Lecture provided at the 8th International Congress of Hymenopterists, Cuzco, Peru, July 23, 2014.
The lectures makes a case to join the bibligraphies and pdf of hymenoptera taxonomy literature on the Biodiersity Literature Repository / Zenodo
The document discusses how bio-ontologies and natural language processing can enable open science by facilitating structured knowledge representation and collaborative curation. It describes services provided by the National Center for Biomedical Ontology (NCBO) that allow use of ontologies for annotation, data aggregation, and accelerating the curation process. Several groups are highlighted that utilize NCBO services for applications such as clinical trial matching, specimen banking, and data summarization.
1) The document discusses EBI's efforts to facilitate semantic alignment of its resources through building ontologies and annotating data with ontologies.
2) It describes EBI's work developing ontologies like the Experiment Factor Ontology and using ontologies to enhance search, data visualization, and data integration.
3) The challenges of representing EBI data in RDF are discussed, and future directions are outlined that could make RDF deployment simpler and enable more interesting queries over EBI data.
The document discusses using ontologies and Schema.org properties to connect biomedical data to ontology terms and concepts. Over 200 biomedical ontologies are in active use by life science databases at EMBL-EBI. Schema.org properties like MedicalCode and CreativeWork can be used to mark up ontology terms, data resources, and their relationships. This would allow questions about which ontologies and terms are used in specific data, and enable richer searching and discovery across data and ontologies.
Next generation sequencing requires next generation publishing: the Biodivers...Vince Smith
Penev, L., Stoev, P., Komericki, A., Akkari, N., Li, S., Zhou, X., Edmunds, S., Hunter, C., Weigand, A., Porco, D., Zapparoli, M., Georgiev, T., Mietchen, D., Roberts, D., Smith, V. 2013. Next generation sequencing requires next generation publishing: the Biodiversity Data Journal published the first eukaryotic new species with a fully sequenced transcriptome, DNA barcode and microcomputed tomography. TDWG, Biodiversity Information Standards. Grand Hotel Mediterraneo Florence, Italy, 27 Oct - 1 Nov.
Research Objects: more than the sum of the partsCarole Goble
Workshop on Managing Digital Research Objects in an Expanding Science Ecosystem, 15 Nov 2017, Bethesda, USA
https://www.rd-alliance.org/managing-digital-research-objects-expanding-science-ecosystem
Research output is more than just the rhetorical narrative. The experimental methods, computational codes, data, algorithms, workflows, Standard Operating Procedures, samples and so on are the objects of research that enable reuse and reproduction of scientific experiments, and they too need to be examined and exchanged as research knowledge.
A first step is to think of Digital Research Objects as a broadening out to embrace these artefacts or assets of research. The next is to recognise that investigations use multiple, interlinked, evolving artefacts. Multiple datasets and multiple models support a study; each model is associated with datasets for construction, validation and prediction; an analytic pipeline has multiple codes and may be made up of nested sub-pipelines, and so on. Research Objects (http://researchobject.org/) is a framework by which the many, nested and contributed components of research can be packaged together in a systematic way, and their context, provenance and relationships richly described.
OBOPedia: An Encyclopaedia of Biology Using OBO OntologiesObopedia swat4ls-20...robertstevens65
A talk on OBOPedia (HTTP://www.obopedia.org.uk) given at Semantic Web Applicaitons and Tools for Life Sciences (SWAT4Ls) 2015 in cambridge, UK December 2015
The document discusses how bio-ontologies and natural language processing can enable open science by facilitating structured knowledge representation and collaborative curation. It describes services provided by the National Center for Biomedical Ontology (NCBO) that allow use of ontologies for annotation, data aggregation, and accelerating the curation process. Several groups are highlighted that utilize NCBO services for applications such as clinical trial matching, specimen banking, and data summarization.
1) The document discusses EBI's efforts to facilitate semantic alignment of its resources through building ontologies and annotating data with ontologies.
2) It describes EBI's work developing ontologies like the Experiment Factor Ontology and using ontologies to enhance search, data visualization, and data integration.
3) The challenges of representing EBI data in RDF are discussed, and future directions are outlined that could make RDF deployment simpler and enable more interesting queries over EBI data.
The document discusses using ontologies and Schema.org properties to connect biomedical data to ontology terms and concepts. Over 200 biomedical ontologies are in active use by life science databases at EMBL-EBI. Schema.org properties like MedicalCode and CreativeWork can be used to mark up ontology terms, data resources, and their relationships. This would allow questions about which ontologies and terms are used in specific data, and enable richer searching and discovery across data and ontologies.
Next generation sequencing requires next generation publishing: the Biodivers...Vince Smith
Penev, L., Stoev, P., Komericki, A., Akkari, N., Li, S., Zhou, X., Edmunds, S., Hunter, C., Weigand, A., Porco, D., Zapparoli, M., Georgiev, T., Mietchen, D., Roberts, D., Smith, V. 2013. Next generation sequencing requires next generation publishing: the Biodiversity Data Journal published the first eukaryotic new species with a fully sequenced transcriptome, DNA barcode and microcomputed tomography. TDWG, Biodiversity Information Standards. Grand Hotel Mediterraneo Florence, Italy, 27 Oct - 1 Nov.
Research Objects: more than the sum of the partsCarole Goble
Workshop on Managing Digital Research Objects in an Expanding Science Ecosystem, 15 Nov 2017, Bethesda, USA
https://www.rd-alliance.org/managing-digital-research-objects-expanding-science-ecosystem
Research output is more than just the rhetorical narrative. The experimental methods, computational codes, data, algorithms, workflows, Standard Operating Procedures, samples and so on are the objects of research that enable reuse and reproduction of scientific experiments, and they too need to be examined and exchanged as research knowledge.
A first step is to think of Digital Research Objects as a broadening out to embrace these artefacts or assets of research. The next is to recognise that investigations use multiple, interlinked, evolving artefacts. Multiple datasets and multiple models support a study; each model is associated with datasets for construction, validation and prediction; an analytic pipeline has multiple codes and may be made up of nested sub-pipelines, and so on. Research Objects (http://researchobject.org/) is a framework by which the many, nested and contributed components of research can be packaged together in a systematic way, and their context, provenance and relationships richly described.
OBOPedia: An Encyclopaedia of Biology Using OBO OntologiesObopedia swat4ls-20...robertstevens65
A talk on OBOPedia (HTTP://www.obopedia.org.uk) given at Semantic Web Applicaitons and Tools for Life Sciences (SWAT4Ls) 2015 in cambridge, UK December 2015
Findable Accessable Interoperable Reusable < data |models | SOPs | samples | articles| * >. FAIR is a mantra; a meme; a myth; a mystery; a moan. For the past 15 years I have been working on FAIR in a bunch of projects and initiatives in Life Science projects. Some are top-down like Life Science European Research Infrastructures ELIXIR and ISBE, and some are bottom-up, supporting research projects in Systems and Synthetic Biology (FAIRDOM), Biodiversity (BioVel), and Pharmacology (open PHACTS), for example. 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. Some have happy endings. Who are the villains and who are the heroes? What are the morals we can draw from these stories?
FAIRDOM - FAIR Asset management and sharing experiences in Systems and Synthe...Carole Goble
Over the past 5 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 and so forth. Don’t stop reading. Data management isn’t likely to win anyone a Nobel prize. But publications should be supported and accompanied by data, methods, procedures, etc. to assure reproducibility of results. Funding agencies expect data (and increasingly software) management retention and access plans as part of the proposal process for projects to be funded. 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 Biology demands the interlinking and exchange of assets and the systematic recording
of metadata for their interpretation.
The FAIR Guiding Principles for scientific data management and stewardship (http://www.nature.com/articles/sdata201618) has been an effective rallying-cry for EU and USA Research Infrastructures. FAIRDOM (Findable, Accessible, Interoperable, Reusable Data, Operations and Models) Initiative has 8 years of experience of asset sharing and data infrastructure ranging across European programmes (SysMO and EraSysAPP ERANets), national initiatives (de.NBI, German Virtual Liver Network, UK SynBio centres) and PI's labs. It aims to support Systems and Synthetic Biology researchers with data and model management, with an emphasis on standards smuggled in by stealth and sensitivity to asset sharing and credit anxiety.
This talk will use the FAIRDOM Initiative to discuss the FAIR management of data, SOPs, and models for Sys Bio, highlighting the challenges of and approaches to sharing, credit, citation and asset infrastructures in practice. I'll also highlight recent experiments in affecting sharing using behavioural interventions.
http://www.fair-dom.org
http://www.fairdomhub.org
http://www.seek4science.org
Presented at COMBINE 2016, Newcastle, 19 September.
http://co.mbine.org/events/COMBINE_2016
This document discusses the use and future of ontologies in biology. It makes three key points:
1) Ontologies are necessary for representing biological knowledge but are not sufficient on their own.
2) Ontology development needs to become more programmatic and automated to scale to the vast amount of biological data and knowledge.
3) Ontologies should be used to generate new conclusions and insights about biology, not just organize existing knowledge. More work is needed to enable reasoning over ontologies.
Keynote: SemSci 2017: Enabling Open Semantic Science
1st International Workshop co-located with ISWC 2017, October 2017, Vienna, Austria,
https://semsci.github.io/semSci2017/
Abstract
We have all grown up with the research article and article collections (let’s call them libraries) as the prime means of scientific discourse. But research output is more than just the rhetorical narrative. The experimental methods, computational codes, data, algorithms, workflows, Standard Operating Procedures, samples and so on are the objects of research that enable reuse and reproduction of scientific experiments, and they too need to be examined and exchanged as research knowledge.
We can think of “Research Objects” as different types and as packages all the components of an investigation. If we stop thinking of publishing papers and start thinking of releasing Research Objects (software), then scholar exchange is a new game: ROs and their content evolve; they are multi-authored and their authorship evolves; they are a mix of virtual and embedded, and so on.
But first, some baby steps before we get carried away with a new vision of scholarly communication. Many journals (e.g. eLife, F1000, Elsevier) are just figuring out how to package together the supplementary materials of a paper. Data catalogues are figuring out how to virtually package multiple datasets scattered across many repositories to keep the integrated experimental context.
Research Objects [1] (http://researchobject.org/) is a framework by which the many, nested and contributed components of research can be packaged together in a systematic way, and their context, provenance and relationships richly described. The brave new world of containerisation provides the containers and Linked Data provides the metadata framework for the container manifest construction and profiles. It’s not just theory, but also in practice with examples in Systems Biology modelling, Bioinformatics computational workflows, and Health Informatics data exchange. I’ll talk about why and how we got here, the framework and examples, and what we need to do.
[1] Sean Bechhofer, Iain Buchan, David De Roure, Paolo Missier, John Ainsworth, Jiten Bhagat, Philip Couch, Don Cruickshank, Mark Delderfield, Ian Dunlop, Matthew Gamble, Danius Michaelides, Stuart Owen, David Newman, Shoaib Sufi, Carole Goble, Why linked data is not enough for scientists, In Future Generation Computer Systems, Volume 29, Issue 2, 2013, Pages 599-611, ISSN 0167-739X, https://doi.org/10.1016/j.future.2011.08.004
Metadata and Semantics Research Conference, Manchester, UK 2015
Research Objects: why, what and how,
In practice the exchange, reuse and reproduction of scientific experiments is hard, dependent on bundling and exchanging the experimental methods, computational codes, data, algorithms, workflows and so on along with the narrative. These "Research Objects" are not fixed, just as research is not “finished”: codes fork, data is updated, algorithms are revised, workflows break, service updates are released. Neither should they be viewed just as second-class artifacts tethered to publications, but the focus of research outcomes in their own right: articles clustered around datasets, methods with citation profiles. Many funders and publishers have come to acknowledge this, moving to data sharing policies and provisioning e-infrastructure platforms. Many researchers recognise the importance of working with Research Objects. The term has become widespread. However. What is a Research Object? How do you mint one, exchange one, build a platform to support one, curate one? How do we introduce them in a lightweight way that platform developers can migrate to? What is the practical impact of a Research Object Commons on training, stewardship, scholarship, sharing? How do we address the scholarly and technological debt of making and maintaining Research Objects? Are there any examples
I’ll present our practical experiences of the why, what and how of Research Objects.
Publishing Germplasm Vocabularies as Linked DataValeria Pesce
What has already been published?
What may still be needed?
How to do it?
This presentation is a part of the 3rd Session of the 1st International e-Conference on Germplasm Data Interoperability https://sites.google.com/site/germplasminteroperability/
Short talk on Research Object and their use for reproducibility and publishing in the Systems Biology Commons Platform FAIRDOMHub, and the underlying software SEEK.
The MIAPA ontology: An annotation ontology for validating minimum metadata re...Hilmar Lapp
This document describes the MIAPA (Minimum Information About a Phylogenetic Analysis) ontology, which was developed to standardize the annotation and reporting of metadata for phylogenetic analyses. The MIAPA ontology reuses terms from existing ontologies and is designed according to OBO Foundry best practices. It provides a standard way to annotate key information about phylogenetic tree topologies, operational taxonomic units, branch lengths, character matrices, alignment and tree inference methods. The goal is to facilitate increased access to and reuse of phylogenetic data through consistent annotation of published trees according to the MIAPA standard.
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
This document discusses Research Objects (RO), which provide a framework for bundling, exchanging, and linking resources related to experiments in order to improve reproducibility. The RO framework uses unique identifiers, aggregation, and metadata to group related resources. Real-world examples of ROs include reviewed scientific papers, workflow runs, and Docker images. ROs can help make research fully FAIR (Findable, Accessible, Interoperable, Reusable). Tools and platforms like FAIRDOM, SEEK, and Figshare support the use of ROs.
Reproducibility, Research Objects and Reality, Leiden 2016Carole Goble
Presented at the Leiden Bioscience Lecture, 24 November 2016, Reproducibility, Research Objects and Reality
Over the past 5 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 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. It all sounds very laudable and straightforward. BUT…..
Reproducibility is a R* minefield, depending on whether you are testing for robustness (rerun), defence (repeat), certification (replicate), comparison (reproduce) or transferring between researchers (reuse). Different forms of "R" make different demands on the completeness, depth and portability of research. Sharing is another minefield raising concerns of credit and protection from sharp practices.
In practice the exchange, reuse and reproduction of scientific experiments is dependent on bundling and exchanging the experimental methods, computational codes, data, algorithms, workflows and so on along with the narrative. These "Research Objects" are not fixed, just as research is not “finished”: the codes fork, data is updated, algorithms are revised, workflows break, service updates are released. ResearchObject.org is an effort to systematically support more portable and reproducible research exchange
In this talk I will explore these issues in data-driven computational life sciences through the examples and stories from initiatives I am involved, and Leiden is involved in too including:
· FAIRDOM which has built a Commons for Systems and Synthetic Biology projects, with an emphasis on standards smuggled in by stealth and efforts to affecting sharing practices using behavioural interventions
· ELIXIR, the EU Research Data Infrastructure, and its efforts to exchange workflows
· Bioschemas.org, an ELIXIR-NIH-Google effort to support the finding of assets.
Being Reproducible: SSBSS Summer School 2017Carole Goble
Lecture 2:
Being Reproducible: Models, Research Objects and R* Brouhaha
Reproducibility is a R* minefield, depending on whether you are testing for robustness (rerun), defence (repeat), certification (replicate), comparison (reproduce) or transferring between researchers (reuse). Different forms of "R" make different demands on the completeness, depth and portability of research. Sharing is another minefield raising concerns of credit and protection from sharp practices.
In practice the exchange, reuse and reproduction of scientific experiments is dependent on bundling and exchanging the experimental methods, computational codes, data, algorithms, workflows and so on along with the narrative. These "Research Objects" are not fixed, just as research is not “finished”: the codes fork, data is updated, algorithms are revised, workflows break, service updates are released. ResearchObject.org is an effort to systematically support more portable and reproducible research exchange.
In this talk I will explore these issues in more depth using the FAIRDOM Platform and its support for reproducible modelling. The talk will cover initiatives and technical issues, and raise social and cultural challenges.
NSF Workshop Data and Software Citation, 6-7 June 2016, Boston USA, Software Panel
FIndable, Accessible, Interoperable, Reusable Software and Data Citation: Europe, Research Objects, and BioSchemas.org
FAIR Data, Operations and Model management for Systems Biology and Systems Me...Carole Goble
This document discusses the FAIRDOM consortium's efforts to promote FAIR (Findable, Accessible, Interoperable, Reusable) principles for managing data, operations, and models from systems biology and systems medicine projects. It outlines challenges in asset management for multi-partner, multi-disciplinary projects using multiple formats and repositories. FAIRDOM provides pillars of support including community actions, platforms/tools, and a public project commons to help address these challenges and better enable sharing, reuse, and reproducibility of research assets according to FAIR principles.
FAIR data and model management for systems biology.FAIRDOM
Written and presented by Carole Goble (University of Manchester) as part of Intelligent Systems for Molecular Biology (ISMB), Dublin. July 10th - 14th 2015.
Written and presented by Carole Goble (University of Manchester) as part of the Reproducible and Citable Data and Models Workshop in Warnemünde, Germany. September 14th - 16th 2015.
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/
Findable Accessable Interoperable Reusable < data |models | SOPs | samples | articles| * >. FAIR is a mantra; a meme; a myth; a mystery; a moan. For the past 15 years I have been working on FAIR in a bunch of projects and initiatives in Life Science projects. Some are top-down like Life Science European Research Infrastructures ELIXIR and ISBE, and some are bottom-up, supporting research projects in Systems and Synthetic Biology (FAIRDOM), Biodiversity (BioVel), and Pharmacology (open PHACTS), for example. 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. Some have happy endings. Who are the villains and who are the heroes? What are the morals we can draw from these stories?
FAIRDOM - FAIR Asset management and sharing experiences in Systems and Synthe...Carole Goble
Over the past 5 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 and so forth. Don’t stop reading. Data management isn’t likely to win anyone a Nobel prize. But publications should be supported and accompanied by data, methods, procedures, etc. to assure reproducibility of results. Funding agencies expect data (and increasingly software) management retention and access plans as part of the proposal process for projects to be funded. 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 Biology demands the interlinking and exchange of assets and the systematic recording
of metadata for their interpretation.
The FAIR Guiding Principles for scientific data management and stewardship (http://www.nature.com/articles/sdata201618) has been an effective rallying-cry for EU and USA Research Infrastructures. FAIRDOM (Findable, Accessible, Interoperable, Reusable Data, Operations and Models) Initiative has 8 years of experience of asset sharing and data infrastructure ranging across European programmes (SysMO and EraSysAPP ERANets), national initiatives (de.NBI, German Virtual Liver Network, UK SynBio centres) and PI's labs. It aims to support Systems and Synthetic Biology researchers with data and model management, with an emphasis on standards smuggled in by stealth and sensitivity to asset sharing and credit anxiety.
This talk will use the FAIRDOM Initiative to discuss the FAIR management of data, SOPs, and models for Sys Bio, highlighting the challenges of and approaches to sharing, credit, citation and asset infrastructures in practice. I'll also highlight recent experiments in affecting sharing using behavioural interventions.
http://www.fair-dom.org
http://www.fairdomhub.org
http://www.seek4science.org
Presented at COMBINE 2016, Newcastle, 19 September.
http://co.mbine.org/events/COMBINE_2016
This document discusses the use and future of ontologies in biology. It makes three key points:
1) Ontologies are necessary for representing biological knowledge but are not sufficient on their own.
2) Ontology development needs to become more programmatic and automated to scale to the vast amount of biological data and knowledge.
3) Ontologies should be used to generate new conclusions and insights about biology, not just organize existing knowledge. More work is needed to enable reasoning over ontologies.
Keynote: SemSci 2017: Enabling Open Semantic Science
1st International Workshop co-located with ISWC 2017, October 2017, Vienna, Austria,
https://semsci.github.io/semSci2017/
Abstract
We have all grown up with the research article and article collections (let’s call them libraries) as the prime means of scientific discourse. But research output is more than just the rhetorical narrative. The experimental methods, computational codes, data, algorithms, workflows, Standard Operating Procedures, samples and so on are the objects of research that enable reuse and reproduction of scientific experiments, and they too need to be examined and exchanged as research knowledge.
We can think of “Research Objects” as different types and as packages all the components of an investigation. If we stop thinking of publishing papers and start thinking of releasing Research Objects (software), then scholar exchange is a new game: ROs and their content evolve; they are multi-authored and their authorship evolves; they are a mix of virtual and embedded, and so on.
But first, some baby steps before we get carried away with a new vision of scholarly communication. Many journals (e.g. eLife, F1000, Elsevier) are just figuring out how to package together the supplementary materials of a paper. Data catalogues are figuring out how to virtually package multiple datasets scattered across many repositories to keep the integrated experimental context.
Research Objects [1] (http://researchobject.org/) is a framework by which the many, nested and contributed components of research can be packaged together in a systematic way, and their context, provenance and relationships richly described. The brave new world of containerisation provides the containers and Linked Data provides the metadata framework for the container manifest construction and profiles. It’s not just theory, but also in practice with examples in Systems Biology modelling, Bioinformatics computational workflows, and Health Informatics data exchange. I’ll talk about why and how we got here, the framework and examples, and what we need to do.
[1] Sean Bechhofer, Iain Buchan, David De Roure, Paolo Missier, John Ainsworth, Jiten Bhagat, Philip Couch, Don Cruickshank, Mark Delderfield, Ian Dunlop, Matthew Gamble, Danius Michaelides, Stuart Owen, David Newman, Shoaib Sufi, Carole Goble, Why linked data is not enough for scientists, In Future Generation Computer Systems, Volume 29, Issue 2, 2013, Pages 599-611, ISSN 0167-739X, https://doi.org/10.1016/j.future.2011.08.004
Metadata and Semantics Research Conference, Manchester, UK 2015
Research Objects: why, what and how,
In practice the exchange, reuse and reproduction of scientific experiments is hard, dependent on bundling and exchanging the experimental methods, computational codes, data, algorithms, workflows and so on along with the narrative. These "Research Objects" are not fixed, just as research is not “finished”: codes fork, data is updated, algorithms are revised, workflows break, service updates are released. Neither should they be viewed just as second-class artifacts tethered to publications, but the focus of research outcomes in their own right: articles clustered around datasets, methods with citation profiles. Many funders and publishers have come to acknowledge this, moving to data sharing policies and provisioning e-infrastructure platforms. Many researchers recognise the importance of working with Research Objects. The term has become widespread. However. What is a Research Object? How do you mint one, exchange one, build a platform to support one, curate one? How do we introduce them in a lightweight way that platform developers can migrate to? What is the practical impact of a Research Object Commons on training, stewardship, scholarship, sharing? How do we address the scholarly and technological debt of making and maintaining Research Objects? Are there any examples
I’ll present our practical experiences of the why, what and how of Research Objects.
Publishing Germplasm Vocabularies as Linked DataValeria Pesce
What has already been published?
What may still be needed?
How to do it?
This presentation is a part of the 3rd Session of the 1st International e-Conference on Germplasm Data Interoperability https://sites.google.com/site/germplasminteroperability/
Short talk on Research Object and their use for reproducibility and publishing in the Systems Biology Commons Platform FAIRDOMHub, and the underlying software SEEK.
The MIAPA ontology: An annotation ontology for validating minimum metadata re...Hilmar Lapp
This document describes the MIAPA (Minimum Information About a Phylogenetic Analysis) ontology, which was developed to standardize the annotation and reporting of metadata for phylogenetic analyses. The MIAPA ontology reuses terms from existing ontologies and is designed according to OBO Foundry best practices. It provides a standard way to annotate key information about phylogenetic tree topologies, operational taxonomic units, branch lengths, character matrices, alignment and tree inference methods. The goal is to facilitate increased access to and reuse of phylogenetic data through consistent annotation of published trees according to the MIAPA standard.
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
This document discusses Research Objects (RO), which provide a framework for bundling, exchanging, and linking resources related to experiments in order to improve reproducibility. The RO framework uses unique identifiers, aggregation, and metadata to group related resources. Real-world examples of ROs include reviewed scientific papers, workflow runs, and Docker images. ROs can help make research fully FAIR (Findable, Accessible, Interoperable, Reusable). Tools and platforms like FAIRDOM, SEEK, and Figshare support the use of ROs.
Reproducibility, Research Objects and Reality, Leiden 2016Carole Goble
Presented at the Leiden Bioscience Lecture, 24 November 2016, Reproducibility, Research Objects and Reality
Over the past 5 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 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. It all sounds very laudable and straightforward. BUT…..
Reproducibility is a R* minefield, depending on whether you are testing for robustness (rerun), defence (repeat), certification (replicate), comparison (reproduce) or transferring between researchers (reuse). Different forms of "R" make different demands on the completeness, depth and portability of research. Sharing is another minefield raising concerns of credit and protection from sharp practices.
In practice the exchange, reuse and reproduction of scientific experiments is dependent on bundling and exchanging the experimental methods, computational codes, data, algorithms, workflows and so on along with the narrative. These "Research Objects" are not fixed, just as research is not “finished”: the codes fork, data is updated, algorithms are revised, workflows break, service updates are released. ResearchObject.org is an effort to systematically support more portable and reproducible research exchange
In this talk I will explore these issues in data-driven computational life sciences through the examples and stories from initiatives I am involved, and Leiden is involved in too including:
· FAIRDOM which has built a Commons for Systems and Synthetic Biology projects, with an emphasis on standards smuggled in by stealth and efforts to affecting sharing practices using behavioural interventions
· ELIXIR, the EU Research Data Infrastructure, and its efforts to exchange workflows
· Bioschemas.org, an ELIXIR-NIH-Google effort to support the finding of assets.
Being Reproducible: SSBSS Summer School 2017Carole Goble
Lecture 2:
Being Reproducible: Models, Research Objects and R* Brouhaha
Reproducibility is a R* minefield, depending on whether you are testing for robustness (rerun), defence (repeat), certification (replicate), comparison (reproduce) or transferring between researchers (reuse). Different forms of "R" make different demands on the completeness, depth and portability of research. Sharing is another minefield raising concerns of credit and protection from sharp practices.
In practice the exchange, reuse and reproduction of scientific experiments is dependent on bundling and exchanging the experimental methods, computational codes, data, algorithms, workflows and so on along with the narrative. These "Research Objects" are not fixed, just as research is not “finished”: the codes fork, data is updated, algorithms are revised, workflows break, service updates are released. ResearchObject.org is an effort to systematically support more portable and reproducible research exchange.
In this talk I will explore these issues in more depth using the FAIRDOM Platform and its support for reproducible modelling. The talk will cover initiatives and technical issues, and raise social and cultural challenges.
NSF Workshop Data and Software Citation, 6-7 June 2016, Boston USA, Software Panel
FIndable, Accessible, Interoperable, Reusable Software and Data Citation: Europe, Research Objects, and BioSchemas.org
FAIR Data, Operations and Model management for Systems Biology and Systems Me...Carole Goble
This document discusses the FAIRDOM consortium's efforts to promote FAIR (Findable, Accessible, Interoperable, Reusable) principles for managing data, operations, and models from systems biology and systems medicine projects. It outlines challenges in asset management for multi-partner, multi-disciplinary projects using multiple formats and repositories. FAIRDOM provides pillars of support including community actions, platforms/tools, and a public project commons to help address these challenges and better enable sharing, reuse, and reproducibility of research assets according to FAIR principles.
FAIR data and model management for systems biology.FAIRDOM
Written and presented by Carole Goble (University of Manchester) as part of Intelligent Systems for Molecular Biology (ISMB), Dublin. July 10th - 14th 2015.
Written and presented by Carole Goble (University of Manchester) as part of the Reproducible and Citable Data and Models Workshop in Warnemünde, Germany. September 14th - 16th 2015.
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/
This document is a classification key that can be used to identify different types of living things. It asks a series of yes or no questions about observable characteristics and uses the answers to direct the user down different paths in the classification system until a specific category is reached, such as mammal, bird, fish, amphibian, reptile, mollusk, insect, or arachnid. The key was created by Dr. Sardharwalla in July 2011 to aid in biological classification.
The document is about a dichotomous key, which is a written tool used to identify plants and animals. It consists of a series of paired questions that leads the user down different paths through a sequence of choices until an identification is reached. Each choice directs the user to the next question couplet number to follow. Dichotomous keys break down classifications into a step-by-step process.
Taxonomic collection and identificationAftab Badshah
Biological collections are valuable for preserving extinct species and rare specimens. They allow researchers to verify original data and study specimens that are otherwise inaccessible. Effective collections involve sampling populations across species' ranges and variations, including larvae and parasites. Specimens are collected using various methods and preserved appropriately through methods like alcohol, stuffing, or formalin depending on the taxon. Proper long-term labeling with data like location, date, life stage, and collector is critical for research.
This document discusses taxonomic characters which are attributes used to classify organisms based on similarities and differences. It covers the importance of characters in classification, their characteristics, types including morphological, physiological, behavioral, ecological and geographic. It also discusses the role of characters in modern taxonomy, character weighting, and inadmissible characters that are excluded from classification like meaningless, logically correlated, partially correlated and invariant characters.
The document describes characteristics of microbes and how to create a dichotomous key to identify bacteria. It includes a table listing characteristics of 8 bacteria species. It then shows the dichotomous key developed from the table to identify the bacteria through a series of yes/no questions. The key begins by separating bacteria based on Gram stain, then asks about galactose fermentation, H2S production, and reaction in litmus milk to systematically identify the bacteria.
Biological collections preserve plant and animal specimens through various methods. Dry collections involve preserving specimens without liquid through rigidity or highlighting distinguishing features. Wet collections submerge specimens in liquid preservatives to maintain body form and soft tissues. Low-temperature collections maintain specimens' viability for analysis by storing at cold temperatures. Microscopy collections prepare specimens for examination under microscopes. Proper collection, preservation, cataloging and storage help museums maintain valuable reference materials.
This document discusses different types of taxonomic keys that can be used to identify biological entities like plants, animals, and microorganisms. Taxonomic keys present the user with a series of choices about characteristics that ultimately lead to the identification of an unknown specimen. The main types discussed are indented keys, simple bracket keys, simple non-bracket keys, pictorial keys, box-type keys, circular keys, and branching keys. Each key type has advantages and disadvantages depending on the group being identified and whether it will be used by specialists or non-specialists like field workers.
The document provides an overview of classification and taxonomy learning objectives, including:
1) Defining the binomial system of naming species and classifying organisms.
2) Describing the five main classes of organisms and their key features.
3) Using dichotomous keys to classify organisms based on observable features.
The document discusses the proper procedures for collecting, transporting, and processing microbiological specimens to accurately identify infectious agents, noting that specimens must be representative of the infection, collected and transported aseptically, and processed promptly in the laboratory to identify causative organisms and guide treatment. Close communication between clinicians and the microbiology lab is important to select the appropriate tests and properly interpret results.
The document discusses taxonomy, which is the classifying and organizing of living things. It covers the early work of Carl Linnaeus, considered the father of modern taxonomy, including his development of the hierarchical classification system and binomial nomenclature. It also outlines the six kingdoms of life - Archaebacteria, Eubacteria, Protista, Fungi, Plantae, and Animalia - describing key characteristics of each.
Lecture presented at the Journals Club of the Naturhistorisches Museum Bern, March 17, 2014.
"Towards an (European) Open Biodiversity Knowledge Management System"
This document summarizes a presentation about the Plazi Treatment Repository project. It discusses how Plazi aims to make over 1 million taxonomic treatments openly accessible by semantically enhancing and linking content from biodiversity literature. A major challenge is copyright restrictions on publications, which Plazi addresses by only including non-copyrighted content and material for internal use. The presentation argues for legal changes like mandatory research licenses to further remove barriers to information exchange.
FAO has developed several semantic technologies and ontologies to improve information sharing and interoperability across different knowledge domains, including AGROVOC, the Agricultural Ontology Service, ontologies for fisheries, crops, nutrition, and geopolitics. These projects use techniques such as concept mapping, multilingual support, and semantic search to facilitate knowledge organization and exchange.
Setting the Scene for ViBRANT – Strategy, Philosophy and Communicationvbrant
The document discusses the future of scientific publishing and open access. It envisions a future where publications are semantically marked up and linked to external data sources to enable advanced text mining and knowledge extraction. Treatments of species would be structured using XML to define content and be linked to identifiers, bibliographic metadata, and other sources. This would allow publications to be queried and analyzed by both humans and machines. Prospective publications could be semantically enhanced from the start, while tools are needed to mark up legacy literature. The goal is open access to scientific knowledge beyond traditional PDFs.
The document discusses the future of scientific publishing and open access to scientific literature. It envisions a future where publications are semantically marked up and linked to external data sources to enable advanced text mining and knowledge extraction. Treatments of species would be structured using XML to define content and be linked to identifiers, bibliographic metadata, and other sources. This would allow publications to be queried and analyzed by both humans and machines. Prospective publications could be semantically enhanced from the start, while tools are needed to mark up legacy literature. The goal is open access and dissemination of scientific findings funded by public resources.
The document discusses several "sins" or bad practices that are commonly seen in bioinformatics, including reinvention, lack of reuse, inconsistent naming schemes, and lack of collaboration and data sharing. It provides examples of these issues and argues that greater emphasis should be placed on standards, collaboration, and leveraging existing tools and data. The document also acknowledges that some reinvention may be necessary due to evolving technologies and unmet needs in the field.
The Seven Deadly Sins of BioinformaticsDuncan Hull
Keynote talk at Bioinformatics Open Source Conference (BOSC) Special Interest Group at the 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2007) in Vienna, July 2007 by Carole Goble, University of Manchester.
CDAO presentation.
The idea of the comparative analysis ontoloty has been presented worldwide, including: NESCent (USA), IGBMC (France), UFRJ (Brazil). Providing a semantic framework for evolutionary analysis in a high-throughtput way after the next and third generation sequencing is the way to approach evolutionary-based studies into genome-wide analysis. The darwinian core of reasoning also allows CDAO to be used with other entities.
This document discusses building an open biodiversity knowledge management system that can extract, store, and serve information on taxa in an interoperable way across kingdoms of life. It notes that the legacy literature contains over 200 million pages but data is incomplete and disconnected. The Pro-iBiosphere project aims to demonstrate how to markup taxon treatments to make them accessible and linkable. Pilots have marked up over 1,500 treatments of plants, fungi, bryophytes, insects and spiders. The document recommends standardizing markup and applying it prospectively to enhance semantic interoperability of biodiversity data.
pro-iBiosphere Towards Open Biodiversity Knowledge COOPEUS 2013millerjeremya
The document discusses the goals and approaches of the Pro-iBiosphere project, which aims to make taxonomic data more accessible and interoperable by linking literature to datasets. It outlines challenges around technical and semantic interoperability of taxonomic data. It also describes the prospective approach of extracting structured data from publications and distributing it to biodiversity databases, and the retrospective approach of extracting elements from existing literature to populate databases.
Can machines understand the scientific literaturepetermurrayrust
With over 5000 scientific articles per day we need machines to help us understand the content. This material is to be used at an interactive session for the Science Society at Trinity College Cambridge UK
Biodiversity informatics involves making biodiversity data accessible through digitization, standardization, and publishing. Biodiversity data is used for taxonomy, biogeography, endangered species monitoring, and more. Key challenges include resolving scientific names and data quality. Major organizations include GBIF, Global Names, and Canadensys which works to mobilize Canadian specimen records. Additional resources can be found through conferences, organizations, and online communities.
Pensoft is presenting Biodiversity Data Journal's Species Conservation Profile (SCP) - a streamlined workflow for collaborative authoring, peer-review and scholarly publication, serving the IUCN Red Data List
This document provides an overview of LOINC (Logical Observation Identifiers Names and Codes) presented by Daniel Vreeman. In 3 sentences: LOINC is a universal standard for identifying health measurements and observations that allows for data exchange between systems. It has over 60,000 codes covering laboratory and clinical observations. The LOINC community is open-source and has over 14,000 members from 145 countries contributing to its ongoing development and adoption worldwide.
The document discusses challenges related to the use of scientific names in biodiversity informatics. It outlines objectives for the Global Names Architecture (GNA) to address issues like name variations, synonyms, homonyms, and differing taxonomic views. The GNA aims to create a complete index of all scientific names linked to species information, reconciled to an authoritative nomenclatural dictionary. It also aims to provide multiple taxonomic classifications and lists that are openly accessible and can effectively organize species data to support discovery.
Franz et al ice 2016 addressing the name meaning drift challenge in open ende...taxonbytes
Presentation for the Symposium: Building the Biodiversity Knowledge Graph for Insects – Components, Progress, and Challenges; 2016 XXV International Congress of Entomology, Orlando, FL – September 26, 2016 (#ICE2016). See https://esa.confex.com/esa/ice2016/meetingapp.cgi/Session/24482
Similar to A Step Towards (From) Read to Write Access to Taxonomic Publications (20)
DOI and the Mitteilungen: communicating scientific results in the futureagosti
lecture presented at Ento.CH, Neuchâtel, Switzerland; March 4, 2016. Developing a scenario for the future of the Mitteilungen der Schweizerischen Entomologischen Gesellschaft into the direction of semantically enhanced publications.
Data Sharing Principles and Legal Interoperability for Essential Biodiversity...agosti
The document discusses principles of open data sharing and legal interoperability of research data. It provides summaries of the GEO Data Sharing Principles from 2005 and a proposed updated version from 2015. The principles advocate sharing data as open data by default without charge or reuse restrictions. Exceptions can be made for reasons of national security, endangered species protection, or other restrictions allowed by law. The document also summarizes proposed principles from RDA/CODATA on facilitating lawful access to research data while balancing various legal interests through transparent communication of rights.
Revolutionizing the Research on Ants through new Methods and Technologies: th...agosti
Invited lecture presented at the XXII Simpósio de Mirmecologia, Ilhéus, BA, Brazil, October 22, 2015. The title takes reference to the ant conference to create a standard protocol to measure and monitor ants - the manual has been published 2000 as "Ants: measuring and monitoring biodiversity" which has been close to 2500 times cited by followup papers - and with the preparation started in 1995 in Ilhéus. The focus is on open access, digital library, sharing of data, publishing and the sociology of myrmecology, and how the data could be used in project like EU-BON.
The document discusses Plazi's work on converting biodiversity literature into structured data through text mining and markup. Key points include:
- Plazi extracts scientific names, tables, references and geographic data from literature and converts it into semantically enriched text and RDF.
- Their pipelines currently have over 50,000 taxonomic treatments life and are providing data to databases like NCBI, GBIF and EOL.
- Future plans include collaborating with ContentMine for daily treatment extraction, releasing RDF and text mining versions 1.0, and expanding the biodiversity literature repository to 100,000 references.
Plazi's thrive to achive Tim Berners-Lee 5*data for biodiversity literature. Lecture from the Opendata.ch/2015 conference, July1, 2015, Berne, Switzerland http://opendata.ch/projects/opendata-ch2015-konferenz/
Plazi or the challenge to free biodiversity data caught in hundreds of millio...agosti
A call for participation of citizen scientists to help to convert the half billion of pages of biodiversity legacy literature into Linked Open Data, an imperative for conservation of the worlds declining biodiversity, but as much as a scientific frontier: How many species are there? Traditionally, citizen scientist plaid a decisive role in describing the Earth's biodiversity. Now the confront a paradoxical challenge that they do not have access to their published scientifc corpus and might have to launch into a second wave of discovery: This time in the printed record.
Lecture held at the "Opportunities and challenges for citizen scientists" workshop at the ETH Zurich, January 23, 2015
This document summarizes the Bouchout Declaration for Open Biodiversity Knowledge Management. The declaration encourages an overarching approach to open biodiversity knowledge management based on principles like open access, open licenses, attribution, infrastructure, registers, persistent identifiers, linked open data, development and business sustainability. It aims to foster free and open access to biodiversity data through policy developments and technical agreements.
Bouchout Declaration
Introduction to the Bouchout Declaration for Open Biodiversity Knowledge Management.
The declaration has been initiated by the Pro-iBiosphere consortium and the official launch will be on June 12, 2014 at the Bouchout castle at the Plantentuin Meise, Meise, Belgium.
This presentation has been given at the Swiss "Konservatorentagung 2014, Frauenfeld", May 23.2014
This document discusses a schema for describing and exchanging the content of taxonomic publications in a way that allows both human and machine access. It proposes using semantic markup like XML to tag elements in publications like names, descriptions, and references in a way that links related data across sources. This would allow content to be more accessible for tasks like data mining while maintaining context. The schema is part of ongoing work by Plazi to apply semantic markup to digitize existing publications and structure new ones for improved dissemination and reuse of taxonomic knowledge.
20110222 behesty monitoring and measuring biodiversityagosti
This document discusses various topics related to monitoring and measuring biodiversity on a global scale. It mentions several key organizations and initiatives, including the Earth Summit, IPBES, NCBI, GBIF, TDWG, and Darwin Core, that are involved with assessing global biodiversity patterns and developing standards for exchanging biodiversity data. The document emphasizes that monitoring biodiversity as a comparative science requires access to data, use of identification aids, metadata standards, networks to share information, and applying data to understand changes over space and time.
The document discusses making taxonomic literature openly accessible in digital format. It proposes marking up publications with XML tags to encode semantic information that allows machines to extract and link data. This would facilitate access to the estimated 100 million pages of existing literature as well as integration of new data. Key recommendations include adopting open access policies, understanding copyright, self-archiving publications, using structured formats like XML, and developing standards and infrastructure to support digitization and interoperability of biodiversity data.
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Authoring a personal GPT for your research and practice: How we created the Q...Leonel Morgado
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...AbdullaAlAsif1
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
ESPP presentation to EU Waste Water Network, 4th June 2024 “EU policies driving nutrient removal and recycling
and the revised UWWTD (Urban Waste Water Treatment Directive)”
9. Treatment
Treatment
publications or (more frequently) sections of
publications documenting the features or distribution
of a related group of organisms (called a “taxon”,
plural “taxa”) in ways adhering to highly formalized
conventions. Some of these are over a century old.
[Catapano, 2011]
21. All content in Plazi (34,000 treatments)
14,590 specimens
8900 plottable specimens from
1138 unique locations
22. 200,000,000+ printed pages
1,900,000 species described
20,000,000+ species treatments
17,000 new species per year
BUT: The data are hidden
Incomplete digitization
Publications are not
semantically enhanced
Collections are incomplete
Data is not linked
Most data are not open
Taxonomic publictationS
25. Conversion
Find the right mix of generic and domain specific solutions
Plazi
SRS
find scan «OCR» markup store
?
domain domaingeneric
Digitization and Markup Workflow:
$$$$ ?
26. Solution for the future
Publish semantically enhanced:
Journal of Hymenoptera Research
30. Solution
Support reliable and permanent open access to digital biodiversity
records
Create identifiers, link provide direct access to digital objects of
biodiversity literature, specimens, multimedia, genes, etc.
Ensure global interoperability and sharing of biodiversity data,
information and knowledge
Ongoing dialogue to refine the concept and implementation
As signatories, we encourage an overarching approach to Open Biodiversity
Knowledge Management which is based on the following fundamental
principles:
http://bouchoutdeclaration
40. Solution
ZENODO @CERN
ZENODO builds and operate a simple and innovative service that
enables researchers, scientists, EU projects and institutions to
share and showcase multidisciplinary research results (data and
publications) that are not part of the existing institutional or
subject-based repositories of the research communities.
Zenodo is the digital repository of CERN
Zenodo agreed to host and support the Biodiversity Literature
Repository
43. Solution
Services or what you get:
Wide access
Refindit
Refbank
Legal Issues
Archiving
Distribution of publications resolved
Your legacy literature is for everybody directly from
your publications accesible
44. Solution
Why don’t we assure that all the legacy taxonomic
literature is in the
Biodiversity Literature Repository?
45. The future
Why not assure that all the legacy taxonomic
literature is in the Biodiversity Literature
Repository?
Why not make our community the first that can
publish in its journal with all publications linked
to a digital copy?
46. The future
Why not assure that all the legacy taxonomic
literature is in the Biodiversity Literature
Repository?
Why not make our community the first that can
publish in its journal with all publications linked
to a digital copy?
47. Links
Links
Further reading: http://plazi.org/?q=plazi_publications
Catapano, 2011 (http://www.ncbi.nlm.nih.gov/books/NBK47081/)
Bouchout Declaration (http://bouchoutdeclaration.org)
Blue List (http://plazi.org/?q=blue_list)
Biodiversity Literature Repository (https://zenodo.org/collection/user-biosyslit
Zenodo (https://zenodo.org/about)
Refindit (http://refindit.org)
Refbank (http://refbank.org)
Pro-iBiosphere (http://pro-ibiosphere.eu/)
Introduction to persistent identifiers (http://wiki.pro-
ibiosphere.eu/wiki/Best_practices_for_stable_URIs)
Twitter
@plazi_treat; @bouchoutdec, @myrmoteras