Linked Open Data_mlanet13

An Introduction to the Semantic Web and Linked Open Data

Kristi L. Holmes, PhDTwitter: @kristiholmes

Layne Mark Johnson, PhD@LayneJohnson

The day after May the Fourth, 2013

Information Overload

We humans have always applied tools to our work to make things

work easier…

Simple Machines

“a web of data that can be processed directly and indirectly by machines”

-Tim Berners-Lee

At its heart, the Semantic Web is really about

extending standard Web technologies to better deal

with data on the Web.

If the WWW is for people, the Semantic Web is for machines

George Thomas and Jim Hendler, http://www.data.gov/communities/node/116/blogs/142

Data modeled as bidirectional relationships

All data has standard form

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Semantic Web Value Proposition…

Web-based infrastructure of standards and technologies which allows for a distributable, machine readable description of data that allows for stronger data and smart web application linkages

How the Semantic Web works

Anakin Skywalker is Luke Skywalker's father.

How the Semantic Web works

XML and RDF are at the heart of the Semantic Web. They give computers a structure in which to look for

information and define relationships between resources.

http://computer.howstuffworks.com/semantic-web

An ontology is simply a vocabulary that describes objects and how they relate to one another. A schema

is a method for organizing information

http://computer.howstuffworks.com/semantic-web

Using languages designed for data

RDF | OWL | XML

Semantic web: describes methods and technologies to allow machines to understand the meaning or "semantics” of information on the web. -- W3C director Sir Tim Berners-Lee

Ontology: a formal representation of the knowledge by a set of concepts within a domain and the relationships between those concepts.-- Wikipedia

Let’s talk about the data…

The Semantic Web isn't just about putting data on the web. It is about making links, so that a person or

machine can explore the web of data.  With linked data, when you have some

of it, you can find other related data.

http://computer.howstuffworks.com/semantic-web

The 5 Stars of Linked Open Data

★★★★★★★★★★★★★★★

http://lab.linkeddata.deri.ie/2010/star-scheme-by-example/http://www.w3.org/DesignIssues/LinkedData.html

AVAILABILITY & VALUE

Is your data 5-star??

The 5 Stars of Linked Open Data

http://5stardata.info

The growth of Linked Data

20082007

2011

http://lod-cloud.net

What kind of things are available as

linked data?

The LOD Cloud

Models and standards that allow for greater data exchange (and flexibility!)

It takes layers and layers of metadata, logic and security to

make the Web machine-readable.

http://computer.howstuffworks.com/semantic-web

Building a web of data

http://geology.com/articles/night-satellite/satellite-photo-of-europe-at-night-lg.jpg

Data Creators, Data Aggregators, & Data Consumers

Repositories. Tools. Applications.

Workflows

Ok! Now let’s dig into a few good examples of how we can put

these things to work

Linked Open Data and Biomedical Research: A Survey of Current International Efforts

Kristi L. Holmes, PhDTwitter: @kristiholmes

Layne Mark Johnson, PhD@LayneJohnson

May 5, 2013

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Courtesy Mike Conlon, U Florida

Projects.

Research NetworkingOntology

Research NetworkingInformation about scholars is optimized using a Web-based infrastructure of

standards and technologies which allows for a distributable, machine readable description of data that allows for stronger data and smart web application linkages across many universities, agencies, societies both

within the US and abroad.

Why is this important?

Linked data infrastructure allows for • Visualizations, research and clinical data integration, and deep

semantic searching across multiple types and sources of data• By breaking data out of traditional database silos, research

networking platforms promote a network effect within a single site and across multiple sites– The value of the network increases with the amount of linked data

and applications that are available to consume the linked data.

The Semantic Web & Researcher Networking

• Increasing recognition of the value of semantic web standards • Increasing momentum in support of semantic web

technologies to facilitate research discovery• Recommendations for researcher networking recently

endorsed by the CTSA Consortium Steering Committee represent a new standard in researcher networking.

• Examples of applications that consume these rich data include: visualizations, enhanced multi-site search. Other utilities are in development across a wide range of topic areas.

Recommendations and Best Practices for Research Networking

The Research Networking Recommendations were approved by the CTSA Consortium Executive and Steering Committee on October 25, 2011.

Recommendations for Research Networking:• Recommendation: All CTSAs should encourage their institution(s) to implement

research networking tool(s) institution-wide that utilize RDF triples and an ontology compatible with the VIVO ontology. 

• Recommendation: Information in people profiles at institutions should be publicly available as data as a general principle, specifically as Linked Open Data.  To ensure quality of information, authoritative electronic data sources versus manual entry should be emphasized.  Institutions will vary in the amount of information that they will include and make publicly available but the value is enhanced by the quality and quantity of information.

• Recommendation: Monitoring of the research networking landscape, technology, and tools should continue to be overseen by experts from the CTSA consortium (e.g., the Research Networking group of the Informatics KFC).

https://www.ctsacentral.org/recommendations-and-best-practices-research-networking

Research Networking Systems

• VIVO, Profiles, SciVal Experts, Stanford’s CAP, Iowa’s Loki

• Encourage your RN provider to meet the recommendations for Researcher networking– Better visibility – Enhanced utility

Profiles

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http://catalyst.harvard.edu/spotlights/profiles.html

VIVO

This work is funded by the National Institutes of Health, U24 RR029822. 

VIVO enjoys a robust open source, open community space to support implementation, adoption, and development efforts around the

world. See http://vivo.sourceforge.net

www.ctsaconnect.org CTSAconnectReveal Connections. Realize

Potential.

CTSAConnect ProjectGoals:

– Identify potential collaborators, relevant resources, and expertise across scientific disciplines

– Assemble translational teams of scientists to address specific research questions

Approach:Create a semantic representation of clinician and basic science researcher expertise to enable– Broad and computable representation of translational

expertise– Publication of expertise as Linked Data (LD) for use in

other applications

2/21/14 31www.ctsaconnect.org CTSAconnectReveal Connections. Realize

Potential.

Merging VIVO and eagle-i

eagle-i is an ontology-driven application for collecting and searching research resources.

VIVO is an ontology-driven application for collecting anddisplaying information about people.

Both publish Linked Data. Neither addresses clinical expertise.

CTSAconnect will produce a single Integrated Semantic Framework, a modular collection of ontologies — that also includes clinical expertise

eagle-i

Resources

VIVO

People

Coordinationeagle-i

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Semantic

Clinical activities

OpenPHACTS

Open PHACTS Project• To reduce the barriers to drug discovery in industry,

academia and for small businesses, the Open PHACTS consortium is building the Open PHACTS Discovery Platform. This will be freely available, integrating pharmacological data from a variety of information resources and providing tools and services to question this integrated data to support pharmacological research. 

Guiding principle is open access, open usage, open source- Key to standards adoption -

http://www.openphacts.org/

OpenPHACTS

Open PHACTS Project• Develop a set of robust standards…• Implement the standards in a semantic integration hub• Deliver services to support drug discovery programs in pharma

and public domain• 22 partners, 8 pharmaceutical companies, 3 biotechs• 36 months project, through March 2014

Guiding principle is open access, open usage, open source- Key to standards adoption -

http://www.openphacts.org/

http://skr3.nlm.nih.gov/SemMed/index.html

Outreach and adoption activities

Education and

training

Ontology and

controlled vocabulary expertise

Relationships with

vendors/data providers

Programming & technical support

Understand data structure

Libraries

Libraries are supporting (& contributing!) to work areas in a variety of ways related to core

mission and service areas

Tools & Apps.

SearchVisualizations

Work efficienciesAnalysis and evaluation

Search

• VIVOsearch and CTSAsearch• VIVOsearchlight

• AgriVIVO – FAO of the UN

• Search across – Land Grant institutions– CTSA Consortium Schools– State university systems; Big 10, Big 12, etc.

http://vivosearchlight.org/@mileswortho

Visualizations!

http://xcite.hackerceo.org/VIVOviz/@hackerceo

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Make work easier

SPARQL Query Builder

Are you using Linked Open Data?

What are your hopes for this collection of technologies?

How can you get involved?

Open data, open tools, open process

Thank you!

Acknowledgements:• Carlo Torniai & Melissa Haendel – OHSU• Tony Williams – OpenPHACTS, RSC• CTSA Research Networking Affinity workgroup• VIVO Project