Creating, visualizing, curating and sharing text mining results

1. DOMEO ANNOTATION TOOLKIT
AND TEXT MINING
CREATING, VISUALISING, CURATING AND SHARING
TEXT MINING RESULTS
Paolo Ciccarese, PhD
paolo.ciccarese@gmail.com
January 30th 2012, W3C Scientific Discourse Call

2.  Domeo Annotation Toolkit is a collection of software
components that allow to create and share
annotation of web documents and their fragments
 It can export and exchange all the annotation in
Annotation Ontology (AO) RDF format
 The Domeo client is the user interface that can be
used to produce manual and semi-automatic
annotation of HTML documents directly in your
browser
http://annotationframework.org/

3. ANNOTATION ONTOLOGY
 OWL vocabulary for representing and sharing
annotation and semantic annotationof digital
resources and their fragments:
 Is orthogonal to the domain(s) of interest
http://purl.org/ao/home
 Supports Stand-off annotation
 Offers tools for identifying fragments
 Designed with extension points
 Defines basic annotation containers
 Supports versioning
 Tracks provenance

4. DOMEO AND TEXT MINING SERVICES
 Domeo allows to trigger text mining algorithms
when they are available through web services
 Software connectors have to be developed to
translate the results in a suitable format
 The results are displayed in the web documents
 Users can record their feedback/judgment through
customizable user interfaces

5. NCBO ANNOTATOR
http://www.bioontology.org/annotator-service
 Web service that annotates textual metadata (e.g.
journal abstract) with relevant ontology concepts
 It is possible to preselect the ontologies of interests
as one of the many parameters

6. DOMEO AND THE NCBO ANNOTATOR
http://www.bioontology.org/annotator-service
 Domeo allows automatic/manual annotation with
terms coming from selected ontologies managed by
the BioPortal

7. RUNNING NCBO ANNOTATOR
Additional text mining services
will be listed here

8. NCBO ANNOTATOR RESULTS IN DOMEO
List of recognized
entities

9. RESULTS CURATION
Customizable

10. CUMULATIVE RESULTS CURATION
 One item only
 All instances with the same text match
 All instances independently from the text match

11. SERIALIZATION IN AO/RDF

12. SOFTWARE CONNECTORS
At the current stage
 For each text mining service we have to write a
specific connector that normally is translating offset
and range into prefix and postfix
 And keep it up to date!

13. UIMA, CLEREZZA AND AO
OSS BASED INFRASTRUCTURE FOR TEXT MINING OVER
ONTOLOGIES
TommasoTeofili and Paolo Ciccarese
tommaso@apache.org

14. APACHE UIMA
 Architecturalframework for UIM
 OASIS standard
 Build, deploy and run text mining pipelines
 Scaling capabilities for large volumes of data
 NLP/TM algorithms wrapped as Analysis Engines
http://uima.apache.org/

15. UIMA TYPES
 Defining annotation domain in Typesystems
 Types and features are just declared
 Existing Typesystemscan be
imported/exported/enhanced
 Ease data exchange between AEs
 Two “main” types
 TOP
 Annotation

16. APACHE CLEREZZA
 Service platform for linked data
 OSGi-based
 RDF API
 RESTful Web Service Framework
 TripleStore independent
 Integrated with Apache UIMA
http://incubator.apache.org/clerezza/

17. UIMA/CLEREZZA CONVENTION
 devs can create custom types / typesystems
 need to manage URIs
 integration of services vs ontology sharing
 ClerezzaTypeSystem
 ClerezzaBaseAnnotation
 uri
 ClerezzaBaseEntity
 uri
 label (rdfs:label)
 references (annotations referring this entity)
 service specific annotations and entity types are defined
subclassing the above

18. CLEREZZABASEANNOTATION DESCRIPTOR

19. CLEREZZABASEENTITYDESCRIPTOR

20. BEFORE

21. AFTER (URI FIELD INHERITED)

22. CONVERSION STRATEGIES
 UIMA annotations stored inside CAS
 Services “talking” via webservices + RDF
 CAS to RDF mapping via Clerezza
 Pluggable mapping strategies
 Clerezza Default
 AnnotationOntology
 …

23. CONVERSION STRATEGIES
Change mapping strategies via XML/Eclipse plugin
Or in the descriptor directly
<nameValuePair>
<name>mappingStrategy</name>
<value><string>ao</string></value>
</nameValuePair>

24. CLEREZZA WEB SERVICES EXAMPLE

25. LOOKING AHEAD
DOMEO TOOLKIT V. 2
Paolo Ciccarese, PhD

26. DOMEO ANNOTATION TOOLKIT V.2
 DomeoAnnotation Toolkit v.2 is planned by the end
of the first quarter of 2012
 It will consist in major refactoring to improve
modularity and make plug-ins writing easier
 It will include various new features and will be the
first step towards a federated architecture
 It will be open source!

27. DOMEO FEDERATION
 We currently have two instances of the Domeo
Toolkit and the number of instances is going to
increase
 We need to define a clean architecture that
supports communication between instances or
nodes
 Instances should be able to access each other
annotations in multiple ways

28. Annotation Flow
Web Service
DOMEO FEDERATION Triplestore
Domeo Domeo Web Client
Web Client
Node 1 Node 2
SPARQL
Web Client
Domeo DomeoN
Node 3 ode 4
SPARQL
Ex: DT3 retrieves annotation from DT1 through a web service
and from DT2 through a SPARQL query against its triplestore

29. SOFTWARE ANNOTATION ACCESS
Nodes can access annotations of other nodes through
 Through Web Services
 Annotation by User
 Annotation by Group
 Annotation by Document
 Annotation by Corpora
 …
 SPARQL queries, when a SPARQL end-point is available

30. USERS ANNOTATION ACCESS
Users can export their own annotation in AO RDF
 Annotation by document
 Annotation by corpora
 All of the annotation

31. Request
CURRENT DOMEO ARCHITECTURE Annotation
Domeo
Web Client
AO-RDF
Annotation
Web Services
Domeo
User
MySQL Annotation
Export
Text Mining UI
Connector
NCBO
Web Service
NCBO
Annotator

32. DOMEO NODE ARCHITECTURE
> ACCESSING EXTERNAL ANNOTATION
Other 1 2
External
Domeo Domeo
Triplestore
Node Web Client
AO-RDF
SPARQL
AO-RDF AO-RDF
Annotation Triple Store
Web Services Connector
Domeo v.2 Node
User
MySQL Annotation
Export
Text Mining UI
Connector
NCBO
Web Service
NCBO
Annotator

33. DOMEO NODE ARCHITECTURE
> ADDING A SPARQL ENDPOINT
Other
External
Domeo Domeo
Triplestore
Node Web Client
AO-RDF
SPARQL
AO-RDF AO-RDF
Annotation Triple Store SPARQL
Web Services Connector
Triplestore
Domeo v.2 Node
User
MySQL Annotation
Export
Text Mining UI
Connector
NCBO
Web Service
NCBO
Annotator

34. DOMEO NODE ARCHITECTURE
> TEXT MINING ALGORITHMS INTEGRATION
Other 1
External
Domeo Domeo
Triplestore
Node Web Client
AO-RDF
SPARQL
AO-RDF AO-RDF
Annotation Triple Store SPARQL
Web Services Connector
Triplestore
Domeo v.2 Node
3 MySQL User
Annotation
Export
Text Mining Clerezza Text Mining UI
Connector Connector Connector
2 4
NCBO Clerezza Text Mining
Library
Web Service Web Service Manager
NCBO UIMA Text Mining
Annotator Algorithm Algorithm

35. DOMEO AND TEXT MINING
IN SUMMARY
 Run algorithms within Domeo
 Making available the algorithms through Web Services
 Integrating the algorithms - as libraries – within the
Domeo architecture.
 Run algorithms separately and then
 Load the results into a Domeo node through web
services
 Store the results directly in the (a) triplestore
 Store the results directly in the database

36. W3C COMMUNITY GROUP
OPEN ANNOTATION
 Annotation Ontology (AO) and Open Annotation
Collaboration (OAC) are merging
 Unified model for representing and sharing
annotation in RDF
http://www.w3.org/community/openannotation/

37. THANK YOU!
If you are interested in using - or contributing to -
the Domeo Annotation Toolkit follow our website
http://annotationframework.org or contact
paolo.ciccarese -at- gmail.com