NCBO SPARQL Endpoint
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The document describes the NCBO SPARQL endpoint, which provides access to ontologies from the BioPortal in RDF format. It can be queried using SPARQL. The endpoint contains over 393 ontologies with 4.2 million terms and 80 million triples. Examples are provided to retrieve ontology metadata and terms. Performance tips recommend using UNIONS instead of FILTERS for optimized queries.
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Presentation at the ESWC 2011 PhD Symposium in May 2011, by Michael Schneider, FZI. Included are backup slides that have not been presented at the event. The corresponding PhD proposal can be found in the ESWC proceedings at <http: />. Alternatively, the PhD proposal can be downloaded from <http: />.
Multilingual issues in the representation of international bibliographic stan...
The document discusses multilingual issues in representing international bibliographic standards for the semantic web. It outlines IFLA's standards for bibliographic data and its namespace used to represent the standards and vocabularies as RDF. Translating the standards into different languages exposed challenges regarding scope, style, source documentation, disambiguation, and language inflection. The presentation calls for authoritative translations of cataloguing standards and related documents in 26+ languages.
Querying the Semantic Web with SPARQL
This document provides an overview of SPARQL, the query language for the Semantic Web. SPARQL allows querying RDF data by matching triple patterns and combining them with operations like optional and union patterns. Key features discussed include the anatomy of SPARQL queries, matching RDF literals and numerical values, filtering solutions, and defining datasets with the FROM clause. The document also covers SPARQL result forms and resources for learning more about SPARQL implementations and extensions.
Bh14 ogo
Presentation at Biohackathon 2014. Semantic integration of orthology resources: beyond the OGO experience
Ontology Engineering
My seminar on ontology engineering, mainly targeting linguists with a basic background in Web ontologies.
A Brief Introduction to SKOS
An introduction to SKOS (Simple Knowledge Organization System), a W3C recommendation/standard for interoperability of controlled vocabularies. Presented at Taxonomy Boot Camp London 2018
Presentation FAIRsFAIR workshop (April 2020)
The document summarizes work done by an ontology metadata task group to make ontologies and other semantic resources more findable, accessible, interoperable, and reusable (FAIR). The group analyzed ontology metadata practices, vocabularies, and libraries/repositories. They developed a new unified metadata model and implemented it in the AgroPortal ontology repository. The repository harvests ontologies and vocabularies, extracts and aggregates their metadata, and makes it available and searchable to help users find and select relevant semantic resources.
FAIR data requires FAIR ontologies, how do we do?
FAIR data requires FAIR ontologies, how do we do?INRAE (MISTEA) and University of Montpellier (LIRMM)
FAIR data requires FAIR ontologies and standards. There has been an explosion in the number of ontologies but they are difficult to identify and manage due to a lack of consistent metadata. Existing ontology metadata practices were reviewed, finding that developers use various metadata vocabularies inconsistently and important ontology-specific metadata is underused. Ontology repositories help make ontologies more FAIR by providing interfaces for publishing, accessing, and reusing ontologies and their metadata. The presentation focuses on the NCBO BioPortal as an example ontology repository and how its technologies have been adopted by other repositories. Improving ontology metadata will help comprehension of the ontology landscape; a new AgroPortal metadata model was created to better describe ontologies and theirSimilar to NCBO SPARQL Endpoint (20)
Integrating a Domain Ontology Development Environment and an Ontology Search ...
Integrating a Domain Ontology Development Environment and an Ontology Search ...
NCBO BioPortal SPARQL Endpoint - The Quad Economy of a Semantic Web Ontology ...
NCBO BioPortal SPARQL Endpoint - The Quad Economy of a Semantic Web Ontology ...
Multilingual issues in the representation of international bibliographic stan...
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Building Translate on Glass
Slides from the Women Hacking Glass session. The slides describe how to use the Google Translate API within a Glass app.
NCBO Web Services: Powering Semantically Aware Applications
The National Center for Biomedical Ontology provides web services and tools to enable the application of ontologies in biomedical science and clinical care. It maintains a library of biomedical ontologies and builds tools for ontology development, data annotation, and data integration. Key web services include services for ontology search, traversal, and download, as well as annotation and mapping services.
NCBO Technology Overview
The document provides an overview of the National Center for Biomedical Ontology (NCBO) technology including REST web services, the BioPortal ontology repository, NCBO web services, and the BioPortal SPARQL endpoint. Key NCBO web services allow users to search ontologies, access ontology terms and hierarchies, propose term annotations, map between ontologies, and annotate data with ontology terms. The document outlines several NCBO tools and resources available for working with biomedical ontologies.
BioPortal: ontologies and integrated data resources
BioPortal is a website hosted by the National Center for Biomedical Ontology that allows users to browse, search, and utilize various biomedical ontologies and integrated data resources. It contains ontologies related to different domains in biomedicine as well as tools to facilitate the annotation and integration of data using the ontologies.
Web Services for Semantic Applications in Healthcare and Life Sciences
The document discusses web services for semantic applications in healthcare and life sciences. It describes RESTful web services that use HTTP and unique URLs to represent objects. It also discusses BioPortal, an ontology repository that allows browsing, searching, and visualizing ontologies in various formats. Tools are presented that use ontology web services and BioPortal for tasks like ontology term selection, automated recognition of terms before publication, and annotation within visualizations.
NCBO Technology for GSC15
The National Center for Biomedical Ontology (NCBO) provides access to biomedical ontologies through its BioPortal repository and suite of web services. BioPortal stores and allows viewing, browsing, and searching across ontologies. The NCBO web services enable programmatic access and enable functions like searching, traversing, and annotating terms. Several software applications leverage the NCBO web services by integrating access to ontologies to provide features like term tagging.
Ontology Web Services
The National Center for Biomedical Ontology provides several ontology web services including:
1) Accessing ontologies and ontology views through services like search, term access, and hierarchy visualization.
2) Creating ontology-based annotations on text data through services like annotation and ontology recommendation.
3) Indexing annotations in a resource index to facilitate search and discovery of annotated resources.
NCBO Tools and Web services
The document describes tools and web services from the National Center for Biomedical Ontology (NCBO) including the Ontology Web Services, Ontology Widgets, NCBO Annotator, NCBO Resource Index, and Ontology Recommender. The NCBO Annotator is an open access web service that annotates text with terms from ontologies in BioPortal and includes a variety of customization parameters. The NCBO Resource Index provides an ontology-based search across publicly available biomedical resources.
Ontology Web services for Semantic Applications
The document describes ontology web services created by the National Center for Biomedical Ontology to facilitate the application of ontologies in biomedical science. The services provide access to ontologies and related functions like searching, term details, hierarchies and mappings. Additional services allow the creation of ontology-based annotations using tools like the annotator and ontology recommender. All services are accessible via RESTful web APIs.
NCBO Technology
The National Center for Biomedical Ontology (NCBO) creates software and tools to enable the application of ontologies in biomedical science. It maintains a library of biomedical ontologies in BioPortal and provides web services and applications to access, integrate and annotate data with ontologies. Key activities include building tools like Protégé, BioPortal, the annotator and providing a SPARQL endpoint to access ontology data in RDF format.
CTSA Inventory Resource Web Presence
The document describes the CTSA Inventory Resource Web Presence (CIRWP), a web-accessible and searchable inventory of research resources across the CTSA consortium. It outlines the development of CIRWP, including building an informatics infrastructure based on standards, extending ontologies to annotate resource descriptions, and deploying web services and tools to enable a distributed inventory. CIRWP includes full or partial inventories from 37 CTSA sites cataloging over 370 informatics resources. The document discusses future goals of CIRWP such as accelerating harmonization across organizations and outreach, and highlights evaluations conducted to design CIRWP with user-centered approaches.
The NCBO Annotator and Enrichment Analysis with the Human Disease Ontology
The document discusses the NCBO Annotator and its ability to annotate clinical notes with terms from over 250 biomedical ontologies. The annotator can process up to 1 million clinical notes per hour and adds features like negation detection. It was used to annotate notes from over 1.04 million patients to allow for pattern analysis and enrichment analysis related to drug safety and off-label drug use with the Human Disease Ontology.
Annotation Analysis for Testing Drug Safety Signals
The NCBO Annotator enables mining clinical documents by:
1) Tagging textual metadata from clinical documents with terms from biomedical ontologies.
2) Using the tagged data to perform further analysis like identifying adverse drug events and patterns of off-label drug use.
3) Future work includes expanding from individual term recognition to identifying expert-defined patterns involving terms for tasks like determining smoking status and medication dosages from notes.
Collaborative Development of Ontologies using BioPortal and WebProtégé
The document discusses the integration of WebProtégé and BioPortal to provide a collaborative environment for ontology development. WebProtégé allows simultaneous editing and discussion of ontologies. BioPortal publishes ontologies and collects community feedback through comments. It also provides analytics. The integration allows editors to see comments in context and make changes, with comments archived once tasks are complete. This provides a full lifecycle of ontology development, feedback, and refinement.
NCBO Overview and Biositemaps
The document describes the National Center for Biomedical Ontology (NCBO) and Biositemaps. It discusses:
1) The NCBO's mission to create software for applying ontologies in biomedicine and its partners including Stanford University, Mayo Clinic, and University of Buffalo.
2) Biositemaps which provide a machine-readable description of biomedical resources using an information model based on the Biomedical Resource Ontology to enable discovery by search engines.
3) How Biositemaps has grown from an initial wiki listing resources by the National Centers for Biomedical Computing to a catalog of over 1,400 resources shared using a standardized framework.
Biomedical Resource Ontology
The document describes the Biomedical Resource Ontology (BRO), which provides semantics for annotating resources in Biositemaps. BRO defines types of resources, activities, and areas of research. It has been applied in tools for editing, searching, and discovering resources across multiple institutions. Ongoing work involves expanding BRO terms, separating the ontology from the information model, and integrating with other related projects.
NCBO Web services: Powering Semantically Aware Applications
The National Center for Biomedical Ontology provides several web services to enable semantically aware applications, including services for ontology development and visualization, data annotation, and data integration. These services include tools for ontology search, traversal, mapping, and comment as well as services for term recognition, annotation, and access to annotated data. Documentation for using these services is available on the NCBO website.
Collaborative Development of Ontologies using BioPortal and WebProtégé
The document discusses the integration of WebProtégé and BioPortal to provide a collaborative environment for ontology development. WebProtégé allows simultaneous editing and discussion of ontologies. BioPortal publishes ontologies and collects community feedback through comments. This integrated platform allows ontology editors to see comments in context and update the ontology accordingly.
Ontology Web Services for Semantic Applications
The document summarizes the Ontology Web Services provided by the National Center for Biomedical Ontology (NCBO) including the BioPortal Ontology Web services, NCBO Annotator Web service, and NCBO Resource Index Web service. These services allow programmatic access and traversal of ontologies, annotation of text with ontology terms, and searching of public biomedical data repositories indexed with ontology terms. The services aim to facilitate integration and interpretation of biomedical data on the Semantic Web.
NCBO Resource Index: Ontology-based Search and Mining of Biomedical Resources
This document summarizes the NCBO Resource Index, which is an ontology-based search tool that indexes over 16 billion annotations from over 200 ontologies and 3.5 million elements. It integrates information from diverse biomedical data sources and ontologies to improve search results through synonyms, hierarchies and mappings. The Resource Index is developed by the National Center for Biomedical Ontology to help users search for, find and explore biomedical resources.
More from Trish Whetzel (20)
NCBO Web Services: Powering Semantically Aware Applications
NCBO Web Services: Powering Semantically Aware Applications
BioPortal: ontologies and integrated data resources
BioPortal: ontologies and integrated data resources
Web Services for Semantic Applications in Healthcare and Life Sciences
Web Services for Semantic Applications in Healthcare and Life Sciences
The NCBO Annotator and Enrichment Analysis with the Human Disease Ontology
The NCBO Annotator and Enrichment Analysis with the Human Disease Ontology
Annotation Analysis for Testing Drug Safety Signals
Annotation Analysis for Testing Drug Safety Signals
Collaborative Development of Ontologies using BioPortal and WebProtégé
Collaborative Development of Ontologies using BioPortal and WebProtégé
NCBO Web services: Powering Semantically Aware Applications
NCBO Web services: Powering Semantically Aware Applications
Collaborative Development of Ontologies using BioPortal and WebProtégé
Collaborative Development of Ontologies using BioPortal and WebProtégé
NCBO Resource Index: Ontology-based Search and Mining of Biomedical Resources
NCBO Resource Index: Ontology-based Search and Mining of Biomedical Resources
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一比一原版(USF毕业证)旧金山大学毕业证如何办理
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四：留信认证留学生信息网站永久可查
国外毕业证学位证成绩单办理方法：
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办理(sdsu毕业证书)圣地亚哥州立大学毕业证【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
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校名:学校英文全称
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其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
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综上所述，办理(sdsu毕业证书)圣地亚哥州立大学毕业证【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
Alluxio Webinar | 10x Faster Trino Queries on Your Data Platform
Alluxio Webinar
June. 18, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jianjian Xie (Staff Software Engineer, Alluxio)
As Trino users increasingly rely on cloud object storage for retrieving data, speed and cloud cost have become major challenges. The separation of compute and storage creates latency challenges when querying datasets; scanning data between storage and compute tiers becomes I/O bound. On the other hand, cloud API costs related to GET/LIST operations and cross-region data transfer add up quickly.
The newly introduced Trino file system cache by Alluxio aims to overcome the above challenges. In this session, Jianjian will dive into Trino data caching strategies, the latest test results, and discuss the multi-level caching architecture. This architecture makes Trino 10x faster for data lakes of any scale, from GB to EB.
What you will learn:
- Challenges relating to the speed and costs of running Trino in the cloud
- The new Trino file system cache feature overview, including the latest development status and test results
- A multi-level cache framework for maximized speed, including Trino file system cache and Alluxio distributed cache
- Real-world cases, including a large online payment firm and a top ridesharing company
- The future roadmap of Trino file system cache and Trino-Alluxio integration
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Alluxio Webinar | 10x Faster Trino Queries on Your Data Platform
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NCBO SPARQL Endpoint
- 1. NCBO SPARQL Endpoint Trish Whetzel Outreach Coordinator THE NATIONAL CENTER FOR BIOMEDICAL ONTOLOGY
- 3. BioPortal SPARQL Content • All ontologies from BioPortal – Original ontology format (OBO, OWL, UMLS/RRF) transformed into RDF – Updated daily – Latest version only • Statistics – 393 ontologies – 4.2M terms – 2419 different predicates – 80M triples
- 4. Resource Description Framework – A collection of RDF statements represents a labeled, directed multi-graph – RDF is modeled as a set of triples – Triples are in the form (subject, predicate, object) where: • Subjects and predicates are URIs • Objects are either URIs or Literals • Literals can be typed and have a language tag – Blank nodes (bnodes) or anonymous resources are nodes that do not have a URI or literal – RDF is not XML, there are different serializations, e.g. N3, turtle, rdf/xml
- 5. RDF – Turtle format – Prefixes are allowed and statements can be grouped by subject – Specific constructions to represent lists and blank nodes – Least verbose and best human readable format, easy to serialize and good performance for parsing
- 6. RDF – N3 format – One line per triple, no prefixes, not grouped by subject – More verbose, easy to serialize, best performance for parsing
- 7. RDF – RDF/XML format – Extremely verbose, worst human readable format – Worst performance for parsing
- 8. SPARQL – W3C standard query language for RDF – Structure
- 9. BioPortal Metadata • Virtual ontology identifier – Stable identifier across all versions of the ontology – All versions of an ontology are linked via this ID • Ontology version identifier – Unique for each ontology version – Most metadata linked directly to the ontology version
- 13. All ontologies updated since DATE
- 14. Find term in all ontologies
- 15. Select all terms from the ABA Adult Mouse Anatomy
- 16. Select URI and preferred label from all terms
- 17. Get parent of given term
- 18. Select all terms and their parent
- 20. Select properties for term
- 21. Count terms in SNOMED
- 22. Performance Tips and Tricks – Completely unbound patterns (?g ?s ?p ?o) are not allowed – To optimize queries, use UNIONS instead of FILTERS – If using FILTER on literals it is better if the filter is not applied to millions of rows – To prevent combinatorial explosions of results, consider use CONSTRUCT or DESCRIBE (any M-N relationship can provoke this)
- 23. SPARQL Code Repository • https://github.com/ncbo/sparql-code-examples
- 24. BioPortal SPARQL Endpoint • Documentation: http://www.bioontology.org/wiki/index.php/SPA RQL_BioPortal • Query interface: http://sparql.bioontology.org/ • Example queries: http://sparql.bioontology.org/examples • Sample code: https://github.com/ncbo/sparql-code- examples
Editor's Notes
- Multi-graph – edges that have the same end nodes
- We can use an unbound GRAPH to find in which ontology a pattern is satisfied.
- Our backend has subPropertyOf reasoning to help to retrieve preferable labels, synomyns and definitions. Use skos:prefLabel for preferable labels, skos:altLabel for synonyms and skos:definition for definitions.
- One can think of optional as a left outer join. The pattern in the optional will be matched if possible or empty slot will be returned.
- Our backend relies on predicate indexing mostly. and most likely queries with unbound ?p will run slow.