Research Objects, SEEK and FAIRDOM

•Download as PPTX, PDF•

1 like•1,744 views

Short talk on Research Object and their use for reproducibility and publishing in the Systems Biology Commons Platform FAIRDOMHub, and the underlying software SEEK.

Science

Metadata objects – not necessarily encapsulated!
Platform Independent framework to Bundle, Port and Link
(scattered) resources, related experiments, and hold context
Container
Packaging:
Zip files, Docker images, BagIt, …
Catalogues & Commons Platforms:
FAIRDOM SEEK, STELAR eLab
Manifest
Metadata
Describes the aggregated
resources, their
annotations and their
provenance
Manifest

Manifest Metadata
Manifest Construction
• Identification – id, title, creator, status….
• Aggregates – list of ids/links to resources
• Annotations – list of annotations about resources
Manifest
Manifest Description
• Checklists – what should be there
• Provenance – where it came from
• Versioning – its evolution
• Dependencies – what else is needed
Manifest

Manifest Construction
Unique identifiers as
names for things.
doi, epic, orcid, purl, RII,
Identifiers.org
Mechanism of
aggregation to group
things together.
OAI-ORE
Metadata about those
things & how they relate
to each other.
W3C OADM
http://w3id.org/ro/

FAIR Manifest Descriptions: RO types
Content Annotation Profiles
Checklist
Provenance
Versioning
Dependencies
NISO-JATS
Dublin Core
EFO ISA
SBML
JERM
Gamble, Goble, Klyne, Zhao
MIM:A Minimum Information
Model vocabulary and framework
for Scientific Linked Data,
IEEE 8th Intl Conf on eScience ,
2012
SED-ML
SBOL
MIAPE

FAIRDOMHub Sys Bio Commons
https://doi.org/10.15490/seek.1.investigation.56

Aggregating Commons
Links into public resources
Integration with public
resources
Integration with
modelling tools
FAIRDOM Repositories
SOPs
models
data
Launch local
executables
Integration with lab tools
Integration with lab
management systems
and local file stores
Direct Upload
BiVes

RO Unzip
• Reproducibility
• Versioning
• Systematic and
extensible meta-
data collection
• Cross platform
exchange
• Publishing
Living Snapshot
https://doi.org/10.15490/seek.1.investigation.56
https://dx.doi.org/10.1111/febs.13237

Other Implementations
• COMBINE Archive +RO
• Workflows RO Bundle
• STELARAsthma eLabs
• Data Publishing
• ATLAS LHC Experiments
using CDE, Docker, improved manifests for
people

Links
• Researchobject.org
• Fair-dom.org
• Seek4science.org

What's hot

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.

FAIRy stories: tales from building the FAIR Research Commons

Carole Goble

The Research Object Initiative:Frameworks and Use Cases

Carole Goble

Reproducible Research: how could Research Objects help

Carole Goble

FAIR Software (and Data) Citation: Europe, Research Object Systems, Networks ...

Carole Goble

Project Website: http://www.researchobject.org/ researchobjects.org is a community project that has developed an approach to describe and package up all resources used as part of an investigation as Research Objects (RO’s). RO’s - provide two main features; a manifest - a consistent way to provide a well-typed, structured description of the resources used in an investigation; and a ‘bundle’ - a mechanism for packaging up manifests with resources as a single, publishable unit. RO’s therefore carry the research context of an experiment - data, software, standard operating procedures (SOPs), models etc - and gather together the components of an experiment so that they are findable, accessible, interoperable and reproducible (FAIR). RO’s combine software and data into an aggregative data structure consisting of well described reconstructable parts. RO’s have the potential to address a number of challenges pertinent to open research including: a) supporting interoperability between infrastructures by using ROs as a primary mechanism for exchange and publication b) supporting the evolution of research objects as a living collection, enabling provenance tracking c) providing the ability to pivot research object components (data, software, models) that are not restricted to the traditional publication. Here we present work towards the development and adoption of ROs: (i) A series of specifications and conventions, using community standards, for the RO manifest and RO bundles. (ii) Implementations of Java, Python and Ruby APIs and tooling against those specifications; (iii) Examples of representations of the RO models in various languages (e.g. JSON-LD, RDF, HTML).

Research Shared: researchobject.org

Norman Morrison

Reproducibility (and the R*) of Science: motivations, challenges and trends

Carole Goble

Presented at Digital Life 2018, Bergen, March 2018. In the Trust and Accountability session. In recent years we have seen a change in expectations for the management and availability of all the outcomes of research (models, data, SOPs, software etc) and for greater transparency and reproduciblity in the method of research. The “FAIR” (Findable, Accessible, Interoperable, Reusable) Guiding Principles for stewardship [1] have proved to be an effective rallying-cry for community groups and for policy makers. The FAIRDOM Initiative (FAIR Data Models Operations, http://www.fair-dom.org) supports Systems Biology research projects with their research data, methods and model management, with an emphasis on standards and sensitivity to asset sharing and credit anxiety. Our aim is a FAIR Research Commons that blends together the doing of research with the communication of research. The Platform has been installed by over 30 labs/projects and our public, centrally hosted FAIRDOMHub [2] supports the outcomes of 90+ projects. We are proud to support projects in Norway’s Digital Life programme. 2018 is our 10th anniversary. Over the past decade we learned a lot about trust between researchers, between researchers and platform developers and curators and between both these groups and funders. We have experienced the Tragedy of the Commons but also seen shifts in attitudes. In this talk we will use our experiences in FAIRDOM to explore the political, economic, social and technical, social practicalities of Trust. [1] Wilkinson et al (2016) The FAIR Guiding Principles for scientific data management and stewardship Scientific Data 3, doi:10.1038/sdata.2016.18 [2] Wolstencroft, et al (2016) FAIRDOMHub: a repository and collaboration environment for sharing systems biology research Nucleic Acids Research, 45(D1): D404-D407. DOI: 10.1093/nar/gkw1032

Trust and Accountability: experiences from the FAIRDOM Commons Initiative.

Carole 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.

Reproducibility, Research Objects and Reality, Leiden 2016

Carole 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

Being FAIR: FAIR data and model management SSBSS 2017 Summer School

Carole Goble

Making your data good enough for sharing.

FAIRDOM

Capturing the context: one small(ish step for modellers, one giant leap for m...

FAIRDOM

What is Reproducibility? The R* brouhaha (and how Research Objects can help)

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.

How are we Faring with FAIR? (and what FAIR is not)

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

FAIRDOM - FAIR Asset management and sharing experiences in Systems and Synthe...

Carole Goble

MultiScale Biology Network Springboard meeting, Nottingham, UK, 1 June 2015 FAIR Data and model management for Systems Biology 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. Yes, 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. And 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. Data and model management for the Systems Biology community is a multi-faceted one including: the development and adoption appropriate community standards (and the navigation of the standards maze); the sustaining of international public archives capable of servicing quantitative biology; and the development of the necessary tools and know-how for researchers within their own institutes so that they can steward their assets in a sustainable, coherent and credited manner while minimizing burden and maximising personal benefit. The FAIRDOM (Findable, Accessible, Interoperable, Reusable Data, Operations and Models) Initiative has grown out of several efforts in European programmes (SysMO and EraSysAPP ERANets and the ISBE ESRFI) and national initiatives (de.NBI, German Virtual Liver Network, SystemsX, UK SynBio centres). It aims to support Systems Biology researchers with data and model management, with an emphasis on standards smuggled in by stealth. This talk will use the FAIRDOM Initiative to discuss the FAIR management of data, SOPs, and models for Sys Bio, highlighting the challenges multi-scale biology presents. http://www.fair-dom.org http://www.fairdomhub.org http://www.seek4science.org

FAIR Data and Model Management for Systems Biology(and SOPs too!)

Carole Goble

The FAIRDOM Commons for Systems Biology

FAIRDOM

Citing data in research articles: principles, implementation, challenges - an...

FAIRDOM

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.

Being Reproducible: SSBSS Summer School 2017

Carole Goble

Being FAIR: Enabling Reproducible Data Science

Carole Goble

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

The Rhetoric of Research Objects

Carole Goble

What's hot (20)

FAIRy stories: tales from building the FAIR Research Commons

The Research Object Initiative:Frameworks and Use Cases

Reproducible Research: how could Research Objects help

FAIR Software (and Data) Citation: Europe, Research Object Systems, Networks ...

Research Shared: researchobject.org

Reproducibility (and the R*) of Science: motivations, challenges and trends

Trust and Accountability: experiences from the FAIRDOM Commons Initiative.

Reproducibility, Research Objects and Reality, Leiden 2016

Being FAIR: FAIR data and model management SSBSS 2017 Summer School

Making your data good enough for sharing.

Capturing the context: one small(ish step for modellers, one giant leap for m...

What is Reproducibility? The R* brouhaha (and how Research Objects can help)

How are we Faring with FAIR? (and what FAIR is not)

FAIRDOM - FAIR Asset management and sharing experiences in Systems and Synthe...

FAIR Data and Model Management for Systems Biology(and SOPs too!)

The FAIRDOM Commons for Systems Biology

Citing data in research articles: principles, implementation, challenges - an...

Being Reproducible: SSBSS Summer School 2017

Being FAIR: Enabling Reproducible Data Science

The Rhetoric of Research Objects

Similar to Research Objects, SEEK and FAIRDOM

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

RO-Crate: packaging metadata love notes into FAIR Digital Objects

Carole Goble

Opening up MOOCs for OER management on the Web of linked data

Gilbert Paquette

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.

Research Objects: more than the sum of the parts

Carole Goble

Linked Open Data Visualization

Laura Po

Union catalogandknowledge engineering for teldap

AAT Taiwan

Share: discovery: a focus on papers

lisld

LKG Editor Dev

Simeon Warner

Yde de Jong & Dave Roberts - ZooBank and EDIT: Towards a business model for Z...

ICZN

Libraries and Linked Data: Looking to the Future (3)

ALATechSource

ALIAOnline Practical Linked (Open) Data for Libraries, Archives & Museums

Jon Voss

dotte.ppt

qwerty309340

Research Objects in Scientific Publications

dgarijo

OER for repository managers

Nick Sheppard

Liberating Laboratory Data - Eureka

Stuart Chalk

20141112 courtot big_datasemwebontologies

Melanie Courtot

Linking Data, Linking People

fereiraJ

ELAG 2014, Workshop on Electronic Resource Management

LydiaU

Managing electronic resources has become a distinctive and important task for libraries in recent years. The diversity of resources, changing licensing policies and new business models of the publishers, consortial acquisition and modern web scale discovery technologies have turned the market place of scientific information into a complex and multidimensional construct. A state-of-the-art management of electronic resources is dependent on flexible data models and the capability to integrate most heterogeneous data sources. AMSL project presentation held on ERM Workshop @ ELAG 2014, Bath, UK

Developing an ERM System based on Linked Data (AMSL project presentation @ ER...

Björn Muschall

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

FAIR Workflows and Research Objects get a Workout

Carole Goble

Linked data 101: Getting Caught in the Semantic Web

Morgan Briles

Similar to Research Objects, SEEK and FAIRDOM (20)

RO-Crate: packaging metadata love notes into FAIR Digital Objects

Opening up MOOCs for OER management on the Web of linked data

Research Objects: more than the sum of the parts

Linked Open Data Visualization

Union catalogandknowledge engineering for teldap

Share: discovery: a focus on papers

LKG Editor Dev

Yde de Jong & Dave Roberts - ZooBank and EDIT: Towards a business model for Z...

Libraries and Linked Data: Looking to the Future (3)

ALIAOnline Practical Linked (Open) Data for Libraries, Archives & Museums

dotte.ppt

Research Objects in Scientific Publications

OER for repository managers

Liberating Laboratory Data - Eureka

20141112 courtot big_datasemwebontologies

Linking Data, Linking People

ELAG 2014, Workshop on Electronic Resource Management

Developing an ERM System based on Linked Data (AMSL project presentation @ ER...

FAIR Workflows and Research Objects get a Workout

Linked data 101: Getting Caught in the Semantic Web

More from 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.

The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...

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

Can’t Pay, Won’t Pay, Don’t Pay: Delivering open science, a Digital Research...

Carole 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

Research Software Sustainability takes a Village

Carole Goble

“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

Title: Love, Money, Fame, Nudge: Enabling Data-intensive BioScience through D...

Carole Goble

FAIR Computational Workflows

Carole 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/

Open Research: Manchester leading and learning

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.

RDMkit, a Research Data Management Toolkit. Built by the Community for the ...

Carole Goble

FAIR Computational Workflows

Carole Goble

FAIR Computational Workflows

Carole Goble

EOSC-Life Workflow Collaboratory

Carole Goble

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.

FAIR Computational Workflows

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.

FAIR Data Bridging from researcher data management to ELIXIR archives in the...

Carole Goble

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.

FAIR Computational Workflows

Carole 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

FAIRy stories: the FAIR Data principles in theory and in practice

Carole Goble

RO-Crate: A framework for packaging research products into FAIR Research Objects

Carole Goble

The swings and roundabouts of a decade of fun and games with Research Objects

Carole Goble

What is Reproducibility? The R* brouhaha and how Research Objects can help

Carole Goble

FAIR History and the Future

Carole Goble

ELIXIR UK Node presentation to the ELIXIR Board

Carole Goble

Reflections on a (slightly unusual) multi-disciplinary academic career

Carole Goble

More from Carole Goble (20)

The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...

Can’t Pay, Won’t Pay, Don’t Pay: Delivering open science, a Digital Research...

Research Software Sustainability takes a Village

Title: Love, Money, Fame, Nudge: Enabling Data-intensive BioScience through D...

FAIR Computational Workflows

Open Research: Manchester leading and learning

RDMkit, a Research Data Management Toolkit. Built by the Community for the ...

FAIR Computational Workflows

EOSC-Life Workflow Collaboratory

FAIR Computational Workflows

FAIR Data Bridging from researcher data management to ELIXIR archives in the...

FAIR Computational Workflows

FAIRy stories: the FAIR Data principles in theory and in practice

RO-Crate: A framework for packaging research products into FAIR Research Objects

The swings and roundabouts of a decade of fun and games with Research Objects

What is Reproducibility? The R* brouhaha and how Research Objects can help

FAIR History and the Future

ELIXIR UK Node presentation to the ELIXIR Board

Reflections on a (slightly unusual) multi-disciplinary academic career

Recently uploaded

SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx

RizalinePalanog2

Seismic Method Estimate velocity from seismic data.pptx

AlMamun560346

PSYCHOSOCIAL NEEDS. in nursing II sem pptx

Suji236384

The computation of anti-derivatives is just an in-tellectual challenge, we know how to take deriv-atives, but … can we invert the process? We call this Computing the indefinite integral . In the last presentation we have seen a few indefinite integrals (we called them bricks), but they did not include the anti-derivative of many functions! We are going to try and do better !

COMPUTING ANTI-DERIVATIVES(Integration by SUBSTITUTION)

AkefAfaneh2

GBSN - Biochemistry (Unit 1)

Areesha Ahmad

99992-vip-66834 📞Noida Sector 22 Noida Low price 100% genuine sexy VIP call girls are provided safe and secure service .call 📞,,24 hours 🕰️-- ✅100% gesnuine young RIYA SERVICE COMPANY ✔✔✔ ★ A-Level (5 star ) ★ Strip-tease ★ BBBJ (Bareback Blowjob) Receive advanced sexual techniques in different mode make their life more pleasurable. ★ Spending time in hotel rooms ★ BJ (Blowjob Without a Condom) ★ Completion (Oral to completion) ★ Covered (Covered blowjob Without a Condom) ★ DATING (Dinner At Night) ★ DSL (Dick Sucking Lips) ★ DT (Dining at the Toes English Spanking) ★ Doggie (Sex style from behind) ★ Duo (shot with two escorts; Threesome with the client) ★ S-GFE (Special Girl Friend Experience) ★ HJ (Hand Job) ★ Special Massage ★ O-Level (Oral sex) ★ Tour (International) ★ 69 (69 sex) ★ BJ (Blowjob With Condom) ★ GFE (Girl Friend Experience) ★ CBJ (Covered Blow Job; Oral sex with a condom _ LOW PRICE V I P MODEL FULL SAFE AND SECURE CALL MExxxs CALL ME

9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service

nishacall1

Bacterial Identification and Classifications

Areesha Ahmad

Justdial Call Girls In Indirapuram, Ghaziabad, 8800357707 Escorts Service Best High Class call girls Service Escorts Service in Home Hotel in Delhi NCR 24 Hours Available Service. We provide Super Class Hot and Sexy Indian Female Escorts Service, A to Z Body and Mind Satisfaction by Top Class Female Models in Delhi Gurgaon Noida NCR in Hotel 24hrs In Call and Out Call Service At Lowest Price. We Have Indian Punjabi Kashmiri Northeast Every Type Sexy Bold Beautiful Young Soft Cute Charming Female Escorts Available. Hygienic Full AC Neat and Clean Rooms Avail. In Hotel 24hrs in Delhi NCR

Justdial Call Girls In Indirapuram, Ghaziabad, 8800357707 Escorts Service

monikaservice1

Mustard, as a crop, is susceptible to a variety of pests that can affect its growth and yield. Here’s a rundown of some common pests that target mustard plants: Aphids: These small, sap-sucking insects can cause significant damage by feeding on the leaves and stems. Aphids also excrete a sticky substance known as honeydew, which can lead to the growth of sooty mold on the plants. Flea Beetles: These tiny beetles jump like fleas when disturbed and chew small holes in the leaves. They are particularly damaging in the early growth stages of the plant. Cabbage Loopers: The larvae of a type of moth, these caterpillars are known for their distinctive looping movement. They chew large holes in the leaves and can defoliate plants if present in large numbers. Diamondback Moth Larvae: Another caterpillar pest, these larvae chew small holes in the leaves and can cause extensive damage, especially when infestations are heavy. Whiteflies: These are tiny, winged insects that feed on plant sap and can quickly become a problem in greenhouse or close planting conditions. Like aphids, they also secrete honeydew. Cutworms: These are the larvae of certain types of moths and are known for cutting young plants at the stem base at ground level. They are most destructive during the night. Root Maggots: The larvae of root maggot flies, these pests attack the roots of mustard plants, causing wilting and potentially killing young plants. Harlequin Bugs: These are colorful stink bugs that suck the sap from mustard plant stems and leaves, causing the leaves to become stippled, wilt, and eventually die if the infestation is severe. Mustard Sawfly: The larvae of the mustard sawfly can cause considerable defoliation, as they feed voraciously on the leaves. Clubroot: Caused by a fungus-like organism, clubroot affects the roots, causing them to swell and distort. While technically a disease, it is often associated with pest management because controlling it involves similar preventative strategies. Control Measures: Managing pests in mustard involves a combination of cultural, biological, and chemical methods. Crop rotation, resistant varieties, timely sowing, maintaining plant health, and using natural predators like ladybugs and parasitic wasps can help keep pest populations under control. Chemical pesticides should be used as a last resort due to their potential impact on the environment and non-target species.

Pests of mustard_Identification_Management_Dr.UPR.pdf

PirithiRaju

Factory Acceptance Test( FAT).pptx .

Poonam Aher Patil

Call Girls In Safdarung Enclave Arjun Nagar Whatsapp +91 9654467111 Delhi ⛟ Open 24 Hrs, ☎ Booking Short 2000 Night 6000 ALL HOME/HOTEL SERVICE DOORSTEP SERVICE IN/CALL & OUT/CALL SERVICE WITH MANY OPTIONS AVAILABLE DELHI GURGAON & NOIDA SERVICE IN REASONABLE RATES FROM LOW TO HIGH PROFILE STAFF’S. Call Girl Number~24X7~Call Girl Services, New Delhi, Delhi OutCall Rate Call Girl Mahipalpur,Call Girl Connaught Place,Call Girl Nehru Place,Call Girl Chanakyapuri,Call Girl Paharganj,Call Girl Dhaula Kuan,Call Girl Moti Bagh,Call Girl Karol Bagh,Call Girl Greater Kailash,Call Girl Naraina, Call Girl Katwaria Sarai,Call Girl Janakpuri,Call Girl Kalkaji,Call Girl Lajpat Nagar,Call Girl Palam,Call Girl Malviya Nagar,Call Girl Mehrauli,Call Girl Govindpuri,Call Girl Sarojini Nagar ,Call Girl Neb Sarai,Call Girl South Ex,Call Girl Munirka,Call Girl Saket,Call Girl Chattarpur

9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000

Sapana Sha

Vip CALL GIRL IN Lonavala 9748763073❤CALL GIRLS IN ESCORT SERVICE❤CALL GIRL IN We are Providing :- ● – Private independent collage Going girls . ● – independent Models . ● – House Wife’s . ● – Private Independent House Wife’s ● – Corporate M.N.C Working Profiles . ● – Call Center Girls . ● – Live Band Girls . ●- Foreigners & Many More . Service type: 1.In call 2.out call 3. full Lip to Lip kiss 4.69 5.b-job without Condom 6. Hard Core sex & Much More. 7 Body to Body Touch 8 Kissing 9 Sucking Boobs and More 10 Enjoy by Hand 11 Relax By Oral 12 Sex with Happy Ending • In Call and Out Call Service • 3* 5* 7* Hotels Service • 24 Hours Available • Indian, Russian, Punjabi, Kashmiri Escorts • Real Models, College Girls, House Wife, Also Available • Short Time and Full Time Service Available • Hygienic Full AC Neat and Clean Rooms Avail. In Hotel 24 hours • Daily Escorts Staff Available • Minimum to Maximum Range Available.c

Vip profile Call Girls In Lonavala 9748763073 For Genuine Sex Service At Just...

Monika Rani

Unit5-Cloud.pptx for lpu course cse121 o

ManavSingh202607

GBSN - Microbiology (Unit 2)

Areesha Ahmad

Call Girls Alandi Call Me 7737669865 Budget Friendly No Advance Booking Booking Now open +91- 7737669865 Why you Choose Us- +91- 7737669865 HOT⇄ 7737669865 Mr ashu ji Call Mr ashu Ji +91- 7737669865 (V020524]N) 𝐇𝐨𝐭𝐞𝐥 𝐑𝐨𝐨𝐦𝐬 𝐈𝐧𝐜𝐥𝐮𝐝𝐢𝐧𝐠 𝐑𝐚𝐭𝐞 𝐒𝐡𝐨𝐭𝐬/𝐇𝐨𝐮𝐫𝐲🆓 .█▬█⓿▀█▀ 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 𝐆𝐈𝐑𝐋 𝐕𝐈𝐏 𝐄𝐒𝐂𝐎𝐑𝐓 Hello Guys ! High Profiles young Beauties and Good Looking standard Profiles Available , Enquire Now if you are interested in Hifi Service and want to get connect with someone who can understand your needs. Service offers you the most beautiful High Profile sexy independent female Escorts in genuine ✔✔✔ To enjoy with hot and sexy girls ✔✔✔ ★providing:- • Models • vip Models • Russian Models

Call Girls Alandi Call Me 7737669865 Budget Friendly No Advance Booking

roncy bisnoi

Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...

Silpa

Context. WASP-76 b has been a recurrent subject of study since the detection of a signature in high-resolution transit spectroscopy data indicating an asymmetry between the two limbs of the planet. The existence of this asymmetric signature has been confirmed by multiple studies, but its physical origin is still under debate. In addition, it contrasts with the absence of asymmetry reported in the infrared (IR) phase curve. Aims. We provide a more comprehensive dataset of WASP-76 b with the goal of drawing a complete view of the physical processes at work in this atmosphere. In particular, we attempt to reconcile visible high-resolution transit spectroscopy data and IR broadband phase curves. Methods. We gathered 3 phase curves, 20 occultations, and 6 transits for WASP-76 b in the visible with the CHEOPS space telescope. We also report the analysis of three unpublished sectors observed by the TESS space telescope (also in the visible), which represents 34 phase curves. Results. WASP-76 b displays an occultation of 260±11 and 152±10 ppm in TESS and CHEOPS bandpasses respectively. Depending on the composition assumed for the atmosphere and the data reduction used for the IR data, we derived geometric albedo estimates that range from 0.05 ± 0.023 to 0.146 ± 0.013 and from <0.13 to 0.189 ± 0.017 in the CHEOPS and TESS bandpasses, respectively. As expected from the IR phase curves, a low-order model of the phase curves does not yield any detectable asymmetry in the visible either. However, an empirical model allowing for sharper phase curve variations offers a hint of a flux excess before the occultation, with an amplitude of ∼40 ppm, an orbital offset of ∼−30◦ , and a width of ∼20◦ . We also constrained the orbital eccentricity of WASP-76 b to a value lower than 0.0067, with a 99.7% confidence level. This result contradicts earlier proposed scenarios aimed at explaining the asymmetry observed in high-resolution transit spectroscopy. Conclusions. In light of these findings, we hypothesise that WASP-76 b could have night-side clouds that extend predominantly towards its eastern limb. At this limb, the clouds would be associated with spherical droplets or spherically shaped aerosols of an unknown species, which would be responsible for a glory effect in the visible phase curves.

Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b

Sérgio Sacani

Chemical Tests; flame test, positive and negative ions test Edexcel Internati...

ssuser79fe74

IDENTIFICATION OF THE LIVING- forensic medicine

sherlingomez2

Forensic Biology & Its biological significance.pdf

rohankumarsinghrore1

Recently uploaded (20)

SCIENCE-4-QUARTER4-WEEK-4-PPT-1 (1).pptx

Seismic Method Estimate velocity from seismic data.pptx

PSYCHOSOCIAL NEEDS. in nursing II sem pptx

COMPUTING ANTI-DERIVATIVES(Integration by SUBSTITUTION)

GBSN - Biochemistry (Unit 1)

9999266834 Call Girls In Noida Sector 22 (Delhi) Call Girl Service

Bacterial Identification and Classifications

Justdial Call Girls In Indirapuram, Ghaziabad, 8800357707 Escorts Service

Pests of mustard_Identification_Management_Dr.UPR.pdf

Factory Acceptance Test( FAT).pptx .

9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000

Vip profile Call Girls In Lonavala 9748763073 For Genuine Sex Service At Just...

Unit5-Cloud.pptx for lpu course cse121 o

GBSN - Microbiology (Unit 2)

Call Girls Alandi Call Me 7737669865 Budget Friendly No Advance Booking

Locating and isolating a gene, FISH, GISH, Chromosome walking and jumping, te...

Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b

Chemical Tests; flame test, positive and negative ions test Edexcel Internati...

IDENTIFICATION OF THE LIVING- forensic medicine

Forensic Biology & Its biological significance.pdf

Research Objects, SEEK and FAIRDOM

1. Research Objects, SEEK4Science and FAIRDOM ProfessorCarole Goble CBE FREng FBCS The University of Manchester, UK The Software Sustainability Institute, UK carole.goble@manchester.ac.uk researchobject.org Schloss Dagstuhl Seminar 16041 Reproducibility of Data-Oriented Experiments in e-Science, 25-29 January 2016

2. Metadata objects – not necessarily encapsulated! Platform Independent framework to Bundle, Port and Link (scattered) resources, related experiments, and hold context Container Packaging: Zip files, Docker images, BagIt, … Catalogues & Commons Platforms: FAIRDOM SEEK, STELAR eLab Manifest Metadata Describes the aggregated resources, their annotations and their provenance Manifest

3. Manifest Metadata Manifest Construction • Identification – id, title, creator, status…. • Aggregates – list of ids/links to resources • Annotations – list of annotations about resources Manifest Manifest Description • Checklists – what should be there • Provenance – where it came from • Versioning – its evolution • Dependencies – what else is needed Manifest

4. Manifest Construction Unique identifiers as names for things. doi, epic, orcid, purl, RII, Identifiers.org Mechanism of aggregation to group things together. OAI-ORE Metadata about those things & how they relate to each other. W3C OADM http://w3id.org/ro/

5. FAIR Manifest Descriptions: RO types Content Annotation Profiles Checklist Provenance Versioning Dependencies NISO-JATS Dublin Core EFO ISA SBML JERM Gamble, Goble, Klyne, Zhao MIM:A Minimum Information Model vocabulary and framework for Scientific Linked Data, IEEE 8th Intl Conf on eScience , 2012 SED-ML SBOL MIAPE

6. FAIRDOMHub Sys Bio Commons https://doi.org/10.15490/seek.1.investigation.56

7. Aggregating Commons Links into public resources Integration with public resources Integration with modelling tools FAIRDOM Repositories SOPs models data Launch local executables Integration with lab tools Integration with lab management systems and local file stores Direct Upload BiVes

8. RO Unzip • Reproducibility • Versioning • Systematic and extensible metadata collection • Cross platform exchange • Publishing Living Snapshot https://doi.org/10.15490/seek.1.investigation.56 https://dx.doi.org/10.1111/febs.13237

10. SEEK Demo Video

11.

12. Other Implementations • COMBINE Archive +RO • Workflows RO Bundle • STELARAsthma eLabs • Data Publishing • ATLAS LHC Experiments using CDE, Docker, improved manifests for people

13. Links • Researchobject.org • Fair-dom.org • Seek4science.org

Editor's Notes

Research Objects: why, what and how, Examples, challengesIn 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.
Scattered Assets across silos Access, Interoperate, Reuse
Bridge and overlap between execution environment and publishing environment
Vagrant BagIt is a hierarchical file packaging format designed to support disk-based storage and network transfer of arbitrary digital content. A "bag" consists of a "payload" (the arbitrary content) and "tags", which are metadata files intended to document the storage and transfer of the bag. A required tag file contains a manifest listing every file in the payload together with its corresponding checksum. The name, BagIt, is inspired by the "enclose and deposit" method,[1] sometimes referred to as "bag it and tag it“ ReproZip is another packaging system Packaging – physical and logical containers Open Archives Initiation Object Reuse and Exchange (OAI ORE) is a standard for describing aggregations of web resources http://www.openarchives.org/ore/ Uses a Resource Map to describe the aggregated resources Proxies allow for statements about the resources within the aggregation Capturing context and viewpoints Several concrete serialisations RDF/XML, Atom, RDFa Open Annotation specification is a community developed data model for annotation of web resources http://www.openannotation.org/spec/core/ Developed by the W3C Open Annotation Community Group Allows for “stand-off” annotations Annotation as a first class citizen Developed to fit with Web Architecture How do you make a research object? Well, gather your resources, describe them in the manifest. Different types of Containers can be used to transfer and package the Research Object; The Research Object Bundle is a structured ZIP file format… but more specific and more general formats are also used, such a Docker images (a bit low-level, capturing the whole execution environment) BagIt (a digital archiving format that is commonly used by libraries), or Simply existing Web resources (which may be subject to change). You can register and archive research object in domain-specific repositories like FAIRDOM’s SEEK (system biology models), FARR Commons CKAN (public health medical data), technology-specific repositories (myExperiment for workflow-centric workflows), or generic data repositories you probably have already heard of, like Zenodo and Figshare.
Packaging – physical and logical containers Open Archives Initiation Object Reuse and Exchange (OAI ORE) is a standard for describing aggregations of web resources http://www.openarchives.org/ore/ Uses a Resource Map to describe the aggregated resources Proxies allow for statements about the resources within the aggregation Capturing context and viewpoints Several concrete serialisations RDF/XML, Atom, RDFa Open Annotation specification is a community developed data model for annotation of web resources http://www.openannotation.org/spec/core/ Developed by the W3C Open Annotation Community Group Allows for “stand-off” annotations Annotation as a first class citizen Developed to fit with Web Architecture
Pericles could be looked at – for preservation. Each RO adheres to a profile; Core profiles are citation – e.g. NISO-JATS spec Library: Dublin Core Application Profile
It works as aggregated asset manager, allowing storage on SEEK, or linking assets from disparate databases.
Export as RO Model, Data, SOP, Parameters Freezing the whole ISA for an investigation would be too restrictive and impractical. Changing an investigation could be as subtle as uploading a new version of a data file that is associated with an assay related to the investigation. So the concept of versioning for an Investigation gets quite complicated. At the same time, it is important that the DOI should be able to point to the investigation in the state it was in at the time it was published and linked to the DOI. To solve this, we have been implementing the construction of Research Objects for investigations, which can be used to create a snapshot of the investigation and all its parts at a specific time. It is also a digital object that can be deposited outside of SEEK.
RO Query
Vagrant – the automation tool for docker Docker “Github” Using their own tools One-command click repeatability

Research Objects, SEEK and FAIRDOM

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Research Objects, SEEK and FAIRDOM

Similar to Research Objects, SEEK and FAIRDOM (20)

More from Carole Goble

More from Carole Goble (20)

Recently uploaded

Recently uploaded (20)

Research Objects, SEEK and FAIRDOM

Editor's Notes