This document discusses extending OpenSocial with RDF to benefit research networking tools. The authors integrated the University of California, San Francisco's (UCSF) Profiles research networking tool with Shindig and Babel to become OpenSocial compliant. This allows OpenSocial applications to be developed for specific domains like research using the VIVO ontology without compromising interoperability. A demonstration application called DIRECT Match was built to find similar researchers across institutions using researcher attributes stored in RDF. The implementation reduces the effort for other RDF-based research networking tools to support OpenSocial.
Bio4j: A pioneer graph based database for the integration of biological Big DataPablo Pareja Tobes
1. Bio4j
2. What’s Bio4j?: Data included
3. What’s Bio4j?: A completely new and powerful framework for protein
4. What’s Bio4j?: Neo4j --> very scalable
5. What's Bio4j?: Everything in Bio4j is open source released under AGPLv3
6. Bioinformatics DBs and Graphs: Highly interconnected overlapping knowledge spread throughout different databases
7. Bioinformatics DBs and Graphs: Data is in most cases modeled in relational databases, (sometimes even just as plain CSV files)
8. Bioinformatics DBs and Graphs: Problems of a relational paradigm
9. Bioinformatics DBs and Graphs: Life + Biology like a graph
10. Bioinformatics DBs and Graphs: NoSQL
11. Bioinformatics DBs and Graphs: NoSQLdata models
12. Bioinformatics DBs and Graphs: The Graph DB model: representation
13. Bioinformatics DBs and Graphs: Neo4j
14. Initial motivation: Why starting all this?
15. Initial motivation: Processes had to be automated for BG7 (http://bg7.ohnosequences.com)
Bio4j: A pioneer graph based database for the integration of biological Big DataPablo Pareja Tobes
1. Bio4j
2. What’s Bio4j?: Data included
3. What’s Bio4j?: A completely new and powerful framework for protein
4. What’s Bio4j?: Neo4j --> very scalable
5. What's Bio4j?: Everything in Bio4j is open source released under AGPLv3
6. Bioinformatics DBs and Graphs: Highly interconnected overlapping knowledge spread throughout different databases
7. Bioinformatics DBs and Graphs: Data is in most cases modeled in relational databases, (sometimes even just as plain CSV files)
8. Bioinformatics DBs and Graphs: Problems of a relational paradigm
9. Bioinformatics DBs and Graphs: Life + Biology like a graph
10. Bioinformatics DBs and Graphs: NoSQL
11. Bioinformatics DBs and Graphs: NoSQLdata models
12. Bioinformatics DBs and Graphs: The Graph DB model: representation
13. Bioinformatics DBs and Graphs: Neo4j
14. Initial motivation: Why starting all this?
15. Initial motivation: Processes had to be automated for BG7 (http://bg7.ohnosequences.com)
Starting from scratch – building the perfect digital repositoryVioleta Ilik
By establishing a digital repository on the Feinberg School of Medicine (FSM), Northwestern University, Chicago campus, we anticipate to gain ability to create, share, and preserve attractive, functional, and citable digital collections and exhibits. Galter Health Sciences Library did not have a repository as of November 2014. In just a few moths we formed a small team that was charged at looking to select the most suitable open source platform for our digital repository software. We followed the National Library of Medicine master evaluation criteria by looking at various factors that included: functionality, scalability, extensibility, interoperability, ease of deployment, system security, system, physical environment, platform support, demonstrated successful deployments, system support, strength of development community, stability of development organization, and strength of technology roadmap for the future. These factors are important for our case considering the desire to connect the digital repository with another platform that was an essential piece in the big FSM picture – VIVO. VIVO is a linked data platform that serves as a researchers’ hub and which provides the names of researchers from academic institutions along with their research output, affiliation, research overview, service, background, researcher’s identities, teaching, and much more.
Build Knowledge Graphs with Oracle RDF to Extract More Value from Your DataJean Ihm
AnD Summit '19 slides - Souri Das, Matthew Perry, Melli Annamalai. This presentation covers knowledge graphs built using the RDF capabilities of Oracle Spatial and Graph. We will illustrate how to define a knowledge graph, create virtual or materialized graphs from existing data (relational tables, CSV files, etc.), derive new knowledge through logical inference, navigate and query graphs using W3C standards, analyze knowledge graphs with graph algorithms, and more. Real-world use cases from various industries will also be shared.
As BioPharma adapts to incorporate nimble networks of suppliers, collaborators, and regulators the ability to link data is critical for dynamic interoperability. Adoption of linked data paradigm allows BioPharma to focus on core business: delivering valuable therapeutics in a timely manner.
Talk at 3th Keystone Training School - Keyword Search in Big Linked Data - Institute for Software Technology and Interactive Systems, TU Wien, Austria, 2017
Clariah Tech Day: Controlled Vocabularies and Ontologies in Dataversevty
This presentation is about external CVs support in Dataverse, Open Source data repository. Data Archiving and Networked Services (DANS-KNAW) decided to use Dataverse as a basic technology to build Data Stations and provide FAIR data services for various Dutch research communities.
This presentation was provided by Abigail Sparling and Adam Cohen of The University of Alberta Library, during the NISO webinar "Implementing Linked Library Data," held on November 13, 2019.
This presentation looks at developing an integrated repository for Leeds Met comprising an Open Access research archive and a repository of reusable learning objects.
From the outset, the project team recognised that intraLibrary lacked functionality essential to an OA research archive, specifically; a publicly accessible search interface. Development work has therefore focussed on developing a suitable interface based on the SRU protocol and configuring a suitable metadata template within intraLibrary. We also consider differentiation and appropriate presentation of discrete types of content by the SRU interface and implementation of the OAI-PMH and XML sitemaps to aid discoverability of research material.
Outline of the UCSF approach to Research Networking, which focuses on rapid iterations of adding new data sources and features to see what works, and abandon what doesn't work.
Profiling systems have achieved notable adoption by research institutions.1 Multi-site search of research profiling systems has substantially evolved since the first deployment of systems such as DIRECT2Experts.2 CTSAsearch is a federated search engine using VIVO-compliant Linked Open Data (LOD) published by members of the NIH-funded Clinical and Translational Science (CTSA) consortium and other interested parties. Sixty-four institutions are currently included, spanning six distinct platforms and three continents (North America, Europe and Australia). In aggregate, CTSAsearch has data on 150-300 thousand unique researchers and their 10 million publications. The public interface is available at http://research.icts.uiowa.edu/polyglot.
Starting from scratch – building the perfect digital repositoryVioleta Ilik
By establishing a digital repository on the Feinberg School of Medicine (FSM), Northwestern University, Chicago campus, we anticipate to gain ability to create, share, and preserve attractive, functional, and citable digital collections and exhibits. Galter Health Sciences Library did not have a repository as of November 2014. In just a few moths we formed a small team that was charged at looking to select the most suitable open source platform for our digital repository software. We followed the National Library of Medicine master evaluation criteria by looking at various factors that included: functionality, scalability, extensibility, interoperability, ease of deployment, system security, system, physical environment, platform support, demonstrated successful deployments, system support, strength of development community, stability of development organization, and strength of technology roadmap for the future. These factors are important for our case considering the desire to connect the digital repository with another platform that was an essential piece in the big FSM picture – VIVO. VIVO is a linked data platform that serves as a researchers’ hub and which provides the names of researchers from academic institutions along with their research output, affiliation, research overview, service, background, researcher’s identities, teaching, and much more.
Build Knowledge Graphs with Oracle RDF to Extract More Value from Your DataJean Ihm
AnD Summit '19 slides - Souri Das, Matthew Perry, Melli Annamalai. This presentation covers knowledge graphs built using the RDF capabilities of Oracle Spatial and Graph. We will illustrate how to define a knowledge graph, create virtual or materialized graphs from existing data (relational tables, CSV files, etc.), derive new knowledge through logical inference, navigate and query graphs using W3C standards, analyze knowledge graphs with graph algorithms, and more. Real-world use cases from various industries will also be shared.
As BioPharma adapts to incorporate nimble networks of suppliers, collaborators, and regulators the ability to link data is critical for dynamic interoperability. Adoption of linked data paradigm allows BioPharma to focus on core business: delivering valuable therapeutics in a timely manner.
Talk at 3th Keystone Training School - Keyword Search in Big Linked Data - Institute for Software Technology and Interactive Systems, TU Wien, Austria, 2017
Clariah Tech Day: Controlled Vocabularies and Ontologies in Dataversevty
This presentation is about external CVs support in Dataverse, Open Source data repository. Data Archiving and Networked Services (DANS-KNAW) decided to use Dataverse as a basic technology to build Data Stations and provide FAIR data services for various Dutch research communities.
This presentation was provided by Abigail Sparling and Adam Cohen of The University of Alberta Library, during the NISO webinar "Implementing Linked Library Data," held on November 13, 2019.
This presentation looks at developing an integrated repository for Leeds Met comprising an Open Access research archive and a repository of reusable learning objects.
From the outset, the project team recognised that intraLibrary lacked functionality essential to an OA research archive, specifically; a publicly accessible search interface. Development work has therefore focussed on developing a suitable interface based on the SRU protocol and configuring a suitable metadata template within intraLibrary. We also consider differentiation and appropriate presentation of discrete types of content by the SRU interface and implementation of the OAI-PMH and XML sitemaps to aid discoverability of research material.
Outline of the UCSF approach to Research Networking, which focuses on rapid iterations of adding new data sources and features to see what works, and abandon what doesn't work.
Profiling systems have achieved notable adoption by research institutions.1 Multi-site search of research profiling systems has substantially evolved since the first deployment of systems such as DIRECT2Experts.2 CTSAsearch is a federated search engine using VIVO-compliant Linked Open Data (LOD) published by members of the NIH-funded Clinical and Translational Science (CTSA) consortium and other interested parties. Sixty-four institutions are currently included, spanning six distinct platforms and three continents (North America, Europe and Australia). In aggregate, CTSAsearch has data on 150-300 thousand unique researchers and their 10 million publications. The public interface is available at http://research.icts.uiowa.edu/polyglot.
We describe current work in federating data from institutional research profiling systems – providing single-point
access to substantial numbers of investigators through concept-driven search, visualization of the relationships
among those investigators and the ability to interlink systems into a single information ecosystem.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
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See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
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The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
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Sectoral targets and attacks as well as the cost of ransom
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Major cyber events in 2024
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Elizabeth Buie - Older adults: Are we really designing for our future selves?
VIVO 2011 OpenSocial and RDF Poster
1. Extending OpenSocial with RDF to Benefit Research Networking Tools
Eric Meeks (UCSF), Leslie Yuan (UCSF), Griffin Weber (Harvard), Maninder Kahlon (UCSF)
Clinical and Translational Science Institute, University of California, San Francisco
Harvard Catalyst, The Harvard Clinical and Translational Science Center
Introduction Methods Results Example Data
Research Networking Tools such as VIVO and Profiles have found UCSF extended Profiles to become an OpenSocial container by OpenSocial applications can now be developed for specific domain
RDF/XML for Griffin Weber
widespread adoption in the biomedical research community. RDF is integrating Profiles with Shindig, a product maintained by the Apache needs without overtaxing interoperability. For example, an OpenSocial
becoming a primary means for exposing the data contained within these Software Foundation. Shindig is an open source Java product that is the application built for the VIVO ontology will work within any OpenSocial
tools, and the VIVO ontology has become the standard vocabulary for reference standard for the OpenSocial API, and is the most commonly Research Networking Tool that produces VIVO RDF. Moreover, a FOAF
expression. Both VIVO and Profiles export data through the RDF/XML used code base for making a web site OpenSocial compliant. based OpenSocial application would also work with a VIVO based tool
serialization format. because the VIVO ontology is an extension of FOAF. Essentially, this
The Babel application from the SIMILE Project (Simple Interoperability RDF approach allows OpenSocial to become domain model agnostic.
OpenSocial is a standard API for running embedded applications of Metadata and Information in unLike Environments) at MIT proved
(gadgets) within a containing web site. OpenSocial is supported by successful in being able to convert RDF/XML from both Profiles and Consistent domain model resolution is still required for interoperability
groups within industry and research such as Google, LinkedIn, Nature VIVO into usable JSON. Babel is open source and like Shindig, but this problem will instead be solved by the use of ontologies, which
Network, and Elsevier SciVerse. developed in Java. offer a more sophisticated answer than the “one size plus extensions
fits all” approach currently found within OpenSocial. From the
UCSF Profiles supports the OpenSocial standard and UCSF has been UCSF integrated Babel into Shindig and created an OpenSocial feature OpenSocial perspective this approach should allow easier adoption into
building a shareable library of OpenSocial applications to extend extension to automatically create People JSON objects that are sourced vertical markets such as academia, research, or enterprise, provided
Profiles functionality. by RDF. Our OpenSocial People objects now have attributes such as that the vertical market is willing to adopt RDF.
authorInAuthorship and hasResearchArea that are meaningful to our
domain. In OpenSocial, our People now look like researchers! The implementation effort for other RDF based Research Networking
Problem Tools (such as VIVO) to become OpenSocial compliant is now reduced
A demonstration gadget called DIRECT Match was built as a proof of because the code for converting domain objects to JSON can be reused
RDF is a data oriented standard whereas OpenSocial is an application concept. DIRECT Match uses the VIVO ontology defined among any Research Networking Tool that produces RDF/XML.
standard. By necessity OpenSocial contains and references standards hasResearchArea and freetextKeyword attributes of the home page
for application support such as user interface, deployment model, owner to automatically query the DIRECT network to find similar
security/authentication and data model. researchers across multiple institutions. DIRECT Match has been SIMILE
successfully tested with RDF content from both Profiles and VIVO. Babel
The data model within OpenSocial, particularly those parts centered
around people and connections, are not well matched for the
biomedical research domain. The default fields that describe a person
and connections reflect the consumer and business oriented market OpenSocial with RDF/XML JSON for Griffin Weber
where OpenSocial originated, and do not align with the academic
definition of a researcher. A standard OpenSocial person has methods
for friends and movies but not for co-authors or publications.
OpenSocial allows for custom extensions of the data model. But Browser
customizations break interoperability. At UCSF we could manually OR*
extend OpenSocial to reflect the fields and connections that define our
researchers but the larger goal is to gain adoption within the research
networking community so that applications built to extend our platform
HTML Content
can easily be shared amongst other institutions. With RDF and the
RDF/XML
existing support for standard ontologies such as VIVO and FOAF we
can achieve this larger goal.
Approach
Domain Object Request
OpenSocial applications use JavaScript and JSON to execute within
the browser. The domain objects in OpenSocial (ex. people, movies, Babel
Next Steps
friends in the consumer oriented world or researcher, publications, co-
JSON Domain Data
authors in the bioinformatics world) need to be expressed as JSON to Release Profiles-based integration to open source community. This is
be available to OpenSocial applications. currently targeted for the 1.2 release of Profiles.
Acknowledgments
The JSON encoding typically happens through a custom development Gadget Content Use the OpenSocial Security Token to create data access mechanisms
Gadget
effort (extending Apache Shindig) specific to the implementing
Specs
for control of who can see what data. This would allow sensitive data to This project was supported by NIH/NCRR UCSF-CTSI Grant Number
institutions technical infrastructure. One institution might store domain be safely folded into Linked Open Data for OpenSocial applications. UL1 RR024131 and Harvard Catalyst Grant Number 1 UL1 RR025758-
data in an Oracle database with a particular set of tables and columns, 01. Its contents are solely the responsibility of the authors and do not
another institution might use SQL Server, etc. Babel is ontology agnostic. Determine need for ontology specific necessarily represent the official views of the NIH.
Gadget Hosting Servers OpenSocial features, such as VIVO-ontology oriented convenience
With RDF, a reusable coding effort is possible by using existing functions to easily access co-authors, publications and more. We would like to thank MIT Libraries and MIT CSAIL as well as all other
technologies such as SIMILE Babel from MIT to convert the RDF/XML http://anywhere/gadget.xml
contributors to the SIMILE Project.
expression of the domain data to JSON in a form that can be readily Assess need for an “eager fetching” strategy to convert referenced child
used by OpenSocial applications. * Successfully tested with VIVO (ask for demo!) but not yet implemented. RDF/XML data to JSON and implement if necessary. We would also like to thank Andy Smith and the OpenSocial foundation.