The document discusses open science and the role of identifiers like DOIs. It describes how research data sharing has become core to open science due to the Internet and digital archives. Researchers now publish their data in addition to papers. Well-managed metadata standards and identifier systems help integrate data across its life cycle from creation to archiving. The DOI system provides persistent links for digital objects and is increasingly used for research data through registration agencies like DataCite.
The document discusses Japan Link Center's (JaLC) experiment to register DOIs for research data. The experiment aims to establish workflows for registering DOIs for research data using JaLC's system. It involves 9 projects with 14 organizations testing DOI registration for research data. The document outlines several issues in registering DOIs for data, including operations flow, persistent access, granularity, dynamics of data, and quantity of data. It also provides examples of how projects can involve multiple institutions and how data lifecycles differ from literature.
The document summarizes the experimental project of registering Digital Object Identifiers (DOIs) for research data at the Japan Link Center (JaLC). The project aims to establish workflows for registering DOIs for research data and test the registration of data DOIs. It involves 9 research projects and 14 organizations registering and integrating DOIs for their data through the JaLC system. The project addresses several issues in registering DOIs for dynamic research data, such as data lifecycles, granularity, persistence, and handling changes over time.
Workshop about research data archiving and open access publishing at the Rese...Dag Endresen
The Research Council of Norway (RCN) organizes a workshop on 1st November 2016 to collect experiences on research data archiving and open access data publishing. The Norwegian GBIF-node will present the GBIF framework including dataset DOIs and download DOIs.
See also:
GBIF.no (2016), http://www.gbif.no/news/2016/data-archiving-ncr.html
GBIF GB21 (2014), http://www.gbif.org/newsroom/news/gb21-science-symposium
GBIF GB21 Slides, http://www.gbif.org/resource/81918
Vimeo video (2014), https://vimeo.com/107148220#t=6m28s
OpenData Public Research
Open Access Events: The Case for Open Data, Why you should Care
Map & Data Library - 5th Floor Robarts Library, University of Toronto
Thursday, Oct. 25 from 10:00-12:00
Organized by Data and Map Librarians, Marcel Fortin and Berenica Vejvoda
This document summarizes Rob Grim's presentation on e-Science, research data, and the role of libraries. It discusses the Open Data Foundation's work in promoting metadata standards like DDI and SDMX. It also outlines the research data lifecycle and how metadata management can help libraries support research through services like data registration, archiving, discovery and access. Finally, it provides examples of how Tilburg University library supports research data through services aligned with data availability, discovery, access and delivery.
The document introduces The Open Data Institute (ODI) and its mission to make open data available and useful. In its first 10 weeks, the ODI has [1] received £10 million in UK public funding and $750k in matching funds, [2] launched programs that could save the NHS £200 million per year and train world leaders, and [3] incubated five startups and convened experts in health, data analytics, and communications to analyze data and identify opportunities. The ODI aims to unleash the economic and social benefits of open data through startups, research, and collaboration across sectors.
The document discusses open science and the role of identifiers like DOIs. It describes how research data sharing has become core to open science due to the Internet and digital archives. Researchers now publish their data in addition to papers. Well-managed metadata standards and identifier systems help integrate data across its life cycle from creation to archiving. The DOI system provides persistent links for digital objects and is increasingly used for research data through registration agencies like DataCite.
The document discusses Japan Link Center's (JaLC) experiment to register DOIs for research data. The experiment aims to establish workflows for registering DOIs for research data using JaLC's system. It involves 9 projects with 14 organizations testing DOI registration for research data. The document outlines several issues in registering DOIs for data, including operations flow, persistent access, granularity, dynamics of data, and quantity of data. It also provides examples of how projects can involve multiple institutions and how data lifecycles differ from literature.
The document summarizes the experimental project of registering Digital Object Identifiers (DOIs) for research data at the Japan Link Center (JaLC). The project aims to establish workflows for registering DOIs for research data and test the registration of data DOIs. It involves 9 research projects and 14 organizations registering and integrating DOIs for their data through the JaLC system. The project addresses several issues in registering DOIs for dynamic research data, such as data lifecycles, granularity, persistence, and handling changes over time.
Workshop about research data archiving and open access publishing at the Rese...Dag Endresen
The Research Council of Norway (RCN) organizes a workshop on 1st November 2016 to collect experiences on research data archiving and open access data publishing. The Norwegian GBIF-node will present the GBIF framework including dataset DOIs and download DOIs.
See also:
GBIF.no (2016), http://www.gbif.no/news/2016/data-archiving-ncr.html
GBIF GB21 (2014), http://www.gbif.org/newsroom/news/gb21-science-symposium
GBIF GB21 Slides, http://www.gbif.org/resource/81918
Vimeo video (2014), https://vimeo.com/107148220#t=6m28s
OpenData Public Research
Open Access Events: The Case for Open Data, Why you should Care
Map & Data Library - 5th Floor Robarts Library, University of Toronto
Thursday, Oct. 25 from 10:00-12:00
Organized by Data and Map Librarians, Marcel Fortin and Berenica Vejvoda
This document summarizes Rob Grim's presentation on e-Science, research data, and the role of libraries. It discusses the Open Data Foundation's work in promoting metadata standards like DDI and SDMX. It also outlines the research data lifecycle and how metadata management can help libraries support research through services like data registration, archiving, discovery and access. Finally, it provides examples of how Tilburg University library supports research data through services aligned with data availability, discovery, access and delivery.
The document introduces The Open Data Institute (ODI) and its mission to make open data available and useful. In its first 10 weeks, the ODI has [1] received £10 million in UK public funding and $750k in matching funds, [2] launched programs that could save the NHS £200 million per year and train world leaders, and [3] incubated five startups and convened experts in health, data analytics, and communications to analyze data and identify opportunities. The ODI aims to unleash the economic and social benefits of open data through startups, research, and collaboration across sectors.
The document discusses how linked open data and semantic web technologies can be applied to educational data and resources on the web. It provides examples of projects that aim to expose, interlink, and enrich educational datasets using these technologies. The goal is to improve data sharing and interoperability, facilitate reuse of open educational resources, and leverage linked data as a knowledge base to support learning and education.
WWW2013 Tutorial: Linked Data & EducationStefan Dietze
Linked data provides opportunities for sharing educational data on the web in a standardized way. It allows for the integration of heterogeneous educational resources and datasets from different platforms. This can enable new applications like cross-platform recommender systems and exploratory search. However, there are also challenges to address like annotation overhead, performance, and scalability when dealing with large amounts of distributed data.
DataCite: the Perfect Complement to CrossRefCrossref
DataCite was created to address the lack of effective ways to link datasets to articles and identify datasets. It assigns digital object identifiers (DOIs) to datasets to allow them to be cited similarly to scholarly articles. Many research institutions and libraries around the world are members of DataCite, including organizations in Europe, North America, and Asia. DataCite helps establish datasets as legitimate contributions to the scientific record that can be identified and cited.
Presented by Tony Mathys at a Current Issues and Applications of the Geospatial Technologies Lecture, Department of Geography and Environment, Aberdeen University, 24 February 2012
The Research Data Alliance (RDA) is an international organization with over 10,000 members from 144 countries working to build the social and technical infrastructure to enable open sharing of data. Its vision is for researchers to openly share data across technologies, disciplines, and countries to address societal challenges. RDA has over 100 groups working on data interoperability issues and has produced 37 flagship outputs, including technical specifications, with over 100 adoption cases in various organizations and disciplines.
The Digital Curation Centre (DCC) helps research institutions and funders develop data management plans and policies. The DCC created an online tool called DMP Online that allows researchers to create customized data management plans that meet funder requirements. DMP Online provides guidance and templates on best practices. The DCC also analyzes funder policies and develops training and resources to help institutions build data management strategies and capabilities.
Being FAIR: FAIR data and model management SSBSS 2017 Summer SchoolCarole Goble
Lecture 1:
Being FAIR: FAIR data and model management
In recent years we have seen a change in expectations for the management of all the outcomes of research – that is the “assets” of data, models, codes, SOPs, workflows. The “FAIR” (Findable, Accessible, Interoperable, Reusable) Guiding Principles for scientific data management and stewardship [1] have proved to be an effective rallying-cry. Funding agencies expect data (and increasingly software) management retention and access plans. Journals are raising their expectations of the availability of data and codes for pre- and post- publication. The multi-component, multi-disciplinary nature of Systems and Synthetic Biology demands the interlinking and exchange of assets and the systematic recording of metadata for their interpretation.
Our FAIRDOM project (http://www.fair-dom.org) supports Systems Biology research projects with their research data, methods and model management, with an emphasis on standards smuggled in by stealth and sensitivity to asset sharing and credit anxiety. The FAIRDOM Platform has been installed by over 30 labs or projects. Our public, centrally hosted Asset Commons, the FAIRDOMHub.org, supports the outcomes of 50+ projects.
Now established as a grassroots association, FAIRDOM has over 8 years of experience of practical asset sharing and data infrastructure at the researcher coal-face ranging across European programmes (SysMO and ERASysAPP ERANets), national initiatives (Germany's de.NBI and Systems Medicine of the Liver; Norway's Digital Life) and European Research Infrastructures (ISBE) as well as in PI's labs and Centres such as the SynBioChem Centre at Manchester.
In this talk I will show explore how FAIRDOM has been designed to support Systems Biology projects and show examples of its configuration and use. I will also explore the technical and social challenges we face.
I will also refer to European efforts to support public archives for the life sciences. ELIXIR (http:// http://www.elixir-europe.org/) the European Research Infrastructure of 21 national nodes and a hub funded by national agreements to coordinate and sustain key data repositories and archives for the Life Science community, improve access to them and related tools, support training and create a platform for dataset interoperability. As the Head of the ELIXIR-UK Node and co-lead of the ELIXIR Interoperability Platform I will show how this work relates to your projects.
[1] Wilkinson et al, The FAIR Guiding Principles for scientific data management and stewardship Scientific Data 3, doi:10.1038/sdata.2016.18
Introduction to knowledge sharing systems: considerations for the conceptual ...Nikos Manouselis
This document discusses conceptual design considerations for TAPipedia, a knowledge sharing system for agricultural and biodiversity sciences. It considers building (1) a wiki-based encyclopedia, (2) a repository for uploading and tagging content, or (3) a search engine or collaboration portal. The author recommends a network of interconnected local and regional knowledge hubs to embrace sharing of local knowledge, and prioritizing helping stakeholders identify capacity development needs and share context-specific knowledge.
FAIRy stories: the FAIR Data principles in theory and in practiceCarole Goble
https://ucsb.zoom.us/meeting/register/tZYod-ippz4pHtaJ0d3ERPIFy2QIvKqjwpXR
FAIRy stories: the FAIR Data principles in theory and in practice
The ‘FAIR Guiding Principles for scientific data management and stewardship’ [1] launched a global dialogue within research and policy communities and started a journey to wider accessibility and reusability of data and preparedness for automation-readiness (I am one of the army of authors). Over the past 5 years FAIR has become a movement, a mantra and a methodology for scientific research and increasingly in the commercial and public sector. FAIR is now part of NIH, European Commission and OECD policy. But just figuring out what the FAIR principles really mean and how we implement them has proved more challenging than one might have guessed. To quote the novelist Rick Riordan “Fairness does not mean everyone gets the same. Fairness means everyone gets what they need”.
As a data infrastructure wrangler I lead and participate in projects implementing forms of FAIR in pan-national European biomedical Research Infrastructures. We apply web-based industry-lead approaches like Schema.org; work with big pharma on specialised FAIRification pipelines for legacy data; promote FAIR by Design methodologies and platforms into the researcher lab; and expand the principles of FAIR beyond data to computational workflows and digital objects. Many use Linked Data approaches.
In this talk I’ll use some of these projects to shine some light on the FAIR movement. Spoiler alert: although there are technical issues, the greatest challenges are social. FAIR is a team sport. Knowledge Graphs play a role – not just as consumers of FAIR data but as active contributors. To paraphrase another novelist, “It is a truth universally acknowledged that a Knowledge Graph must be in want of FAIR data.”
[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
The document discusses technologies and infrastructure for publishing biodiversity data from environmental impact assessments (EIA). It covers the types and formats of EIA biodiversity data, tools for data capture and digitization, platforms for data discovery and publishing, ensuring data quality, and hosting data centers to facilitate long-term archiving and publishing of EIA biodiversity data.
Extended version of slides used for talk on "Scaling up (and doing business with) food safety information transparency" at the Food@Cranfield network (http://www.som.cranfield.ac.uk/som/p19207/research/research-clubs/food-cranfield-research-network), on an event dedicated to Using Big Data. Presented the concept of using AGINFRA to facilitate and scale up food safety data. Part of the Big Data Europe (http://www.big-data-europe.eu) liaison & dissemination activities.
Slides of the AIMS webinar on the Conceptual Design of TAPipedia, introducing initial version of the Design for public feedback & comments.
http://aims.fao.org/activity/blog/new-webinarsaims%E2%80%9Cdesigning-tapipedia-information-sharing-platform-capacity-development
Making agricultural knowledge globally discoverable: are we there yet?Nikos Manouselis
This document discusses making agricultural knowledge globally accessible through open data initiatives. It describes Agro-Know's work in aggregating and organizing agricultural data from diverse sources to make it discoverable. Current efforts replicate work by harvesting, transforming and indexing data separately. The document envisions a large, open platform that catalogs all relevant agricultural information, makes it machine-readable and discoverable, and allows data to be shared and used to address societal challenges.
Agro-Know & the European agricultural research information ecosystemNikos Manouselis
The document discusses building a European data infrastructure for agricultural research information. It proposes connecting heterogeneous agricultural data sources to allow for unified querying. Semantic web technologies like linked open data would allow different communities to access the same data using their own vocabularies and ontologies. Challenges include querying very large distributed datasets and developing scalable semantic indexing. Potential collaborations are mentioned between the presenter's company, Agro-Know, and the Chinese Academy of Agricultural Sciences to share agricultural knowledge and research.
The webinar discussed FAIRDOM services that can help applicants to the ERACoBioTech call with their data management plans and requirements. FAIRDOM offers webinars on developing data management plans, and their platform and tools can help with organizing, storing, sharing, and publishing research data and models in a FAIR manner by utilizing metadata standards. Different levels of support are available, from general community resources through their hub, to premium customized support for individual projects. Consortia can include FAIRDOM as a subcontractor within the guidelines of the ERACoBioTech call.
FAIRDOM data management support for ERACoBioTech ProposalsFAIRDOM
This document provides information about a webinar from the FAIRDOM Consortium on data management for ERACoBioTech full proposals. It includes:
- Details on how to budget for and include a data management plan in proposals
- A checklist for developing a data management plan covering topics like the types and volumes of data, data sharing and reuse, and making data FAIR
- An overview of the FAIRDOM services and software platform that can help with project data management and stewardship
RDMkit, a Research Data Management Toolkit. Built by the Community for the ...Carole Goble
https://datascience.nih.gov/news/march-data-sharing-and-reuse-seminar 11 March 2022
Starting in 2023, the US National Institutes of Health (NIH) will require institutes and researchers receiving funding to include a Data Management Plan (DMP) in their grant applications, including the making their data publicly available. Similar mandates are already in place in Europe, for example a DMP is mandatory in Horizon Europe projects involving data.
Policy is one thing - practice is quite another. How do we provide the necessary information, guidance and advice for our bioscientists, researchers, data stewards and project managers? There are numerous repositories and standards. Which is best? What are the challenges at each step of the data lifecycle? How should different types of data? What tools are available? Research Data Management advice is often too general to be useful and specific information is fragmented and hard to find.
ELIXIR, the pan-national European Research Infrastructure for Life Science data, aims to enable research projects to operate “FAIR data first”. ELIXIR supports researchers across their whole RDM lifecycle, navigating the complexity of a data ecosystem that bridges from local cyberinfrastructures to pan-national archives and across bio-domains.
The ELIXIR RDMkit (https://rdmkit.elixir-europe.org (link is external)) is a toolkit built by the biosciences community, for the biosciences community to provide the RDM information they need. It is a framework for advice and best practice for RDM and acts as a hub of RDM information, with links to tool registries, training materials, standards, and databases, and to services that offer deeper knowledge for DMP planning and FAIR-ification practices.
Launched in March 2021, over 120 contributors have provided nearly 100 pages of content and links to more than 300 tools. Content covers the data lifecycle and specialized domains in biology, national considerations and examples of “tool assemblies” developed to support RDM. It has been accessed by over 123 countries, and the top of the access list is … the United States.
The RDMkit is already a recommended resource of the European Commission. The platform, editorial, and contributor methods helped build a specialized sister toolkit for infectious diseases as part of the recently launched BY-COVID project. The toolkit’s platform is the simplest we could manage - built on plain GitHub - and the whole development and contribution approach tailored to be as lightweight and sustainable as possible.
In this talk, Carole and Frederik will present the RDMkit; aims and context, content, community management, how folks can contribute, and our future plans and potential prospects for trans-Atlantic cooperation.
Data policy must be partnered with data practice. Our researchers need to be the best informed in order to meet these new data management and data sharing mandates.
The Research Data Alliance (RDA) is a global organization that aims to build the social and technical infrastructure to enable open sharing of data across technologies, disciplines, and countries. It is supported by the European Commission, Australian National Data Service, and US National Science Foundation. RDA brings together experts and practitioners to develop standards, develop tools, and overcome barriers to data sharing through Working Groups and Interest Groups. Upcoming outputs from RDA in 2014 include developing systems for data type registries, persistent identifier information types, metadata standards, and practical data policies. RDA currently has over 1,500 members from over 70 countries working to advance open data sharing.
The document discusses how linked open data and semantic web technologies can be applied to educational data and resources on the web. It provides examples of projects that aim to expose, interlink, and enrich educational datasets using these technologies. The goal is to improve data sharing and interoperability, facilitate reuse of open educational resources, and leverage linked data as a knowledge base to support learning and education.
WWW2013 Tutorial: Linked Data & EducationStefan Dietze
Linked data provides opportunities for sharing educational data on the web in a standardized way. It allows for the integration of heterogeneous educational resources and datasets from different platforms. This can enable new applications like cross-platform recommender systems and exploratory search. However, there are also challenges to address like annotation overhead, performance, and scalability when dealing with large amounts of distributed data.
DataCite: the Perfect Complement to CrossRefCrossref
DataCite was created to address the lack of effective ways to link datasets to articles and identify datasets. It assigns digital object identifiers (DOIs) to datasets to allow them to be cited similarly to scholarly articles. Many research institutions and libraries around the world are members of DataCite, including organizations in Europe, North America, and Asia. DataCite helps establish datasets as legitimate contributions to the scientific record that can be identified and cited.
Presented by Tony Mathys at a Current Issues and Applications of the Geospatial Technologies Lecture, Department of Geography and Environment, Aberdeen University, 24 February 2012
The Research Data Alliance (RDA) is an international organization with over 10,000 members from 144 countries working to build the social and technical infrastructure to enable open sharing of data. Its vision is for researchers to openly share data across technologies, disciplines, and countries to address societal challenges. RDA has over 100 groups working on data interoperability issues and has produced 37 flagship outputs, including technical specifications, with over 100 adoption cases in various organizations and disciplines.
The Digital Curation Centre (DCC) helps research institutions and funders develop data management plans and policies. The DCC created an online tool called DMP Online that allows researchers to create customized data management plans that meet funder requirements. DMP Online provides guidance and templates on best practices. The DCC also analyzes funder policies and develops training and resources to help institutions build data management strategies and capabilities.
Being FAIR: FAIR data and model management SSBSS 2017 Summer SchoolCarole Goble
Lecture 1:
Being FAIR: FAIR data and model management
In recent years we have seen a change in expectations for the management of all the outcomes of research – that is the “assets” of data, models, codes, SOPs, workflows. The “FAIR” (Findable, Accessible, Interoperable, Reusable) Guiding Principles for scientific data management and stewardship [1] have proved to be an effective rallying-cry. Funding agencies expect data (and increasingly software) management retention and access plans. Journals are raising their expectations of the availability of data and codes for pre- and post- publication. The multi-component, multi-disciplinary nature of Systems and Synthetic Biology demands the interlinking and exchange of assets and the systematic recording of metadata for their interpretation.
Our FAIRDOM project (http://www.fair-dom.org) supports Systems Biology research projects with their research data, methods and model management, with an emphasis on standards smuggled in by stealth and sensitivity to asset sharing and credit anxiety. The FAIRDOM Platform has been installed by over 30 labs or projects. Our public, centrally hosted Asset Commons, the FAIRDOMHub.org, supports the outcomes of 50+ projects.
Now established as a grassroots association, FAIRDOM has over 8 years of experience of practical asset sharing and data infrastructure at the researcher coal-face ranging across European programmes (SysMO and ERASysAPP ERANets), national initiatives (Germany's de.NBI and Systems Medicine of the Liver; Norway's Digital Life) and European Research Infrastructures (ISBE) as well as in PI's labs and Centres such as the SynBioChem Centre at Manchester.
In this talk I will show explore how FAIRDOM has been designed to support Systems Biology projects and show examples of its configuration and use. I will also explore the technical and social challenges we face.
I will also refer to European efforts to support public archives for the life sciences. ELIXIR (http:// http://www.elixir-europe.org/) the European Research Infrastructure of 21 national nodes and a hub funded by national agreements to coordinate and sustain key data repositories and archives for the Life Science community, improve access to them and related tools, support training and create a platform for dataset interoperability. As the Head of the ELIXIR-UK Node and co-lead of the ELIXIR Interoperability Platform I will show how this work relates to your projects.
[1] Wilkinson et al, The FAIR Guiding Principles for scientific data management and stewardship Scientific Data 3, doi:10.1038/sdata.2016.18
Introduction to knowledge sharing systems: considerations for the conceptual ...Nikos Manouselis
This document discusses conceptual design considerations for TAPipedia, a knowledge sharing system for agricultural and biodiversity sciences. It considers building (1) a wiki-based encyclopedia, (2) a repository for uploading and tagging content, or (3) a search engine or collaboration portal. The author recommends a network of interconnected local and regional knowledge hubs to embrace sharing of local knowledge, and prioritizing helping stakeholders identify capacity development needs and share context-specific knowledge.
FAIRy stories: the FAIR Data principles in theory and in practiceCarole Goble
https://ucsb.zoom.us/meeting/register/tZYod-ippz4pHtaJ0d3ERPIFy2QIvKqjwpXR
FAIRy stories: the FAIR Data principles in theory and in practice
The ‘FAIR Guiding Principles for scientific data management and stewardship’ [1] launched a global dialogue within research and policy communities and started a journey to wider accessibility and reusability of data and preparedness for automation-readiness (I am one of the army of authors). Over the past 5 years FAIR has become a movement, a mantra and a methodology for scientific research and increasingly in the commercial and public sector. FAIR is now part of NIH, European Commission and OECD policy. But just figuring out what the FAIR principles really mean and how we implement them has proved more challenging than one might have guessed. To quote the novelist Rick Riordan “Fairness does not mean everyone gets the same. Fairness means everyone gets what they need”.
As a data infrastructure wrangler I lead and participate in projects implementing forms of FAIR in pan-national European biomedical Research Infrastructures. We apply web-based industry-lead approaches like Schema.org; work with big pharma on specialised FAIRification pipelines for legacy data; promote FAIR by Design methodologies and platforms into the researcher lab; and expand the principles of FAIR beyond data to computational workflows and digital objects. Many use Linked Data approaches.
In this talk I’ll use some of these projects to shine some light on the FAIR movement. Spoiler alert: although there are technical issues, the greatest challenges are social. FAIR is a team sport. Knowledge Graphs play a role – not just as consumers of FAIR data but as active contributors. To paraphrase another novelist, “It is a truth universally acknowledged that a Knowledge Graph must be in want of FAIR data.”
[1] Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18
The document discusses technologies and infrastructure for publishing biodiversity data from environmental impact assessments (EIA). It covers the types and formats of EIA biodiversity data, tools for data capture and digitization, platforms for data discovery and publishing, ensuring data quality, and hosting data centers to facilitate long-term archiving and publishing of EIA biodiversity data.
Extended version of slides used for talk on "Scaling up (and doing business with) food safety information transparency" at the Food@Cranfield network (http://www.som.cranfield.ac.uk/som/p19207/research/research-clubs/food-cranfield-research-network), on an event dedicated to Using Big Data. Presented the concept of using AGINFRA to facilitate and scale up food safety data. Part of the Big Data Europe (http://www.big-data-europe.eu) liaison & dissemination activities.
Slides of the AIMS webinar on the Conceptual Design of TAPipedia, introducing initial version of the Design for public feedback & comments.
http://aims.fao.org/activity/blog/new-webinarsaims%E2%80%9Cdesigning-tapipedia-information-sharing-platform-capacity-development
Making agricultural knowledge globally discoverable: are we there yet?Nikos Manouselis
This document discusses making agricultural knowledge globally accessible through open data initiatives. It describes Agro-Know's work in aggregating and organizing agricultural data from diverse sources to make it discoverable. Current efforts replicate work by harvesting, transforming and indexing data separately. The document envisions a large, open platform that catalogs all relevant agricultural information, makes it machine-readable and discoverable, and allows data to be shared and used to address societal challenges.
Agro-Know & the European agricultural research information ecosystemNikos Manouselis
The document discusses building a European data infrastructure for agricultural research information. It proposes connecting heterogeneous agricultural data sources to allow for unified querying. Semantic web technologies like linked open data would allow different communities to access the same data using their own vocabularies and ontologies. Challenges include querying very large distributed datasets and developing scalable semantic indexing. Potential collaborations are mentioned between the presenter's company, Agro-Know, and the Chinese Academy of Agricultural Sciences to share agricultural knowledge and research.
The webinar discussed FAIRDOM services that can help applicants to the ERACoBioTech call with their data management plans and requirements. FAIRDOM offers webinars on developing data management plans, and their platform and tools can help with organizing, storing, sharing, and publishing research data and models in a FAIR manner by utilizing metadata standards. Different levels of support are available, from general community resources through their hub, to premium customized support for individual projects. Consortia can include FAIRDOM as a subcontractor within the guidelines of the ERACoBioTech call.
FAIRDOM data management support for ERACoBioTech ProposalsFAIRDOM
This document provides information about a webinar from the FAIRDOM Consortium on data management for ERACoBioTech full proposals. It includes:
- Details on how to budget for and include a data management plan in proposals
- A checklist for developing a data management plan covering topics like the types and volumes of data, data sharing and reuse, and making data FAIR
- An overview of the FAIRDOM services and software platform that can help with project data management and stewardship
RDMkit, a Research Data Management Toolkit. Built by the Community for the ...Carole Goble
https://datascience.nih.gov/news/march-data-sharing-and-reuse-seminar 11 March 2022
Starting in 2023, the US National Institutes of Health (NIH) will require institutes and researchers receiving funding to include a Data Management Plan (DMP) in their grant applications, including the making their data publicly available. Similar mandates are already in place in Europe, for example a DMP is mandatory in Horizon Europe projects involving data.
Policy is one thing - practice is quite another. How do we provide the necessary information, guidance and advice for our bioscientists, researchers, data stewards and project managers? There are numerous repositories and standards. Which is best? What are the challenges at each step of the data lifecycle? How should different types of data? What tools are available? Research Data Management advice is often too general to be useful and specific information is fragmented and hard to find.
ELIXIR, the pan-national European Research Infrastructure for Life Science data, aims to enable research projects to operate “FAIR data first”. ELIXIR supports researchers across their whole RDM lifecycle, navigating the complexity of a data ecosystem that bridges from local cyberinfrastructures to pan-national archives and across bio-domains.
The ELIXIR RDMkit (https://rdmkit.elixir-europe.org (link is external)) is a toolkit built by the biosciences community, for the biosciences community to provide the RDM information they need. It is a framework for advice and best practice for RDM and acts as a hub of RDM information, with links to tool registries, training materials, standards, and databases, and to services that offer deeper knowledge for DMP planning and FAIR-ification practices.
Launched in March 2021, over 120 contributors have provided nearly 100 pages of content and links to more than 300 tools. Content covers the data lifecycle and specialized domains in biology, national considerations and examples of “tool assemblies” developed to support RDM. It has been accessed by over 123 countries, and the top of the access list is … the United States.
The RDMkit is already a recommended resource of the European Commission. The platform, editorial, and contributor methods helped build a specialized sister toolkit for infectious diseases as part of the recently launched BY-COVID project. The toolkit’s platform is the simplest we could manage - built on plain GitHub - and the whole development and contribution approach tailored to be as lightweight and sustainable as possible.
In this talk, Carole and Frederik will present the RDMkit; aims and context, content, community management, how folks can contribute, and our future plans and potential prospects for trans-Atlantic cooperation.
Data policy must be partnered with data practice. Our researchers need to be the best informed in order to meet these new data management and data sharing mandates.
The Research Data Alliance (RDA) is a global organization that aims to build the social and technical infrastructure to enable open sharing of data across technologies, disciplines, and countries. It is supported by the European Commission, Australian National Data Service, and US National Science Foundation. RDA brings together experts and practitioners to develop standards, develop tools, and overcome barriers to data sharing through Working Groups and Interest Groups. Upcoming outputs from RDA in 2014 include developing systems for data type registries, persistent identifier information types, metadata standards, and practical data policies. RDA currently has over 1,500 members from over 70 countries working to advance open data sharing.
This document discusses FAIR data principles and open data. It provides an overview of the FAIR data principles of Findable, Accessible, Interoperable and Reusable data. It outlines the benefits of open data in a big data world but also acknowledges the challenges of implementing open data practices. The document proposes establishing an African Open Data Forum and developing research data infrastructure, skills training, policies and strategies to support open science and FAIR data practices in Africa.
Why are e-Infrastructures useful from a small business perspective?Nikos Manouselis
Slides of talk at seminar for the EuroRIs network (http://www.euroris-net.eu) of National Contact Points (NCPs) for EU funding programmes on Research Infrastructures.
This document discusses data collections and some of the challenges associated with them. It defines data collections as collections of numeric data from sources like surveys and polls that are in machine-readable formats. It notes that libraries are increasingly involved in preserving and providing access to institutional research data. Some challenges discussed include the costs associated with subscriptions, selection decisions, supporting user access through finding aids and education, and infrastructure issues around storage, systems, and institutional support. The document emphasizes that metadata standards and data curation are important areas for ensuring long-term preservation and understanding of data collections.
NHM Data Portal: first steps toward the Graph-of-LifeEdward Baker
This document summarizes a presentation about the Natural History Museum's (NHM) efforts to create a centralized data portal and move towards a "Graph of Life" by connecting their collected data. It describes the large number and variety of objects in the NHM collections, efforts to digitize specimens, and challenges with previous disconnected digital access systems. The new NHM Data Portal aims to make data discovery and access easier through an open-source CKAN platform, providing over 3.7 million records and APIs. It discusses using the portal and linked open data approaches to ask new questions across datasets, provide metrics on data quality and use, and integrate with external aggregators.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Open@Fao presentation at the EADI Open For Development Project, 2012
1. Open For Development
EADI IMWG Conference 2012
Open @ FAO
Stephen.Katz@ fao.org (Twitter: @SteveK1958)
Chief, Knowledge Management and Library Services
Food and Agriculture Organization of the United Nations
2. Agenda
Open @ FAO
1 Context and History of Open @ FAO
Ongoing Practical Initiatives
2 • FAO Open Archive
• Open Data (data.fao.org)
• Data Governance and Standards
3
Issues, Challenges and Lessons Learned
4 Group Discussion
3. Open @ FAO : Food For Thought?
Food for Thought
4. Food and Agriculture Organization of the United Nations
(FAO)
• FAO is a specialized
agency of the United
Nations with its own
independent governance
• 190+ Member Countries
• HQs in Rome, Offices in
over 80 countries with
over 5000 staff.
5. Food and Agriculture Organization of the United Nations
(FAO)
• Collects, analyses, interprets and
disseminates information on
nutrition, food and agriculture
• Policy Advice
• Furnishes Technical Assistance
• A Neutral Forum for International
Cooperation
6. FAO has been in the
“knowledge” business
since 1946!
Our mandate....
Ensure that the world’s
knowledge of food and
agriculture is available to
those who need it when
they need it and in a form
which they can access
and use.
7. Open @ FAO : A Bit of History
1995 – Central Publishing Unit Abolished
1996 – SGML Repository Proposal; FAOSTAT on-line
1997 – Document Repository (XML Compatible)
2003 – Document Repository (PDF)
2007 – Open Archive Proposal (Fedora Commons)
2010 – Open Data Repository Proposal (data.fao.org)
2012 – OpenArchive.Fao.Org; Data.Fao.Org
8. FAO Open Archive
Goals/Objectives
To make FAO’s Global Public Goods openly
accessible from a single access point
To be able to exchange data in an open and
standardized way
To have a smooth/efficient workflow to
manage FAO’s Institutional memory
To integrate e-publishing and library workflows
9. FAO Open Archive
Architecture
Based on Open Source tools (Fedora
Commons and Java)
Based on modern standards for data
management (MODS and FRBR)
Allowing for easier management and sharing
of multilingual content
And this is what it looks like:
10.
11.
12.
13.
14.
15.
16. Open Archive Resources
Available at Start-up Time
Resource Type Number of Records
Full Text Documents 40,100
Photos and Videos 17,100
Audio Files 1,200
17. Open Data (data.fao.org)
Goals/Objectives
To address fragmentation and duplication of
information systems and data presently distributed
across many organizational units
http://data.fao.org: one-stop shop that aggregates,
integrates, and catalogues data from multiple sources
across FAO. Topics are related to nutrition, food and
agriculture and include statistics, maps, pictures,
documents and more.
18. Open Data (data.fao.org)
Guiding Principles
Uniting FAO data with one brand : http://data.fao.org
Engaging a Community : #FAOdata
Mobile First
Serve the data in the most convenient format
Integrate, don't reimplement
19. data.fao.org - The Big Picture
Specialised
Website Services and Widgets application(s)
consume/provide
Orchestration and Integration
Search Catalogue Statistics Maps Content Infrastructure
Statistical Data
Full text Identity Warehouse Geospatial Documents Logging
Structured Metadata Raster Pictures Caching
Linked Data Time Series Vector Video Security
... Indicators Point Multimedia Audit
Observations Pages ...
20. Data Flow Architecture
Data
Data Source
Source
Ingest
Harmonise
Data
Integrate
Source
Enrich
Publish
Data
Source Data
Source
26. CIARD – a global movement
• All organizations that create and
To make
possess public agricultural
agricultural research information disseminate
research and share it more widely
information • CIARD partners create coherence
and by a) coordinating their efforts, b)
knowledge promoting common formats, c)
truly acessible adopting open systems and
to all standards
• Create a global network of public
collections of data and information
28. Distributed Data Sets
• stats
• gene banks
• gis data
• blogs,
• journals
• open archives
• raw data
• technologies
• learning objects
• ………..
How to make value added services?
How to infer new knowledge?
How to organize collaboration?
Maybe we really need this?...
29. …to
• stats
• gene banks
• gis data
• blogs,
• journals
• open archives
• raw data
• technologies
• learning objects
• ………..
31. OpenAgris
Aggregates different data sources to expand
knowledge about a topic
Is a “linked-data” environment mashing-up
interlinked datasets to create an integrated
knowledge base
OpenAgris uses the Agrovoc thesaurus as
backbone to interlink to other existing
datasets (DBPedia, WorldBank, Geopolitical
Ontology…)
32.
33. Open Archive : Issues, Challenges, Lessons
Unclear Policy Framework
Unclear collection selection policy
Variable quality standards (content, legal, editorial,
accountability)
Licensing policy/conditions for re-use
Working with partners and scientific journals
Freely available but need attribution
Supply vs demand (personal interest vs impact)
Tension with Sales and Marketing needs
May Lead To Negative Consequences such as:
Low credibility/trust, reputational risk, legal exposure?
34. Open Data : Issues, Challenges, Lessons
Well the same stuff as before really
Unclear Policy Framework
Unclear collection selection policy
Variable quality standards
Licensing policy/conditions for re-use
Working with partners
Freely available but need attribution
Supply vs demand (personal interest vs impact)
Tension with Sales and Marketing needs
May Lead To Negative Consequences such as:
Low credibility/trust, reputational risk, legal exposure?
35. Open Data : Issues, Challenges, Lessons
But also:
Every data-type has it’s own standards (e.g. OGC for GIS,
SDMX for stats, MODS for documents, IPTC for Photos)
Aggregate data quality set by lowest common denominator
Poor data governance leads to:
Conflicting/contradictory data values from different sources
Lack of agreement of definitions and concepts, and
Insufficient metadata
Comparing apples, pears and oranges (different units, different
assumptions, different contexts)
May Lead To Negative Consequences such as:
Low credibility/trust, reputational risk, legal exposure?