Semantic Web Adoption
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The document discusses the adoption of semantic web technologies. It notes that while tools and specifications have matured, applications are now coming to the forefront. It provides examples of semantic web deployments in various domains like digital libraries, eGovernment, healthcare and by major companies. Real-world applications include data integration, intelligent portals and knowledge management systems. Overall adoption is increasing but skills and training remain obstacles.
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ChemSpider was developed with the intention of aggregating and indexing available sources of chemical structures and their associated information into a single searchable repository and making it available to everybody, at no charge. There are many tens of chemical structure databases such as literature data, chemical vendor catalogs, molecular properties, environmental data, toxicity data, analytical data etc. and no single way to search across them. Despite the diversity of databases available online their inherent quality, accuracy and completeness is lacking in many regards. ChemSpider was established to provide a platform whereby the chemistry community could contribute to cleaning up the data, improving the quality of data online and expanding the information available to include data such as reaction syntheses, analytical data and experimental properties. ChemSpider has now grown into a database of over 20 million chemical substances integrated with over 300 disparate data sources, many of these directly supporting the Life Sciences. This presentation will provide an overview of our efforts to improve the quality of data online, to provide a foundation for the semantic web for chemistry and to provide access to a set online tools and services to support access to these data. I will also discuss how ChemSpider is being used to enhance Semantic Publishing in Chemistry at RSC.
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RSC ChemSpider -- Managing and Integrating Chemistry on the Internet to Build...
RSC ChemSpider -- Managing and Integrating Chemistry on the Internet to Build...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The increasing availability of free and open access resources for scientists on the internet presents us with a revolution in data availability. The Royal Society of Chemistry hosts ChemSpider, a free access website for chemists built with the intention of building community for chemists (http://www.chemspider.com/).
ChemSpider is an aggregator of chemistry related information, at present over 20 million unique chemical entities linked out to over 300 separate data sources, ChemSpider has taken on the task of both robotically and manually curating publicly available data sources. It is also a public deposition platform where chemists can deposit their own data including novel structures, analytical data, synthesis procedures and host data associated with the growing activities associated with Open Notebook Science.
This presentation will examine chemistry on the internet, the dubious quality of what is available and how the ChemSpider crowdsourced curation platform is fast becoming one of the centralized hubs for resourcing information about chemical entities.
We will also review our efforts to provide free resources for synthesis procedures, spectral data and structure-based searching of the chemistry literature and how chemists can contribute directly to each of these projects.
Applied semantic technology and linked data
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eScience Resources for the Chemistry Community from the Royal Society of Chem...
eScience Resources for the Chemistry Community from the Royal Society of Chem...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Our access to scientific information has changed in ways that were hardly imagined even by the early pioneers of the internet. The immense quantities of data and the array of tools available to search and analyze online content continues to expand while the pace of change does not appear to be slowing. ChemSpider is one of the chemistry community’s primary online public compound databases. Containing tens of millions of chemical compounds and its associated data ChemSpider serves data tens of thousands of chemists every day and it serves as the foundation for many important international projects to integrate chemistry and biology data, facilitate drug discovery efforts and help to identify new chemicals from under the ocean. This presentation will provide an overview of the expanding reach of the ChemSpider platform and the nature of the solutions that it helps to enable. We will also discuss the possibilities it offers in the domain of crowdsourcing and open data sharing. The future of scientific information and communication will be underpinned by these efforts, influenced by increasing participation from the scientific community and facilitated collaboration and ultimately accelerate scientific progress.ChemSpider – A Platform to Gather, Host and Integrate Structure Based Data Ac...
ChemSpider – A Platform to Gather, Host and Integrate Structure Based Data Ac...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
ChemSpider was developed with the intention of aggregating and indexing available sources of chemical structures and their associated information into a single searchable repository and making it available to everybody, at no charge. There are many tens of chemical structure databases such as literature data, chemical vendor catalogs, molecular properties, environmental data, toxicity data, analytical data etc. and no single way to search across them. Despite the diversity of databases available online their inherent quality, accuracy and completeness is lacking in many regards. ChemSpider was established to provide a platform whereby the chemistry community could contribute to cleaning up the data, improving the quality of data online and expanding the information available to include data such as reaction syntheses, analytical data and experimental properties. ChemSpider has now grown into a database of well over 20 million chemical substances integrated with over 300 disparate data sources, many of these directly supporting the Life Sciences. This presentation will provide an overview of our efforts to improve the quality of data online, to provide a foundation for the semantic web for chemistry and to provide access to a set online tools and services to support access to these data. I will also discuss how ChemSpider is being used to enhance Semantic Publishing in Chemistry at RSC. Towards FAIR principles for research software @ FAIR Software Session, Nation...
Slides of a presentation about our paper "Towards FAIR Principles for Research Software" (https://doi.org/10.3233/DS-190026) that I gave at the Dutch National eScience Symposium 2019 in Amsterdam (https://www.esciencesymposium2019.nl/).
Abstract:
The FAIR Guiding Principles, published in 2016, aim to improve the findability, accessibility, interoperability and reusability of digital research objects for both humans and machines. Until now the FAIR principles have been mostly applied to research data. The ideas behind these principles are, however, also directly relevant to research software. Hence there is a distinct need to explore how the FAIR principles can be applied to software. In this work, we aim to summarize the current status of the debate around FAIR and software, as basis for the development of community-agreed principles for FAIR research software in the future. We discuss what makes software different from data with regard to the application of the FAIR principles, and which desired characteristics of research software go beyond FAIR. Then we present an analysis of where the existing principles can directly be applied to software, where they need to be adapted or reinterpreted, and where the definition of additional principles is required. Here interoperability has proven to be the most challenging principle, calling for particular attention in future discussions. Finally, we outline next steps on the way towards definite FAIR principles for research software.
FAIR Computational Workflows
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.
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http://repscience2016.research-infrastructures.eu/
Improving online chemistry one structure at a time
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RSC|ChemSpider is one of the world’s largest online resources for chemistry related data and services. Developed with the intention of delivering access to structure-based chemistry data via the internet the ChemSpider platform hosts over 26 million unique chemical compounds aggregated from over 400 data sources and provides an environment for the community to both annotate and curate these existing data as well as deposit new data to the system. The search system delivers flexible querying capabilities together with links to external sites for publication and patent data. ChemSpider has spawned a number of projects include ChemSpider SyntheticPages for hosting openly peer-reviewed chemical synthesis articles. This presentation will review the present capabilities of the ChemSpider system providing direct examples of how to use the system to source high quality data of value to pharmaceutical companies. We will discuss some of the challenges associated with validating data quality, examine how ChemSpider is a part of the semantic web for chemistry and investigate approaches to using ChemSpider integrated to analytical instrumentation.What's hot (20)
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Let’s go on a FAIR safari!
COMBINE 2019, EU-STANDS4PM, Heidelberg, Germany 18 July 2019
FAIR: Findable Accessable Interoperable Reusable. The “FAIR Principles” for research data, software, computational workflows, scripts, or any other kind of Research Object one can think of, is now a mantra; a method; a meme; a myth; a mystery. FAIR is about supporting and tracking the flow and availability of data across research organisations and the portability and sustainability of processing methods to enable transparent and reproducible results. All this is within the context of a bottom up society of collaborating (or burdened?) scientists, a top down collective of compliance-focused funders and policy makers and an in-the-middle posse of e-infrastructure providers.
Making the FAIR principles a reality is tricky. They are aspirations not standards. They are multi-dimensional and dependent on context such as the sensitivity and availability of the data and methods. We already see a jungle of projects, initiatives and programmes wrestling with the challenges. FAIR efforts have particularly focused on the “last mile” – “FAIRifying” destination community archive repositories and measuring their “compliance” to FAIR metrics (or less controversially “indicators”). But what about FAIR at the first mile, at source and how do we help Alice and Bob with their (secure) data management? If we tackle the FAIR first and last mile, what about the FAIR middle? What about FAIR beyond just data – like exchanging and reusing pipelines for precision medicine?
Since 2008 the FAIRDOM collaboration [1] has worked on FAIR asset management and the development of a FAIR asset Commons for multi-partner researcher projects [2], initially in the Systems Biology field. Since 2016 we have been working with the BioCompute Object Partnership [3] on standardising computational records of HTS precision medicine pipelines.
So, using our FAIRDOM and BioCompute Object binoculars let’s go on a FAIR safari! Let’s peruse the ecosystem, observe the different herds and reflect what where we are for FAIR personalised medicine.
References
[1] http://www.fair-dom.org
[2] http://www.fairdomhub.org
[3] http://www.biocomputeobject.org
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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Semantic Web Adoption
- 1. Semantic Web Adoption Ivan Herman, W3C First China Semantic Web Symposium (CSWS 2007), Beijing, China, 2007-11-19
- 3. A way of looking at it… Semantic Technologies
- 4. The 2007 Gartner predictions By 2017, we expect the vision of the Semantic Web […] to coalesce […] and the majority of Web pages are decorated with some form of semantic hypertext. By 2012, 80% of public Web sites will use some level of semantic hypertext to create SW documents […] 15% of public Web sites will use more extensive Semantic Web-based ontologies to create semantic databases (note: “semantic hypertext” refers to, eg, RDFa, microformats with possible GRDDL, etc.) Source: “Finding and Exploiting Value in Semantic Web Technologies on the Web”, Gartner Research Report, May 2007
- 11. So how do applications look like?
- 13. Applications are not always very complex…
- 23. Extracting structured data from Wikipedia Courtesy of Chris Bizer, Free University of Berlin http://en.wikipedia.org/wiki/ Calgary <http://dbpedia.org/resource/ Calgary > dbpedia:native_name “Calgary” ; dbpedia:altitude “1048” ; dbpedia:population_city “988193” ; dbpedia:population_metro “1079310” ; dpbedia:mayor_name dbpedia:Dave_Bronconnier ; dpbedia:governing_body dbpedia:Calgary_City_Council ; ...
- 24. Automatic links among open datasets DBpedia Geonames Processors can switch automatically from one to the other… <http://dbpedia.org/resource/ Calgary > owl.sameAs <http://sws.geonames.org/5913490>; ... < http://sws.geonames.org/5913490 > owl:sameAs <http://DBpedia.org/resource/Calgary> wgs84_pos:lat “51.050112282”; wgs84_pos:long “-114.085285152”; sws:population “968460” ...
- 26. Examples of real applications…
- 30. Oracle’s Technology Network portal Courtesy of Mike DiLascio, Siderean Software, and Justin Kestelyn, Oracle Corporation ( SWEO Case Study ) Aggregates many source of content Re-group, categorize, etc content (using a taxonomy)
- 33. Semantic portal for art collections Courtesy of Jacco van Ossenbruggen, CWI, and Guus Schreiber, VU Amsterdam
Editor's Notes
- This is just a generic slide set. Should be adapted, reviewed, possibly with slides removed, for a specific event. Rule of thumb: on the average, a slide is a minute…