The document provides information about ELIXIR-UK, which is the UK node of ELIXIR, a European infrastructure for biological information. ELIXIR-UK is a network of 18 UK organizations and has established training programs, services, and communities. It coordinates UK participation in ELIXIR and related EU projects. ELIXIR-UK also works to establish interoperability across biological data resources and help make these resources FAIR (Findable, Accessible, Interoperable, Reusable). It is working to establish BioFAIR, a proposed new institute that would coordinate UK life science data infrastructure.
German Conference on Bioinformatics 2021
https://gcb2021.de/
FAIR Computational Workflows
Computational workflows capture precise descriptions of the steps and data dependencies needed to carry out computational data pipelines, analysis and simulations in many areas of Science, including the Life Sciences. The use of computational workflows to manage these multi-step computational processes has accelerated in the past few years driven by the need for scalable data processing, the exchange of processing know-how, and the desire for more reproducible (or at least transparent) and quality assured processing methods. The SARS-CoV-2 pandemic has significantly highlighted the value of workflows.
This increased interest in workflows has been matched by the number of workflow management systems available to scientists (Galaxy, Snakemake, Nextflow and 270+ more) and the number of workflow services like registries and monitors. There is also recognition that workflows are first class, publishable Research Objects just as data are. They deserve their own FAIR (Findable, Accessible, Interoperable, Reusable) principles and services that cater for their dual roles as explicit method description and software method execution [1]. To promote long-term usability and uptake by the scientific community, workflows (as well as the tools that integrate them) should become FAIR+R(eproducible), and citable so that author’s credit is attributed fairly and accurately.
The work on improving the FAIRness of workflows has already started and a whole ecosystem of tools, guidelines and best practices has been under development to reduce the time needed to adapt, reuse and extend existing scientific workflows. An example is the EOSC-Life Cluster of 13 European Biomedical Research Infrastructures which is developing a FAIR Workflow Collaboratory based on the ELIXIR Research Infrastructure for Life Science Data Tools ecosystem. While there are many tools for addressing different aspects of FAIR workflows, many challenges remain for describing, annotating, and exposing scientific workflows so that they can be found, understood and reused by other scientists.
This keynote will explore the FAIR principles for computational workflows in the Life Science using the EOSC-Life Workflow Collaboratory as an example.
[1] Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes,Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters, and Daniel Schober FAIR Computational Workflows Data Intelligence 2020 2:1-2, 108-121 https://doi.org/10.1162/dint_a_00033.
presentation at https://researchsoft.github.io/FAIReScience/, FAIReScience 2021 online workshop
virtually co-located with the 17th IEEE International Conference on eScience (eScience 2021)
FAIR Computational Workflows
Computational workflows capture precise descriptions of the steps and data dependencies needed to carry out computational data pipelines, analysis and simulations in many areas of Science, including the Life Sciences. The use of computational workflows to manage these multi-step computational processes has accelerated in the past few years driven by the need for scalable data processing, the exchange of processing know-how, and the desire for more reproducible (or at least transparent) and quality assured processing methods. The SARS-CoV-2 pandemic has significantly highlighted the value of workflows.
This increased interest in workflows has been matched by the number of workflow management systems available to scientists (Galaxy, Snakemake, Nextflow and 270+ more) and the number of workflow services like registries and monitors. There is also recognition that workflows are first class, publishable Research Objects just as data are. They deserve their own FAIR (Findable, Accessible, Interoperable, Reusable) principles and services that cater for their dual roles as explicit method description and software method execution [1]. To promote long-term usability and uptake by the scientific community, workflows (as well as the tools that integrate them) should become FAIR+R(eproducible), and citable so that author’s credit is attributed fairly and accurately.
The work on improving the FAIRness of workflows has already started and a whole ecosystem of tools, guidelines and best practices has been under development to reduce the time needed to adapt, reuse and extend existing scientific workflows. An example is the EOSC-Life Cluster of 13 European Biomedical Research Infrastructures which is developing a FAIR Workflow Collaboratory based on the ELIXIR Research Infrastructure for Life Science Data Tools ecosystem. While there are many tools for addressing different aspects of FAIR workflows, many challenges remain for describing, annotating, and exposing scientific workflows so that they can be found, understood and reused by other scientists.
This keynote will explore the FAIR principles for computational workflows in the Life Science using the EOSC-Life Workflow Collaboratory as an example.
[1] Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes,Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters, and Daniel Schober FAIR Computational Workflows Data Intelligence 2020 2:1-2, 108-121 https://doi.org/10.1162/dint_a_00033.
Reproducibility - The myths and truths of pipeline bioinformaticsSimon Cockell
In a talk for the Newcastle Bioinformatics Special Interest Group (http://bsu.ncl.ac.uk/fms-bioinformatics) I explored the topic of reproducibility. Looking at the pros and cons of pipelining analyses, as well as some tools for achieving this. I also considered some additional tools for enabling reproducible bioinformatics, and look at the 'executable paper', and whether it represents the future for bioinformatics publishing.
Scientific Workflows: what do we have, what do we miss?Paolo Romano
Presentation given on June 22, 2013, in Nice, at the CIBB 2013 International Workshop.
In collaboration with Paolo Missier, University of Newcastle upon Tyne, UK
Better software, better service, better research: The Software Sustainabilit...Carole Goble
Ever spotted some great looking software only to discover you can’t get it, it doesn’t work, there is no documentation to help fix it and the developers don’t have the time or incentive to help? Ever produced some software that you want to be widely used or have folks contribute? What’s the sustainability of that key platform/library/tool /database your lab uses day in and day out? Are you helping the providers? The same issues stand for Data (or as we now say “FAIR” Findable, Accessible, Interoperable, Reusable Data) and its metadata. Is anyone looking out for Europe’s data services– the datasets and analysis systems you use and you make – the standards they use and the curators and developers who make them? Or is FAIR just a FAIRy story? I’ll tell how two organisations with quite different structures and approaches - the UK’s Software Sustainability Institute and the ELIXIR European Research Infrastructure for Life Science Data – are working for the common goal of better software, better service, and better research.
https://www.rothamsted.ac.uk/events/14th-international-symposium-integrative-bioinformatics
German Conference on Bioinformatics 2021
https://gcb2021.de/
FAIR Computational Workflows
Computational workflows capture precise descriptions of the steps and data dependencies needed to carry out computational data pipelines, analysis and simulations in many areas of Science, including the Life Sciences. The use of computational workflows to manage these multi-step computational processes has accelerated in the past few years driven by the need for scalable data processing, the exchange of processing know-how, and the desire for more reproducible (or at least transparent) and quality assured processing methods. The SARS-CoV-2 pandemic has significantly highlighted the value of workflows.
This increased interest in workflows has been matched by the number of workflow management systems available to scientists (Galaxy, Snakemake, Nextflow and 270+ more) and the number of workflow services like registries and monitors. There is also recognition that workflows are first class, publishable Research Objects just as data are. They deserve their own FAIR (Findable, Accessible, Interoperable, Reusable) principles and services that cater for their dual roles as explicit method description and software method execution [1]. To promote long-term usability and uptake by the scientific community, workflows (as well as the tools that integrate them) should become FAIR+R(eproducible), and citable so that author’s credit is attributed fairly and accurately.
The work on improving the FAIRness of workflows has already started and a whole ecosystem of tools, guidelines and best practices has been under development to reduce the time needed to adapt, reuse and extend existing scientific workflows. An example is the EOSC-Life Cluster of 13 European Biomedical Research Infrastructures which is developing a FAIR Workflow Collaboratory based on the ELIXIR Research Infrastructure for Life Science Data Tools ecosystem. While there are many tools for addressing different aspects of FAIR workflows, many challenges remain for describing, annotating, and exposing scientific workflows so that they can be found, understood and reused by other scientists.
This keynote will explore the FAIR principles for computational workflows in the Life Science using the EOSC-Life Workflow Collaboratory as an example.
[1] Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes,Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters, and Daniel Schober FAIR Computational Workflows Data Intelligence 2020 2:1-2, 108-121 https://doi.org/10.1162/dint_a_00033.
presentation at https://researchsoft.github.io/FAIReScience/, FAIReScience 2021 online workshop
virtually co-located with the 17th IEEE International Conference on eScience (eScience 2021)
FAIR Computational Workflows
Computational workflows capture precise descriptions of the steps and data dependencies needed to carry out computational data pipelines, analysis and simulations in many areas of Science, including the Life Sciences. The use of computational workflows to manage these multi-step computational processes has accelerated in the past few years driven by the need for scalable data processing, the exchange of processing know-how, and the desire for more reproducible (or at least transparent) and quality assured processing methods. The SARS-CoV-2 pandemic has significantly highlighted the value of workflows.
This increased interest in workflows has been matched by the number of workflow management systems available to scientists (Galaxy, Snakemake, Nextflow and 270+ more) and the number of workflow services like registries and monitors. There is also recognition that workflows are first class, publishable Research Objects just as data are. They deserve their own FAIR (Findable, Accessible, Interoperable, Reusable) principles and services that cater for their dual roles as explicit method description and software method execution [1]. To promote long-term usability and uptake by the scientific community, workflows (as well as the tools that integrate them) should become FAIR+R(eproducible), and citable so that author’s credit is attributed fairly and accurately.
The work on improving the FAIRness of workflows has already started and a whole ecosystem of tools, guidelines and best practices has been under development to reduce the time needed to adapt, reuse and extend existing scientific workflows. An example is the EOSC-Life Cluster of 13 European Biomedical Research Infrastructures which is developing a FAIR Workflow Collaboratory based on the ELIXIR Research Infrastructure for Life Science Data Tools ecosystem. While there are many tools for addressing different aspects of FAIR workflows, many challenges remain for describing, annotating, and exposing scientific workflows so that they can be found, understood and reused by other scientists.
This keynote will explore the FAIR principles for computational workflows in the Life Science using the EOSC-Life Workflow Collaboratory as an example.
[1] Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes,Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters, and Daniel Schober FAIR Computational Workflows Data Intelligence 2020 2:1-2, 108-121 https://doi.org/10.1162/dint_a_00033.
Reproducibility - The myths and truths of pipeline bioinformaticsSimon Cockell
In a talk for the Newcastle Bioinformatics Special Interest Group (http://bsu.ncl.ac.uk/fms-bioinformatics) I explored the topic of reproducibility. Looking at the pros and cons of pipelining analyses, as well as some tools for achieving this. I also considered some additional tools for enabling reproducible bioinformatics, and look at the 'executable paper', and whether it represents the future for bioinformatics publishing.
Scientific Workflows: what do we have, what do we miss?Paolo Romano
Presentation given on June 22, 2013, in Nice, at the CIBB 2013 International Workshop.
In collaboration with Paolo Missier, University of Newcastle upon Tyne, UK
Better software, better service, better research: The Software Sustainabilit...Carole Goble
Ever spotted some great looking software only to discover you can’t get it, it doesn’t work, there is no documentation to help fix it and the developers don’t have the time or incentive to help? Ever produced some software that you want to be widely used or have folks contribute? What’s the sustainability of that key platform/library/tool /database your lab uses day in and day out? Are you helping the providers? The same issues stand for Data (or as we now say “FAIR” Findable, Accessible, Interoperable, Reusable Data) and its metadata. Is anyone looking out for Europe’s data services– the datasets and analysis systems you use and you make – the standards they use and the curators and developers who make them? Or is FAIR just a FAIRy story? I’ll tell how two organisations with quite different structures and approaches - the UK’s Software Sustainability Institute and the ELIXIR European Research Infrastructure for Life Science Data – are working for the common goal of better software, better service, and better research.
https://www.rothamsted.ac.uk/events/14th-international-symposium-integrative-bioinformatics
The swings and roundabouts of a decade of fun and games with Research Objects Carole Goble
Research Objects and their instantiation as RO-Crate: motivation, explanation, examples, history and lessons, and opportunities for scholarly communications, delivered virtually to 17th Italian Research Conference on Digital Libraries
FAIR Data Bridging from researcher data management to ELIXIR archives in the...Carole Goble
ISMB-ECCB 2021, NIH/ODSS Session, 27 July 2021
ELIXIR is the pan-national European Research Infrastructure for Life Science data, whose 23 national nodes and the EBI coordinate the development and long-term sustainability of domain public databases. FAIR services, policies and curation approaches aim to build a FAIR connected data ecosystem of trusted domain repositories, from ENA, HPA and EGA to specialised resources like CorkOakDB and PIPPA for plant phenotypes. But this is only one part of the data landscape and often the end of data’s journey. The nodes support research projects to operate “FAIR data first”, working with institutional and national platforms that are often generic or designed for project-based data management. We need to bridge between project-based and community-based, and support researchers across their whole RDM lifecycle, navigating the complexity this ecosystem. The ELIXIR-CONVERGE project and its flagship RDMkit toolkit (https://rdmkit.elixir-europe.org) aims to do just that.
Open Science: how to serve the needs of the researcher? Carole Goble
Open science Jisc CNI roundtable 2018
Lightning talk
What should the future look like?
What are the essential characteristics we desire in a relatively near future system to support scholarly communication across the full research life cycle?
What are the key areas requiring attention, action, or investment today to reach the future that we want to reach?
What are the best opportunities to build upon existing practices, investments and infrastructure, both
open and commercially provided?
Where must alternatives be developed?
What areas are already on good trajectories and can be left to evolve without additional intervention
RO-Crate: A framework for packaging research products into FAIR Research ObjectsCarole Goble
RO-Crate: A framework for packaging research products into FAIR Research Objects presented to Research Data Alliance RDA Data Fabric/GEDE FAIR Digital Object meeting. 2021-02-25
FAIR Workflows and Research Objects get a Workout Carole Goble
So, you want to build a pan-national digital space for bioscience data and methods? That works with a bunch of pre-existing data repositories and processing platforms? So you can share FAIR workflows and move them between services? Package them up with data and other stuff (or just package up data for that matter)? How? WorkflowHub (https://workflowhub.eu) and RO-Crate Research Objects (https://www.researchobject.org/ro-crate) that’s how! A step towards FAIR Digital Objects gets a workout.
Presented at DataVerse Community Meeting 2021
Building the FAIR Research Commons: A Data Driven Society of ScientistsCarole Goble
Science is knowledge work. The scientific method and scholarly communication are about facilitating “knowledge turns” – that is, the turning of observation and hypothesis through experimentation, comparison, and analysis into new, pooled knowledge. Turns depend on the FAIR flow and availability of data, methods for automated processing, reproducible results and on a society of scientists coordinating and collaborating. We need to build a new form of Research Commons and I will present my steps towards this.
Presented at Symposium: The Future of a Data-Driven Society, Maastricht University, 25 Jan 2018 that accompanied the 42nd Dies Natalis where I was awarded an honorary doctorate
Personal video:
https://www.youtube.com/watch?v=k5WN6KDDatU&index=4&list=PLzi-FBaZlOOagma5dCW7WSA5lv22tmNMD
Video of the symposium:
https://www.youtube.com/watch?v=JN9eMMtCHf8&t=19s&index=6&list=PLzi-FBaZlOOagma5dCW7WSA5lv22tmNMD
presented at WORKS 2021
https://works-workshop.org/
16th Workshop on Workflows in Support of Large-Scale Science
November 15, 2021
Held in conjunction with SC21: The International Conference for High Performance Computing, Networking, Storage and Analysis
What is Reproducibility? The R* brouhaha (and how Research Objects can help)Carole Goble
presented at 1st First International Workshop on Reproducible Open Science @ TPDL, 9 Sept 2016, Hannover, Germany
http://repscience2016.research-infrastructures.eu/
Publishing your research: Research Data Management (Introduction) Jamie Bisset
Publishing your research: Research Data Management (Introduction) (November 2013) slides. Delivered as part of the Durham University Researcher Development Programme. Further Training available at https://www.dur.ac.uk/library/research/training/
A Big Picture in Research Data ManagementCarole Goble
A personal view of the big picture in Research Data Management, given at GFBio - de.NBI Summer School 2018 Riding the Data Life Cycle! Braunschweig Integrated Centre of Systems Biology (BRICS), 03 - 07 September 2018
A keynote given on the FAIR Data Principles at the FAIRplus Innovation and SME Forum, Hinxton Genome Campus, Cambridge, UK, 29 January 2020. The history of the principles, issues about the principles and speculations about the future
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 European Open Science Cloud: just what is it?Carole Goble
Presented at Jisc and CNI leaders conference 2018, 2 July 2018, Oxford, UK (https://www.jisc.ac.uk/events/jisc-and-cni-leaders-conference-02-jul-2018). The European Open Science Cloud. What exactly is it? In principle it is conceived as a virtual environment with open and seamless services for storage, management, analysis and re-use of research data, across borders and scientific disciplines. How? By federating existing scientific data infrastructures, currently dispersed across disciplines and Member States. In practice, what it is depends on the stakeholder. To European Research Infrastructures it’s a coordinated mission to organise and exchange their data, metadata, software and services to be FAIR – Findable, Accessible, Interoperable, Reusable – and to use e-Infrastructures, either EU or commercial. To EU e-Infrastructures offering data storage and cloud services, it’s a funding mission to integrate their services, policies and organisational structures, and to be used by the Research Infrastructures. To agencies it’s a means to promote Open Science, standardisation, cross-disciplinary research and coordinated investment with a dream of a “one stop shop” for researchers. And for Libraries?
The swings and roundabouts of a decade of fun and games with Research Objects Carole Goble
Research Objects and their instantiation as RO-Crate: motivation, explanation, examples, history and lessons, and opportunities for scholarly communications, delivered virtually to 17th Italian Research Conference on Digital Libraries
FAIR Data Bridging from researcher data management to ELIXIR archives in the...Carole Goble
ISMB-ECCB 2021, NIH/ODSS Session, 27 July 2021
ELIXIR is the pan-national European Research Infrastructure for Life Science data, whose 23 national nodes and the EBI coordinate the development and long-term sustainability of domain public databases. FAIR services, policies and curation approaches aim to build a FAIR connected data ecosystem of trusted domain repositories, from ENA, HPA and EGA to specialised resources like CorkOakDB and PIPPA for plant phenotypes. But this is only one part of the data landscape and often the end of data’s journey. The nodes support research projects to operate “FAIR data first”, working with institutional and national platforms that are often generic or designed for project-based data management. We need to bridge between project-based and community-based, and support researchers across their whole RDM lifecycle, navigating the complexity this ecosystem. The ELIXIR-CONVERGE project and its flagship RDMkit toolkit (https://rdmkit.elixir-europe.org) aims to do just that.
Open Science: how to serve the needs of the researcher? Carole Goble
Open science Jisc CNI roundtable 2018
Lightning talk
What should the future look like?
What are the essential characteristics we desire in a relatively near future system to support scholarly communication across the full research life cycle?
What are the key areas requiring attention, action, or investment today to reach the future that we want to reach?
What are the best opportunities to build upon existing practices, investments and infrastructure, both
open and commercially provided?
Where must alternatives be developed?
What areas are already on good trajectories and can be left to evolve without additional intervention
RO-Crate: A framework for packaging research products into FAIR Research ObjectsCarole Goble
RO-Crate: A framework for packaging research products into FAIR Research Objects presented to Research Data Alliance RDA Data Fabric/GEDE FAIR Digital Object meeting. 2021-02-25
FAIR Workflows and Research Objects get a Workout Carole Goble
So, you want to build a pan-national digital space for bioscience data and methods? That works with a bunch of pre-existing data repositories and processing platforms? So you can share FAIR workflows and move them between services? Package them up with data and other stuff (or just package up data for that matter)? How? WorkflowHub (https://workflowhub.eu) and RO-Crate Research Objects (https://www.researchobject.org/ro-crate) that’s how! A step towards FAIR Digital Objects gets a workout.
Presented at DataVerse Community Meeting 2021
Building the FAIR Research Commons: A Data Driven Society of ScientistsCarole Goble
Science is knowledge work. The scientific method and scholarly communication are about facilitating “knowledge turns” – that is, the turning of observation and hypothesis through experimentation, comparison, and analysis into new, pooled knowledge. Turns depend on the FAIR flow and availability of data, methods for automated processing, reproducible results and on a society of scientists coordinating and collaborating. We need to build a new form of Research Commons and I will present my steps towards this.
Presented at Symposium: The Future of a Data-Driven Society, Maastricht University, 25 Jan 2018 that accompanied the 42nd Dies Natalis where I was awarded an honorary doctorate
Personal video:
https://www.youtube.com/watch?v=k5WN6KDDatU&index=4&list=PLzi-FBaZlOOagma5dCW7WSA5lv22tmNMD
Video of the symposium:
https://www.youtube.com/watch?v=JN9eMMtCHf8&t=19s&index=6&list=PLzi-FBaZlOOagma5dCW7WSA5lv22tmNMD
presented at WORKS 2021
https://works-workshop.org/
16th Workshop on Workflows in Support of Large-Scale Science
November 15, 2021
Held in conjunction with SC21: The International Conference for High Performance Computing, Networking, Storage and Analysis
What is Reproducibility? The R* brouhaha (and how Research Objects can help)Carole Goble
presented at 1st First International Workshop on Reproducible Open Science @ TPDL, 9 Sept 2016, Hannover, Germany
http://repscience2016.research-infrastructures.eu/
Publishing your research: Research Data Management (Introduction) Jamie Bisset
Publishing your research: Research Data Management (Introduction) (November 2013) slides. Delivered as part of the Durham University Researcher Development Programme. Further Training available at https://www.dur.ac.uk/library/research/training/
A Big Picture in Research Data ManagementCarole Goble
A personal view of the big picture in Research Data Management, given at GFBio - de.NBI Summer School 2018 Riding the Data Life Cycle! Braunschweig Integrated Centre of Systems Biology (BRICS), 03 - 07 September 2018
A keynote given on the FAIR Data Principles at the FAIRplus Innovation and SME Forum, Hinxton Genome Campus, Cambridge, UK, 29 January 2020. The history of the principles, issues about the principles and speculations about the future
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 European Open Science Cloud: just what is it?Carole Goble
Presented at Jisc and CNI leaders conference 2018, 2 July 2018, Oxford, UK (https://www.jisc.ac.uk/events/jisc-and-cni-leaders-conference-02-jul-2018). The European Open Science Cloud. What exactly is it? In principle it is conceived as a virtual environment with open and seamless services for storage, management, analysis and re-use of research data, across borders and scientific disciplines. How? By federating existing scientific data infrastructures, currently dispersed across disciplines and Member States. In practice, what it is depends on the stakeholder. To European Research Infrastructures it’s a coordinated mission to organise and exchange their data, metadata, software and services to be FAIR – Findable, Accessible, Interoperable, Reusable – and to use e-Infrastructures, either EU or commercial. To EU e-Infrastructures offering data storage and cloud services, it’s a funding mission to integrate their services, policies and organisational structures, and to be used by the Research Infrastructures. To agencies it’s a means to promote Open Science, standardisation, cross-disciplinary research and coordinated investment with a dream of a “one stop shop” for researchers. And for Libraries?
Introduction to ELIXIR-UK's training activities presented by Rita Hendricusdottir at the ELIXIR-UK Workshop during Genome Science 2016 in Liverpool on 31st August 2016
Text (personal views position statement) to accompany presentation on what research infrastructures really need for data, XLDB-Europe, 8-10th June 2011, Edinburgh
The Ascent of Open Science and the European Open Science CloudTiziana Ferrari
Open science is becoming more and more part of the daily practice in conducting science. Around the world, researchers are increasingly aware of the value and importance of open science. As scientific research becomes highly data-driven and dependent on computing, scientists are conscious of the growing need to share data, software and infrastructure to reduce wasteful duplication and increase economies of scale. In an ideal world, every step of the research process would be public and transparent – the full methodology and all the tools used, as well as the data, would be accessible to the public and all groups without restriction, enabling reproducibility and refinement by other scientists.
This presentation will show case a number of success stories indicating how federated digital infrastructure, that have been sustained by the member states and the European Commission, have become an indispensable tool to enable collaboration ad sharing.
The European Open Science Cloud was launched by the European Commission in 2016 aiming to (1) increase the ability to exploit research data across scientific disciplines and between the public and private sector, (2) interconnect existing and new digital infrastructures in Europe and (3) support open science.
The presentation showcases how open data, open data analytics and open e-Infrastructures like EGI (https://www.egi.eu/) have been key enables of scientific discoveries from the discovery of gravitational waves with LIGO-VIRGO to drug design with the molecular modelling tools of WeNMR.
EOSC-hub (https://www.eosc-hub.eu/) - the first and the largest of the EOSC implementation projects of the H2020 funding programme, has succeeded in delivering some of the building blocks like the EOSC portal and Marketplace, tools and processes for federating data and services providers, harmonized policies, a federated AAI infrastructure, Competence Centres to support research infrastructures in their complex digital needs, interoperability guidelines and the Early Adopter Programme to provide expert support and service capacity to research projects.
Approach and outcome of the Biodiversity Virtual e-Laboratory (BioVeL) projectAlex Hardisty
Describes what we set out to do, what we achieved, and some of the lessons learnt during the BioVeL project. This presentation was given at the BioVeL final event "BioVeL In Practice and In Future", Paris, 13th November 2014
Similar to ELIXIR UK Node presentation to the ELIXIR Board (20)
The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...Carole Goble
Presented at the FAIR Data in Practice Symposium, 16 may 2023 at BioITWorld Boston. https://www.bio-itworldexpo.com/fair-data. The ELIXIR European research Infrastructure for life science data is an inter-governmental organizations coordinating, integrating and sustaining FAIR data and software resources across its 23 nations. To help advise users, data stewards, project managers and service providers, ELIXIR has developed complementary community-driven, open knowledge resources for guiding FAIR Research Data Management (RDMkit) and providing FAIRification recipes (FAIRCookbook). 150+ people have contributed content so far, including representatives of the pharmaceutical industry.
Can’t Pay, Won’t Pay, Don’t Pay: Delivering open science, a Digital Research...Carole Goble
Invited talk, PHIL_OS, March 30-31 2023, Exeter
https://opensciencestudies.eu/whither-open-science. Includes hidden slides.
FAIR and Open Science needs Digital Research Infrastructure, which is a federated system of systems and needs funding models that are fit for purpose
Culture change needed for paying for Open Science’s infrastructure and funding support for data driven research needs more reality and less rhetoric
RO-Crate: packaging metadata love notes into FAIR Digital ObjectsCarole Goble
Abstract
slides available at: https://zenodo.org/record/7147703#.Y7agoxXP2F4
The Helmholtz Metadata Collaboration aims to make the research data [and software] produced by Helmholtz Centres FAIR for their own and the wider science community by means of metadata enrichment [1]. Why metadata enrichment and why FAIR? Because the whole scientific enterprise depends on a cycle of finding, exchanging, understanding, validating, reproducing), integrating and reusing research entities across a dispersed community of researchers.
Metadata is not just “a love note to the future” [2], it is a love note to today’s collaborators and peers. Moreover, a FAIR Commons must cater for the metadata of all the entities of research – data, software, workflows, protocols, instruments, geo-spatial locations, specimens, samples, people (well as traditional articles) – and their interconnectivity. That is a lot of metadata love notes to manage, bundle up and move around. Notes written in different languages at different times by different folks, produced and hosted by different platforms, yet referring to each other, and building an integrated picture of a multi-part and multi-party investigation. We need a crate!
RO-Crate [3] is an open, community-driven, and lightweight approach to packaging research entities along with their metadata in a machine-readable manner. Following key principles - “just enough” and “developer and legacy friendliness - RO-Crate simplifies the process of making research outputs FAIR while also enhancing research reproducibility and citability. As a self-describing and unbounded “metadata middleware” framework RO-Crate shows that a little bit of packaging goes a long way to realise the goals of FAIR Digital Objects (FDO)[4], and to not just overcome platform diversity but celebrate it while retaining investigation contextual integrity.
In this talk I will present the why, and how Research Object packaging eases Metadata Collaboration using examples in big data and mixed object exchange, mixed object archiving and publishing, mass citation, and reproducibility. Some examples come from the HMC, others from EOSC, USA and Australia, and from different disciplines.
Metadata is a love note to the future, RO-Crate is the delivery package.
[1] https://helmholtz-metadaten.de/en
[2] Scott, Jason The Metadata Mania, http://ascii.textfiles.com/archives/3181, June 2011
[3] Soiland-Reyes, Stian et al. “Packaging Research Artefacts with RO-Crate”. Data Science, 2022; 5(2):97-138, DOI: 10.3233/DS-210053
[4] De Smedt K, Koureas D, Wittenburg P. “FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units”. Publications. 2020; 8(2):21. https://doi.org/10.3390/publications8020021
Research Software Sustainability takes a VillageCarole Goble
The Research Software Alliance (ReSA) and the Netherlands eScience Center hosted a two-day international workshop to set the future agenda for national and international funders to support sustainable research software.
As the importance of software in research has become increasingly apparent, so has the urgent need to sustain it. Funders can play a crucial role in this respect by ensuring structural support. Over the past few years, a variety of methods for sustaining research software have been explored, including improving and extending funding policies and instruments. During the workshop, funding organizations joined forces to explore how they can effectively contribute to making research software sustainable.
This keynote helped frame the discussion from the perspective of community involvement in research software sustainability.
https://future-of-research-software.org/
this talk is available at Goble, Carole. (2022, November 8). Research Software Sustainability takes a Village. International funders workshop, The Future of Research Software, Amsterdam, The Netherlands. Zenodo. https://doi.org/10.5281/zenodo.7304596
“Bioscience has emerged as a data-rich discipline, in a transformation that is spreading as widely now as molecular biology in the twentieth century. We look forward to supporting new research careers, where data are valued and shared widely, where new software is a natural part of Biology, and where re-analysis and modelling are as creative as experimentation in understanding the rules of life and their applications.” Prof Andrew Millar FRS, chair Expert Group UKRI-BBSRC Review of data-intensive bioscience 2020.
Indeed - biomedical science is knowledge work and knowledge turning - the turning of observation and hypothesis through experimentation, comparison, and analysis into new, pooled knowledge. Turns depend on the FAIR and Open flow and availability of data and methods for automated processing and reproducible results, and on a society of scientists coordinating and collaborating.
For the past 25 years I have worked on the social and technical challenges in digital infrastructure to support scientific collaboration, data and method sharing, and automate scientific processing. Big ideas I have been instrumental in – sharing and publishing high quality computational workflows, semantic web technologies in bioscience, ecosystems of Research Objects as the currency of scholarly knowledge, FAIR data principles - preached revolution to inspire but need nudges* to get traction.
I’ll talk about making good on Andrew’s quote: what I’m doing to nudge and where we need to do more. I’ll also talk about my experiences as a woman in a digital infrastructure and computer science over the past 40 years – and some nudging is needed there too.
*Thaler RH, Sunstein CR (2008) Nudge: Improving Decisions about Health, Wealth, and Happiness. Yale University Press. ISBN 978-0-14-311526-7. OCLC 791403664.
https://www.bsc.es/research-and-development/research-seminars/hybrid-bsc-rslife-sessionbioinfo4women-seminar-love-money-fame-nudge-enabling-data-intensive
Open Research: Manchester leading and learningCarole Goble
Open and FAIR science has an international momentum. Large scale communities are striving to make and manage the digital infrastructure needed for scientists to be open as possible, closed as necessary, as expected by the NIH, OECD, UNESCO and the EC. ELIXIR is such a research infrastructure in Europe for Life Sciences. This talk will highlight two of ELIXIR's Open Science resources built by Open Science communities to enable life science researchers to be open, and led by Manchester. And how can we learn from these and bring these practices to Manchester?
Launch: Manchester Office for Open Research, 4th April 2022
https://www.openresearch.manchester.ac.uk/
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.
How are we Faring with FAIR? (and what FAIR is not)Carole Goble
Keynote presented at the workshop FAIRe Data Infrastructures, 15 October 2020
https://www.gmds.de/aktivitaeten/medizinische-informatik/projektgruppenseiten/faire-dateninfrastrukturen-fuer-die-biomedizinische-informatik/workshop-2020/
Remarkably it was only in 2016 that the ‘FAIR Guiding Principles for scientific data management and stewardship’ appeared in Scientific Data. The paper was intended to launch a dialogue within the research and policy communities: to start a journey to wider accessibility and reusability of data and prepare for automation-readiness by supporting findability, accessibility, interoperability and reusability for machines. Many of the authors (including myself) came from biomedical and associated communities. The paper succeeded in its aim, at least at the policy, enterprise and professional data infrastructure level. Whether FAIR has impacted the researcher at the bench or bedside is open to doubt. It certainly inspired a great deal of activity, many projects, a lot of positioning of interests and raised awareness. COVID has injected impetus and urgency to the FAIR cause (good) and also highlighted its politicisation (not so good).
In this talk I’ll make some personal reflections on how we are faring with FAIR: as one of the original principles authors; as a participant in many current FAIR initiatives (particularly in the biomedical sector and for research objects other than data) and as a veteran of FAIR before we had the principles.
FAIRy stories: tales from building the FAIR Research CommonsCarole Goble
Plenary Lecture Presented at INCF Neuroinformatics 2019 https://www.neuroinformatics2019.org
Title: FAIRy stories: tales from building the FAIR Research Commons
Findable Accessable Interoperable Reusable. The “FAIR Principles” for research data, software, computational workflows, scripts, or any kind of Research Object is a mantra; a method; a meme; a myth; a mystery. For the past 15 years I have been working on FAIR in a range of projects and initiatives in the Life Sciences as we try to build the FAIR Research Commons. Some are top-down like the European Research Infrastructures ELIXIR, ISBE and IBISBA, and the NIH Data Commons. Some are bottom-up, supporting FAIR for investigator-led projects (FAIRDOM), biodiversity analytics (BioVel), and FAIR drug discovery (Open PHACTS, FAIRplus). Some have become movements, like Bioschemas, the Common Workflow Language and Research Objects. Others focus on cross-cutting approaches in reproducibility, computational workflows, metadata representation and scholarly sharing & publication. In this talk I will relate a series of FAIRy tales. Some of them are Grimm. There are villains and heroes. Some have happy endings; all have morals.
COMBINE 2019, EU-STANDS4PM, Heidelberg, Germany 18 July 2019
FAIR: Findable Accessable Interoperable Reusable. The “FAIR Principles” for research data, software, computational workflows, scripts, or any other kind of Research Object one can think of, is now a mantra; a method; a meme; a myth; a mystery. FAIR is about supporting and tracking the flow and availability of data across research organisations and the portability and sustainability of processing methods to enable transparent and reproducible results. All this is within the context of a bottom up society of collaborating (or burdened?) scientists, a top down collective of compliance-focused funders and policy makers and an in-the-middle posse of e-infrastructure providers.
Making the FAIR principles a reality is tricky. They are aspirations not standards. They are multi-dimensional and dependent on context such as the sensitivity and availability of the data and methods. We already see a jungle of projects, initiatives and programmes wrestling with the challenges. FAIR efforts have particularly focused on the “last mile” – “FAIRifying” destination community archive repositories and measuring their “compliance” to FAIR metrics (or less controversially “indicators”). But what about FAIR at the first mile, at source and how do we help Alice and Bob with their (secure) data management? If we tackle the FAIR first and last mile, what about the FAIR middle? What about FAIR beyond just data – like exchanging and reusing pipelines for precision medicine?
Since 2008 the FAIRDOM collaboration [1] has worked on FAIR asset management and the development of a FAIR asset Commons for multi-partner researcher projects [2], initially in the Systems Biology field. Since 2016 we have been working with the BioCompute Object Partnership [3] on standardising computational records of HTS precision medicine pipelines.
So, using our FAIRDOM and BioCompute Object binoculars let’s go on a FAIR safari! Let’s peruse the ecosystem, observe the different herds and reflect what where we are for FAIR personalised medicine.
References
[1] http://www.fair-dom.org
[2] http://www.fairdomhub.org
[3] http://www.biocomputeobject.org
Reproducible Research: how could Research Objects helpCarole Goble
Reproducible Research: how could Research Objects help, given at 21st Genomic Standards Consortium Meeting
Dates: May 20-23, 2019
https://press3.mcs.anl.gov/gensc/meetings/gsc21/
Reflections on a (slightly unusual) multi-disciplinary academic careerCarole Goble
Talk given at the School of Computer Science, The University of Manchester, UK Postgraduate Research Symposium 2019
the Carole Goble Doctoral Paper award was given for the first time
Being FAIR: Enabling Reproducible Data ScienceCarole Goble
Talk presented at Early Detection of Cancer Conference, OHSU, Portland, Oregon USA, 2-4 Oct 2018, http://earlydetectionresearch.com/ in the Data Science session
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
1. European Life Sciences Infrastructure for Biological
Information
www.elixir-europe.org
ELIXIR-UK
Carole Goble and Neil Hall
Heads of Node
2. ELIXIR-UK Node: a Network of 18 Organisations
Legal signatory
Node Coordination Office
Head of Node
Head of Node
Cardiff University, Earlham Institute, Edinburgh Genomics, Heriot
Watt University, Imperial College London, Newcastle University,
Rothamsted Research, The University of Birmingham, The University
of Liverpool, The University of Manchester, The University of
Nottingham, University of Bradford, University College London,
University of Cambridge, University of Dundee, University of
Edinburgh, University of Leicester, University of Oxford
Nœud ELIXIR-UK: un réseau de 18 organisations
3. ELIXIR UK Node
Established in 2013 with starter grant (2014-
2017) focused on networking and training
• Training Coordinators
• TeSS Training Portal
• The Carpentries
Expansion in 2016 to full range of Node
activities
• Reflecting the services, activities,
platforms and communities engaged in
Coordination office funded (2017-2020)
• Node Coordinator
• Communications and Networking funds
Neil Hall
Head of Node
Earlham Institute
Carole Goble
Head of Node
Manchester
Nicola Soranzo
TechCoordinator
Earlham Institute
Gabriella Rustici
TrainingCoordinator
Cambridge
Catherine Hunter
Node Coordinator,
Earlham Institute
4. ELIXIR UK Node
Neil Hall
Head of Node
Earlham Institute
Carole Goble
Head of Node
Manchester
Nicola Soranzo
TechCoordinator
Earlham Institute
Gabriella Rustici
TrainingCoordinator
Cambridge
Catherine Hunter
Node Coordinator,
Earlham Institute
Node
Funding
ELIXIR funds
Impl studies,
platform funding,
staff exchange
EU ELIXIR Awards
Competitively won
Investigator won
services and
activities
Node-Node
collaborations
In kind
The UK doesn’t
currently run
dedicated ESFRI
e-Infrastructure
call
5. UK funding landscape
• Coordination office funding
£750k (2 posts)
• Communications
• Workshops
• Meetings and Travel
• Administration of Elixir funds
• 15 node –services receiving ~
£6,000,000 from UKRI, EU
Wellcome Trust and NIH.
• No funding direct from node
£
£
Node Services
Meetings
Comms
Workshops
6. UK funding landscape
• Coordination office funding
£750k (2 posts)
• Communications
• Workshops
• Meetings and Travel
• Administration of Elixir funds
• 15 node –services receiving ~
£6,000,000 from UKRI, EU
Wellcome Trust and NIH.
• No funding direct from node
7. ELIXIR RELATED EU Projects
PROJECT INSTITUTIONS
EOSC-Pilot University of Manchester
University of Oxford
Heriot Watt University
EOSC-Life University of Manchester
University of Oxford
University of Cambridge
University of Dundee
ELIXIR-Excelerate University of Manchester
University of Oxford
University of Cambridge
University of Edinburgh
Heriot Watt University
Earlham institute
ELIXIR-Converge University of Manchester
University of Cambridge
CORBEL University of Manchester
IMI FAIRplus University of Manchester
University of Oxford
Heriot Watt University
EJP-RD University of Manchester
University of Cambridge
EOSC-Enhance University of Manchester
8. ELIXIR and the UK Landscape
The vatican
£8.7 Bn
Funding
£1 Bn
£0.6 Bn
24
research
intensive
universities
9. Policy Wrangling
Revisions to the OECD
Recommendation of the Council
concerning Access to Research
Data from Public Funding
10. UK e-Infrastructure for Life Science Landscape
Biological sciences, health and food themes
“Significant expansion of the UK node
of ELIXIR to support BioFAIR, a data
sustainability institute supporting the
coordination and development of UK
life science data”
11. ELIXIR-UK Serves
Membership ELIXIR UK
BioFAIR
a data sustainability
institute supporting
the coordination and
development of UK
life science data
BioFAIR Digital Object
Commons for UK Life
Science.
Mobilising and
coordinating UK life
science data
infrastructure
community
Accessing funding
and engagement
opportunities by UK
members
Developing ELIXIR
Communities
Executing the
Strategic Plan
Services SDPs
Platforms
Communities
Portals
Activities
EU Projects
Node-Node
cooperations
12. A Network
• Helping our members run and
participate in meetings
• Sponsoring meetings
• 2020 UK Bioinformatics
Conference to coincide with
UK All Hands
ELIXIRAll Hands 2018, Berlin
Biohackathon, November 2018, near Paris
ELIXIR UK All Hands, 2018, Birmingham
Dagstuhl Seminar FAIR e-
Infrastructures Nov 2018
14. Focus A lot of Node
co-operations
EBI are of course
strong partners
• Communities
• Services
• Interoperability
• FAIRification
• Markup
• Workflows
17. Highlight: 3DBioinfo
To develop the infrastructure for FAIR
structural and functional annotations
To create open resources for sharing,
integrating and benchmarking software
tools for modelling the proteome in 3D
To develop tools to Describe, Analyse,
Annotate, and Predict Nucleic Acid
Structures
To help develop models for protein-ligand
interactions
3DBioInfo Launch, Basel, 2018Christine Orengo, UCL
Increasing Interoperability between
ELIXIR Protein Structure and Sequence
Resources and Expanding these
Resources with 3D-Models of CATH
Domains, built by SWISS-MODEL
CATH protein structure
classification Core Data
Resource,
Jalview multiple sequence
alignment editing,
visualisation and analysis
tool
PHYRE2 protein structure
prediction
Co-led Commissioned Service:
18. The ELIXIR Node Services
UK developed Service Best Practice. 9 new services in review.
https://f1000research.com/articles/5-2894/v2
Dundee Resource for
SequenceAnalysis and
Structure Prediction
CDR
RIR
Portal
20. Highlight: The TeSS Training Portal https://tess.elixir-europe.org
ELIXIR training portal to aggregate events and training materials
77%
increase in
users
2018-2019
75
content
providers
284
Upcoming
events
10657
past
1328
materials
1K
users /
month
50:50
manual/auto
Born native of ELIXIR
21. The TeSS Training Portal in a Nutshell
automatically aggregate
training resources
link to registries
content embedded with widgets
in 3rd party sites
curation tools
22. Organising and Navigating Content
Concept Maps and Learning Paths
Experiments Funded
by Commissioned
services
Concept maps
Learning outcome templates
Generate learning paths
Relate to Service Bundles
23. Community Contributions for Content and Code,
and Wider uptake -> from start-up to maturity
Open Development
Framework
Metadata
processors
Scraper
development
Curation
Contributions
Embedded
widgets
Scale Contribution
Modularise, Packaging, Governance
Other communities. Around topics, communities,
organisations, geographical. CZI, EJP-RD, HDR-UK, ARDC, EOSC.
TeSS needs to be packaged, marketed, and supported properly
Content
User UX
Added value
24. TeSS, the UK Node and the ELIXIR Platform
a native ELIXIR infrastructure service
Changes in UK leadership
• Manchester -> Cambridge
Resources challenge
• 1.5 FTE dedicated development in
one organisation (4 people needed)
• Over dependence on Niall
• Lack resources to build UK base
National funding challenges
• Seen as an ELIXIR not UK service
• Incorporation into BioFAIR proposal
Resources for content curation
• Affects quality of service
UK Node
ELIXIR
Platform
Excelerate
Impl Studies
2014 2016 2019 2021
A native ELIXIR Infrastructure
Service to be collective
managed by all ELIXIR Nodes
25. Highlight: Interoperability …. Data, Tools
platform, impl studies and EU grants
FAIRification of data infrastructure
FAIRmetrics, capability models, processes
FAIR Cookbook
Bioschemas
With NL, DE, EBI, LU …
Data FAIRification
Workflows & Software
Workflow Registry
Containerisation, Galaxy
CommonWorkflow Language, GA4GH
Research Objects
FAIR Software Practices
Registries, portability, interoperability
With ES, BE, DE, FR, EBI, NL …
FAIRmetrics
26. Highlight: Interoperability …. Data, Tools
platform, impl studies and EU grants
FAIRification of data infrastructure
FAIRmetrics, capability models, processes
FAIR Cookbook
Bioschemas
With NL, DE, EBI, LU …
Data FAIRification
Workflows & Software
Workflow Registry
Containerisation, Galaxy
CommonWorkflow Language, GA4GH
Research Objects
FAIR Software Practices
Registries, portability, interoperability
With ES, BE, DE, FR, EBI, NL …
28. Highlight: Bioschemas
Exploiting schema.org for FAIRer Life Sciences resources
ELIXIR-UK direct the initiative & promote ResearchSchemas
Community initiative
Schema.org specs
Support software
Foster adoption and use
Find, register, index, search
resources
Resource mark up for tools
Metadata movement
between resources
Registry auto curation
Leveraging a de
facto widely
adopted standard
Alasdair Gray, HWU
32. Community Plant Sciences Genotype-Phenotype
Data Management and Validation Toolkit
FAIR data Analysis
Search engine
Metadata
Access
33. Serving the UK: BioFAIR
bringing together all our expertise for the UK
differentiated from EMBL-EBI
Federated
Digital Object Commons partnered
with national infrastructure
Integrated data services
and toolkits and training
Data sustainability institute
supporting the coordination
and development of UK life
science data
Data Management services and capability ->
ELIXIR CONVERGE
34. Serving the UK: BioFAIR
bringing together all our expertise for the UK
differentiated from EMBL-EBI
Recognition now that this is
needed
BBSRC Review of Data
Driven Bioscience
BBSRC Bioscience Big Ideas
Pipeline
UKRI “infrastructure
roadmap”
Brexit - every crisis is an
opportunity …
35. ELIXIR-UK
Navigating a fragmented national
landscape
Outstanding people and track record
Doing a lot on borrowed resources
Significant contributions to ELIXIR
And EOSC
Node-Node co-operations
BioFAIR
a data sustainability
institute supporting
the coordination and
development of UK
life science data
BioFAIR Digital Object
Commons for UK Life
Science.