SWAN/SIOC: Aligning Scientific Discourse Representation and Social Semantics

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SWAN/SIOC Aligning Scientific Discourse
Representation and Social Semantics

• Alexandre Passant1, Paolo Ciccarese2, 3, John G.
  Breslin4, Tim Clark2, 3
• 1 DERI, NUI Galway, Ireland 2 Massachusetts
  General Hospital, Boston, USA
• 3 Harvard Medical School, Boston, USA 4 School of
  Engineering and Informatics, NUI Galway, Ireland

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Motivation

• To provide a complete RDF-based model to model
  online activities and scientific argumentation in
  neuromedicine
• Combining Web 2.0 shared knowledge using SIOC and
  formal scientific data (hypotheses, claims,
  dialogue, evidence, publications, etc.) via SWAN
• To make (both formal and informal) discourse
  concepts and relationships more accessible to
  computation
• So that they can be better navigated, compared
  and understood both across and within domains

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How is this achieved?

• An alignment of ontologies was performed to
  provide a complete framework for modelling
  activities in scientific communities
• SWAN objects were integrated into SIOC Types
  module
• SWAN was reused to model argumentative
  discussions
• External models such as SCOT and MOAT were reused
  for tagging
• SCF is being updated so that it can create data
  according to this model

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Collaborative websites are like data silos
Source Pidgin Technologies, www.pidgintech.com
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Many isolated communities of users and their data
Source Pidgin Technologies, www.pidgintech.com
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Need ways to connect these islands
Source Pidgin Technologies, www.pidgintech.com
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Allowing users to easily move from one to another
Source Pidgin Technologies, www.pidgintech.com
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Enabling users to easily bring their data with
them
Source Pidgin Technologies, www.pidgintech.com
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Types of data silos (scientific and social)

• Collaborative websites used by scientific
  researchers in various domains
• SWAN/SCF is being used to connect these
• Social websites used by people collaborating or
  communicating through the Web 2.0 platform
• SIOC is being used to connect these
• SWAN/SIOC connects both sets of data silos
  together, not just structures but what is
  embedded within content as well

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SWAN (Semantic Web Applications in Neuromedicine)

• An ontology of scientific discourse (Ciccarese et
  al. 2008)
• A participatory knowledge base of hypotheses,
  claims, evidence and concepts in biomedicine,
  with the first instance in the domain of
  Alzheimers disease (AD)
• Currently being integrated with the SCF (Science
  Collaboration Framework) toolkit for biomedical
  web communities
• http//swan.mindinformatics.org/

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What does SWAN consist of?

• A formal structure to record and present
  scientific discourse
• Tools for scientists to manage, access and share
  knowledge
• Tools for discovering conflicts, gaps and missing
  evidence
• An information bridge to promote collaboration
• A community process built upon the Alzforum site

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Main concepts and relationships in the SWAN
ontology
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Modules in the SWAN ontology
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A typical hypothesis
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Contributions from leading researchers
Inventory of ideas
Mechanisms of disease
Key research topics
Contribute content
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Scientist view Toxic protein fragments believed
responsible for AD Key information, gaps and
conflicts
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Browsing evidence and inconsistencies

• New experiment required?

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A researcher-supported effort

• Dozens of etiopathological AD models annotated by
  SWAN curators in collaboration with leading
  researchers
• Content reviewed before release by over twenty
  senior AD researchers
• Software features reviewed before release by over
  thirty senior AD researchers
• Extensive feedback incorporated into SWAN, such
  that this is a community tool (in line with Web
  2.0 principles)

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Semantically-Interlinked Online Communities (SIOC)

• An effort from DERI, NUI Galway to discover how
  we can create / establish ontologies on the
  Semantic Web
• Goal of the SIOC ontology is to address
  interoperability issues on the (Social) Web
• http//sioc-project.org/
• SIOC has been adopted in a framework of 50
  applications or modules deployed on over 400
  sites
• Various domains Web 2.0, enterprise information
  integration, HCLS, e-government

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The steps taken

• Develop an ontology of terms for representing
  rich data from the Social Web
• Create a food chain for producing, collecting and
  consuming SIOC data
• As well dissemination via papers about SIOC,
  provide docs and examples at sioc-project.org
• SIOC aims to enrich the Web infrastructure
• During the next upgrade cycle, gigabytes of
  semantically-enriched community data become
  available!

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Some of the SIOC core ontology classes and
properties
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Some examples of where SIOC is already use (about
50 applications / modules)
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Creating a Social Semantic Web of
previously-disconnected social data silos
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Also integrating scientific data silos in a
semantic scientific collaboration framework

• Enabling researchers to
• Collect data
• Draw conclusions
• Gather information
• Create/modify hypotheses
• Perform experiments
• But with the benefit of cross-community and
  cross-domain experiences and results

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Mappings between SWAN and SIOC at
http//rdfs.org/sioc/swan in OWL-DL
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Mappings between SWAN and SIOC classes

• Subclasses of siocItem
• swanscidisDiscourseElement
• swanscidisResearchStatement
• swanscidisResearchQuestion
• swanscidisResearchComment
• swancitCitation
• swancitJournalArticle
• Other mappings
• siocPost gt swancitWebArticle, swancitWebNews
• siocComment gt swancitWebComment

• swanscidis is the Scientific Discourse module,
  which provides a set of classes and properties to
  represent discourse elements
• swancit is the Citations module, which aims to
  model the various citation elements that occur in
  scientific publishing

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Mappings between SWAN and SIOC properties

• Subtypes of siocrelated_to
• swandisrelagreesWith / swandisreldisagreesWith
• swandisrelalternativeTo
• swandisrelarisesFrom
• swandisrelcites
• swandisrelconsistentWith / swandisrelinconsisten
  tWith
• swandisreldiscusses
• swandisrelinResponseTo
• swandisrelmotivatedBy
• swandisrelrefersTo

• swandisrel is the Scientific Discourse
  Relationships module, which collects some of the
  relationships used for modelling discourse
• May also use siocItem dctermshasPart
  swanscidisDiscourseElement, for example, to
  represent that a particular hypothesis is part of
  a blog post

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Mappings redundancy

• Redundant mappings
• Can be entailed thanks to the transitivity of
  rdfssubClassOf / rdfssubPropertyOf
• e.g. swancitJournalArticle rdfssubClassOf
  siocitem can be inferred from
  swancitJournalArticle rdfssubClassOf
  swancitCitation and swancitCitation
  rdfssubClassOf siocItem
• However
• SIOC applications generally do not support such
  chained entailments
• Need to address lightweight inference
• Therefore we provide direct rdfssubClassOf
  mappings

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Querying mappings
PREFIX sioc lthttp//rdfs.org/sioc/nsgt SELECT
DISTINCT ?s ?o WHERE ?s siocrelated_to ?o . ?s
a siocItem . ?o a siocItem .

• Simple query to identify relatedness between
  items
• Applying a SIOC query over SWAN data
• SPARQL / Pellet, files loaded on runtime in
  memory
• Experiment with both simple mappings (including
  transitive closure) and full mappings

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W3C HCLS Interest Group notes published

• http//www.w3.org/TR/hcls-sioc/
• http//www.w3.org/TR/hcls-swan/
• http//www.w3.org/TR/hcls-swansioc/

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RDFa support in Drupal 7 for SSW data
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Exposing scientific results to search

• Yahoo! Search Monkey and Google Rich Snippets
• Highlights the structured data embedded in web
  pages
• Google developers have indicated that scholarly
  publications marked up with Rich Snippets will
  also be picked up and appropriately indexed by
  Google Scholar

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Acknowledgements

• We would like to thank Science Foundation Ireland
  for their support under grant SFI/08/CE/I1380
  (Líon 2)
• We would also like to thank an anonymous
  foundation for a generous gift in support of this
  work
• Thanks to members of the W3C HCLSIG, in
  particular
• Susie Stephens
• Scott Marshall
• Eric Prudhommeaux

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Motivation

• To provide a complete RDF-based model to model
  online activities and scientific argumentation in
  neuromedicine
• Combining Web 2.0 shared knowledge using SIOC and
  formal scientific data (hypotheses, claims,
  dialogue, evidence, publications, etc.) via SWAN
• To make (both formal and informal) discourse
  concepts and relationships more accessible to
  computation
• So that they can be better navigated, compared
  and understood both across and within domains