An Ontology Driven Approach to Improve the OpenSocial Standard

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

Problem

Introduction NIH Grant Match* and Recommended Reading* Gadgets using

researcher data obtained with different custom API’s

• Science 2.0 is happening, and Research Networking Tools such as

Profiles, VIVO, SciVal Experts and others have become

commonplace throughout our institutions.

• Our Research Networking Tools fulfill a need that can not be met by

commercial social networking sites such as LinkedIn, Facebook and

Google+ because we need institutional provenance for our data

content and first class support for our data model.

• Commercial social networking sites have become platforms. This

allows them to leverage numerous development communities and

more rapidly deliver innovative functionality.

• Our Research Networking Tools should also become platforms. We

believe that delivering more functionality more quickly to our

researchers will increase productivity and accelerate science.

DIRECT Match Gadget using researcher

data obtained with VIVO RDF via JSON

Browser

Babel

OpenSocial with RDF/XML converted to JSON via Simile Babel

Approach

Gadget Content Gadget Hosting Servers

http://anywhere/gadget.xml

RD

F/X

ML

HTML Content

OR*

JSON Domain Data

Domain Object Request

Acknowledgments

This project was supported by NIH/NCRR UCSF-CTSI Grant Number

UL1 RR024131 and Harvard Catalyst Grant Number 1 UL1 RR025758-

01. Its contents are solely the responsibility of the authors and do not

necessarily represent the official views of the NIH.

We would like to thank Andy Bowline of Wake Forest, MIT Libraries and

MIT CSAIL as well as all other contributors to the SIMILE Project.

We also want to thank Andy Smith and the OpenSocial Foundation.

• Converting a web site to a web platform is not trivial. It can be done

independently by a large software development team, or it can be

done by leveraging existing open source solutions such as Apache

Shindig.

• The software resources available to our institutions are limited as

compared to a recognizable commercial site such as Facebook or

LinkedIn. Apache Shindig, which is based on the OpenSocial

standard, is the more attractive if not only viable solution.

• The OpenSocial standard does not have first class support for our

data model. Fortunately OpenSocial is extendable and this gives us

an opportunity to address our specific data model needs.

* Successfully tested with VIVO (ask for demo!) but not yet implemented.

Gadget

Specification

Backend Services

Request Proxy

* Built by Andy Bowline of the

Wake Forest School of Medicine.

• Manually extending OpenSocial with custom fields to match our data

model was always an option but an expensive one from a

development perspective and a flawed one because customization

breaks interoperability.

• Convergence towards RDF and the VIVO ontology across our

Research Networking Tools presented an opportunity. With a

standard ontology we now have a standard way to express our data,

but how can we integrate the VIVO ontology into OpenSocial?

• OpenSocial works well with JSON but not with any standard

serialized forms of RDF such as RDF/XML or Turtle. A standard

means of converting RDF to JSON was required.

Next Steps

• Integrate our solution into the RDF based version of Profiles and

make our code available to the open source community.

• Promote our solution to the OpenSocial Foundation. Other verticals

are suffering from the same domain based data model issues with

OpenSocial that we encountered in bioinformatics.

• Get you to help us build our community for Open Research

Networking Gadgets (ORNG) at http://opengadgets.org!

Solution

• An open source product called Babel which was developed by the

MIT Simile Project was discovered. Babel provides many data

translation services, including RDF/XML to JSON.

• A proof of concept system was created by integrating the production

UCSF Profiles code with pre-release VIVO compliant Profiles code,

and integrating Babel with Apache Shindig.

• The DIRECT Match Gadget was built to test the proof of concept

system. It worked! It has also been successfully unit tested with

RDF/XML from various external VIVO compliant sources.

The.

Ontology.

RDF/XML converted to JSON for Griffin Weber