in many cases it is wise to combine the well known commodity best practice (often Apache) Big Data Stack (with ~120 software subsystems) with high performance computing technologies.
We describe this and give early results based on clustering running with different paradigms.
We identify key layers where HPC Apache integration is particularly important: File systems, Cluster resource management, File and object data management, Inter process and thread communication, Analytics libraries, Workflow and Monitoring.
See
[1] A Tale of Two Data-Intensive Paradigms: Applications, Abstractions, and Architectures, Shantenu Jha, Judy Qiu, Andre Luckow, Pradeep Mantha and Geoffrey Fox, accepted in IEEE BigData 2014, available at: http://arxiv.org/abs/1403.1528
[2] High Performance High Functionality Big Data Software Stack, G Fox, J Qiu and S Jha, in Big Data and Extreme-scale Computing (BDEC), 2014. Fukuoka, Japan. http://grids.ucs.indiana.edu/ptliupages/publications/HPCandApacheBigDataFinal.pdf
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.
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
PT-CRIS aims to ensure the creation and sustained development of an national integrated information ecosystem to support scientific activity developed in Portugal according to the best international standards and practices
Rich feeds for rescue an integration storybdemchak
This document provides an overview of policies for security and data sharing in the Physical Activity Location Measurement System (PALMS). PALMS aims to support data collection and analysis for exposure biology studies while being extensible, flexible, and HIPAA compliant. It discusses PALMS' logical architecture and policy composition, as well as the relationship between PALMS and caBIG (cancer Biomedical Informatics Grid) for security, identity management, and data sharing. Key components of PALMS include policy-driven access control, secure and customized studies, and collaboration.
Rich feeds for rescue, palms cyberinfrastructure integration storiesbdemchak
This document provides an overview of policies for security and data sharing in the Physical Activity Location Measurement System (PALMS). PALMS aims to support data collection and analysis for exposure biology studies while maintaining security, extensibility, and HIPAA compliance. The document outlines PALMS objectives, organization, logical architecture, and how policy will be composed and executed. It also discusses how PALMS could integrate with existing frameworks like caBIG and GAARDS to leverage security standards and community resources.
Overview of policies for security and data sharingbdemchak
This document provides an overview of policies for security and data sharing in the Physical Activity Location Measurement System (PALMS). PALMS aims to support data collection and analysis for exposure biology studies while being extensible, flexible, and HIPAA compliant. It discusses PALMS' logical architecture and policy composition, as well as the relationship between PALMS and the cancer Biomedical Informatics Grid (caBIG) framework. Key topics covered include identity management, access control policies, and integrating PALMS with caBIG services and tools for enforcing security policies in enterprise grids.
A benchmarking tool developed by the DCC to assess research data infrastructure. The presentation also outlines alternative versions developed by the University of the West of England and an EPSRC-compliance version
The document provides an overview of the development of the NIH Data Commons. It discusses factors driving the need for a data commons, including large amounts of data being generated and increased support for data sharing. It outlines the goals of making data findable, accessible, interoperable and reusable. Several pilots are exploring the feasibility of the commons framework, including placing large datasets in the cloud and developing indexing methods. Considerations in fully realizing the commons are also discussed, such as standards, discoverability, policies and incentives.
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 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.
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
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.
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.
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
This document discusses how Hydra, an open source repository system, is now called Samvera. Samvera means "togetherness" in Icelandic and reinforces the community developing repository solutions by working together based on common components and solutions. While the underlying names like Hyrax, Hyku and Avalon remain the same, Hydra is now known as Samvera to emphasize collaboration within the community developing repository solutions.
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
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
3. Shared Service Vision
» Researchers shouldn’t need to think (too much!) about Research
Data Management
» "Visible data, invisible infrastructure"
• Provide researchers intuitive, easy functionality to publish, archive and
preserve their research outputs.
• Provide interoperable systems to allow researchers and institutions to
fulfil and go beyond policy requirements and adhere to best practice
throughout the RDM lifecycle.
3
4. Shared Service Goals
» RDM Policy compliance
» Increased sector efficiencies: procurement, data re-use,
interoperability opportunities
» Improving the integrity of research
» Addressing Market Gaps: Integrated RDM system, PreservationGap,
Usability
» Accelerating Research Data Management in institutions
» Supporting institutions meet Open Access/REF
4
5. A **key** requirement
CNI Fall Meeting, December 14th -15th 2015 - Jisc Shared Research Data Management Service
7. Pilot’s MVP’s
» Everything!
» “Easy to use and cost effective archiving, ingest, preservation,
repository, reporting and discovery supported that can handle
sensitive data”
» “Robust data storage that has growth ability for active and archive
data”
» “Standard metadata profile - international for interoperability”
» “Integration with all main CRIS systems and PURE”
» “Meets REF and funder deposit requirements (supports deposit of REF
data output types)”
» …..........
7
8. What we need
» Operational Requirements laid out for systems that integrate with each other
8
10. RD Shared Service Framework Lots
» Lot 1 - Research Data Repositories (4)
» Lot 2- Repository Interfaces (6)
» Lot 3 - Research Data Exchange Interface (3)
» Lot 4 - Research Information and Administration Systems Integrations
(1)
» Lot 5 -Research Data Preservation Platforms (2)
» Lot 6 - Research Data Preservation tools development (2)
» Lot 7 - Research Data Reporting (2)
» Lot 8 - User Experience enhancements (4)
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11. RD Shared Service Framework Platforms
» Lot 1 - Research Data Repositories (4)
– Discoverygarden – Islandora (open source, based on Fedora)
– Figshare (proprietary, hosted)
– Haplo (based on RIM system used atWestminster, open source)
– Sero - Hydra (open source, based on Fedora)
» Lot 5 -Research Data Preservation Platforms (2)
– Arkivum – Archivematica (open source preservation platform)
– Preservica – (propreitary, hosted or licenced)
» Lot 7 - Research Data Reporting (2)
– Connexica – CXAIR (proprietary, hosted)
– Sero – Edges (Also used by Jisc Monitor)
11
12. RD Shared Service Framework Development
Lot 2 (Max of 6) Lot 3 (Max of 3) Lot 4 (Max of 10) Lot 6 (Max of 5) Lot 8 (Max of 4)
Integrations Data Exchange CRIS Integration PresToolsDev UX
Sero Uni of London CC Symplectic Arkivum Edingburgh Uni
Ocasta Edinburgh Uni Edingburgh Uni magneticNorth
Uni of London CC Arkivum Ocasta
Edingburgh Uni Arkivum
Discovery Garden
Ken Chad
» Suppliers to be contracted using mini competitions
» Pilots need to provide requirements for call offs from platform lots
» Supplier workshop and joint supplier-pilot workshop are to be arranged
when Framework is confirmed.
» “University of Jisc” set up to test integrations.
14. Consultancy Support
Consultancy Description
RDM Costing (Cambridge
Econometrics)
To investigate current costing practices, tools, models and potential
future developments in the field of RDM costing—and this work is
being applied to developing the business model for the research data
shared service pilot
Data Asset Framework
(Research Consulting)
To provide the consultation phase for stakeholders in the project,
not focused on the final technology solution, for example an audit of
datasets, legal and compliance framework, financial and strategic
commitment.
Technical Architect
(Digirati)
To provide expert technical advice to the project on the technical
architecture of the service, assessment of institutional technical
capability and to assist in gatheringdetailed requirements from
institutions and researchers
Metadata and
Interoperability (CLAX)
An examination of metadata specifications and provide advice on
identifier systems and interoperability
Project Management (LM) To provide project management support and coordinate contract
negotiations, facilitate collaboration between suppliers and HEI’s and
monitor overall service development. This function will also gather
evidence to feed into the business model for the next stage
Market Research (TBC) To gather information on the demand for a service and to test
proposed models for the business case to proceed to aproduction
service.
Preservation Audit (TBC) To provide the requirements and priorities for RDM preservation
tools development
15. Data Asset Framework Outputs
» Reporting on researcher data needs and RDM support staff needs
» Analyse existing DAF's and associated materials (interviews etc.)
» Provide institutionally branded DAF survey for institutions with no current
DAF's
» Provide matrix comparing existing DAF's to survey to highlight any
information gaps
» Site visits with researcher focus groups and support staff (with
some institutions that have already completed DAF's and prioritising
those with information gaps)
» Survey/Focus group Analysis for those with existing DAF’s - interim
findings at Sept RDN
» Site visits/Focus Groups with institutions using Jisc Survey
15
16. Technical Architect Outputs
» Impact Mapping Results
» Conceptual architecture and initial integration strategy and
development pathway for the service as a whole, based on supplier
and pilot system analysis.
» Methodology for Jisc/Architect to monitor supplier progress against
contracts and the development pathway
» Specifications for development of new interfaces for systems
identified through discussions with pilots institutions and suppliers.
» Visits to pilot institutions and reporting
» Plan forTechnicalArchitect/TechnicalAdvisor work for July 2016 –April
2018
16
17. Metadata and Interoperability Outputs
» Define a schema for the service using the UK Research Data Discovery profile as a base
» Test pilot use cases and requirements against the proposed profile for the service
» Comparison of existing pilot metadata with proposed schema
» What is the minimum metadata to meet the use cases (Jisc base? DataCite? plus admin)?
» Where are the opportunities for auto-generation of metadata in the profile
» Opportunities presented by use of Identifiers. Current use, plans and approaches by pilot institutions
and define shared service approach to identifiers
» Investigate incorporation of additional metadata sources e.g. equipment.data,Artivity (provenance)
etc.
» Ensure text metadata meets open access/Ref requirements.
17
18. Pilots
18
Institution Name
Cardiff University
CREST - Consortium for Research Excellence, Support andTraining (Harper Adams, St
Mary’s -Twickenham, UCA &Winchester)
Imperial College of Science,Technology and Medicine
Middlesex University
Plymouth University
Royal College of Music
St George's Hospital Medical School
University of Cambridge
University of Lancaster
University of Lincoln
University of StAndrews
University of Surrey
University ofYork
» Pilot institutions selected to create a balanced portfolio of types of
institution, specialisms and research systems already in place
19. Pilot Engagement Activities
19
» Quarterly user group meetings and regular contact outside
» Technical architecture
– Visits, interviews, assessment and reporting (current activity)
» DataAsset Framework
– Desk research, surveys, focus groups and interviews with researchers and RDM support staff
(Started March 2016)
» Metadata and interoperability
– Focus groups and interviews with researchers and RDM support staff (starting May 2016)
» RDMCosting
– Workshops and interviews with RDM support staff (workshop 6th May)
» Supplier selection
– Interviews, Pilots/Suppliers workshop with key contacts (TBC) also informed by technical
architecture work
» Development activity
– Working with suppliers to develop and test systems with researchers.
20. Moving to a Production Service
20
» Need market research to assess demand for shared services and to
test proposed models and pricing
» Need accurate and transparent costing information from the
service. Software costs, hosting costs, storage costs
» Need to investigate a financial model. Is all the service paid for on
top of the subscription? Or is some of it within the subscription
» Jisc Business case process: POG, preliminary, full business case etc.
» Currently operating a “Pick and Mix” model of multiple systems,
however moving to Consensus and simplified offer should be a long
term goal
22. Engagement with wider community
22
» Research DataToolkit
–Information on how to implement an RDM service and also how
you use RDSS
–We need to identify where we are creating information in the pilot
and within R@R to synthesise intoToolkit
–We need to be organised with our project outputs and useful
information
23. StrategicView
23
» Links with OA infrastructure:
– Text deposit and publication and preservation is a hgh priority for some
of the pilots,
– also metadata push/notifications/alerts between OA and RDM
infrastructures to allow for analytics
– Are there parallels in processes, staff and platforms for Jisc services for
different content types e.g. Data and publications and should we look to
consolidate?
» Links with equipment.data, KONFER
» Other Jisc services? E.g. potential for preservation to meet records
management needs
» Increased links with disciplinary practice, infrastructure and funders
» Migration from fragmented repository infrastructure into shared services.
24. Jisc Shared Service (Core)Team
24
»Rachel Bruce – Deputy Chief Innovation Officer
»Catherine Grout – Head of Change – Research
»John Kaye – Senior Co-Design Manager
»Paul Stokes– Senior Co-Design Manager
»Daniela Duca - Senior Co-Design Manager
»Nikki Browne – Project Manager
Jisc Digital Futures – Research
The big GAP – so while there are solutions like Arkivum there is a gap in terms of curating for preservation – tools that allow file format identification, metadata and the creation of archival information packages – data integrity and even emulation …people haven’t got to deal with this yet , perhaps also the what to keep question.
Interoperability with systems can provide opportunities for efficiencies and ease of use for researchers
A range of minimum viable products, which we are currently firming up with our technical architect
Plus reporting
Underlined are platform lots, which are existing products that can be installed straight after contracting, the other lots are development lots to provide interoperability, usability and suitability for RDM
Define process to select platforms
Project will be makiing links berween the rest of the Research at Risk portfolio
A range of consultancy support is underway or planned
Parallels in processes, staff and platfoms different content types