1. © 2008, Sam Chapman, K-Now and the University of Sheffield 1 1 Creating and Using Organisational Semantic Webs in Large Networked Organisations Ravish Bhagdev 1,2, Ajay Chakravarthy 1, Sam Chapman 1,2, Fabio Ciravegna 1,2 and Vita Lanfranchi 1 12 University of Sheffield, UK {N.Surname}@shef.ac.uk Knowledge Now Limited, UK {Name}@k-now.co.uk

2. © 2008, Sam Chapman, K-Now and the University of Sheffield 2 Outline  Traditional Knowledge Management  What is problematic?  Large Networked Organisations  What are the organisational needs?  Knowledge Acquisition  Forms as Ontologies  Form-based Knowledge Capture  Knowledge Sharing and Reuse  Conclusions

3. © 2008, Sam Chapman, K-Now and the University of Sheffield 3 Traditional KM  Enterprise Knowledge Portal  providing unique standardized access to proprietary knowledge  Single Conceptual Schema for official agreed view  supporting communication between different parts of organisation  Large homogeneous knowledge or document repositories  for collection and organisation of corporate knowledge

4. © 2008, Sam Chapman, K-Now and the University of Sheffield 4 Traditional KM: Issues  Effect:  Many portals are deserted by users  replacements: non-official tools such as shared directories, personalized and local databases, email, etc.  Reason:  Difficulty in adopting models, schemas and procedures  that are unsuitable to specific communities of users  that are not dynamic

5. © 2008, Sam Chapman, K-Now and the University of Sheffield 5 Large Networked Organisations  Modern KM is based on dynamic communities  that acquire and share knowledge according to dedicated schemas  existing across traditional organisational boundaries  ill fit pre-determined standard schemas  require rapidly tailoring knowledge for their specific ad-hoc uses  often outside the company (outsourcing) Organisation2 Organisation1

6. © 2008, Sam Chapman, K-Now and the University of Sheffield 6 Modern KM principles  Principle of Autonomy  where each unit is granted a high degree of autonomy to manage their local knowledge;  Principle of coordination  where units are enabled to exchange knowledge with other units through a mechanism of mapping other units’ context onto their local context. Bonifacio et al, 2002

7. © 2008, Sam Chapman, K-Now and the University of Sheffield 7 Challenge: support communities in capturing knowledge  Do not force communities to share a single company-wide (ontological) view  Help them define a neat, formal, shareable, individual ontological view  that can be connected to other views  although connections can be imperfect  some is better than nothing

8. © 2008, Sam Chapman, K-Now and the University of Sheffield 8 Challenge: support communities in sharing and reusing knowledge  Distributed interconnected resources  can be queried across via interconnected ontologies  Searching metadata rather than text  Retrieving information independently from the store/media  Enables querying resources using my ontological view  largely independently from the view used originally to create it

9. © 2008, Sam Chapman, K-Now and the University of Sheffield 9 Semantic Web for Networked Communities  Enables freedom for communities  definition of community-specific views of the world;  capture and acquisition of knowledge according to them;  easy networked modification of the knowledge schema  Enables sharing with other communities  integration with the rest of the organisation’s knowledge;  via integration of ontologies  definition and reuse of different views on the same data great number of small ontological components consisting largely of pointers to each other

10. © 2008, Sam Chapman, K-Now and the University of Sheffield 10 Our proposal:  Integrate knowledge acquisition, capturing and sharing  K-Forms  Form based User centred community specific view  definition of knowledge structures, i.e. the ontology  creation of instances, i.e. triples  K-Extraction  Legacy data capture  K-Search  searching and sharing of information and knowledge.

11. © 2008, Sam Chapman, K-Now and the University of Sheffield 11 KNOWLEDGE ACQUISITION AND CAPTURE K-Forms

12. © 2008, Sam Chapman, K-Now and the University of Sheffield 12 K-Forms  Users define Web based forms visually using a Web browser  Forms  Tables  Selections  Lists  Conceptual type  Possible values  Validation required  etc.  Same freedom as Word/Excel forms  Flexible creation/modification of knowledge schema

13. © 2008, Sam Chapman, K-Now and the University of Sheffield 13 Sharing among forms  When a form is created parts of other forms are suggested intelligently for reuse  to help users:  create forms consistently without forgetting anything  reduce time (saves specifying all details)  encourage sharing and linkage  People tend to develop new forms starting from an existing form and reuse components from others

14. © 2008, Sam Chapman, K-Now and the University of Sheffield 14 FORMS AS ONTOLOGIES The technical view

15. © 2008, Sam Chapman, K-Now and the University of Sheffield 15 Forms as ontologies  The form schema is turned automatically into an explicit ontology  Objects are OWL concepts  Properties are  OWL properties if filler is base type  OWL Relations if filler is a nested object  Forms can be divided into sections and fields. 15

16. © 2008, Sam Chapman, K-Now and the University of Sheffield 16 Sections  Sections can have subsections and fields  are presented as sub-forms to be filled.  Sections are represented as OWL classes ( Class)  which can have subsections (related classes)  or individual fields (properties)

17. © 2008, Sam Chapman, K-Now and the University of Sheffield 17 Fields  Fields are typed  represent meta-properties of the document (e.g. author, date, etc.)  or its content (e.g. an issue to be reported).  Fields can be added as a property of each section, subsection, or directly in form classes  they are represented as OWL properties.  Restrictions can be set for the possible values of the using xml datatype schema (xsd:types)

18. © 2008, Sam Chapman, K-Now and the University of Sheffield 18 Semantic interconnections  Relations among concepts are represented as OWL relations between classes and properties  Relational tables can be represented as advanced sections.  The domain of some relations may be the overarching Class.  When concepts are introduced at the top level, a relation is formally created domain Class and range Class.

19. © 2008, Sam Chapman, K-Now and the University of Sheffield 19 Linking ontologies  When part of form is reused,  underlying ontology matching tool imports OWL concepts, relations and properties  This creates a semantic web of ontologies  all the SW technologies used for managing distributed ontologies apply  e.g. distributed searching FormA Person Name... Feedbac k... FormA Person Name... Feedbac k... FormA Person Name... Feedbac k FormAVehicle Person Name... Feedba ck...

20. © 2008, Sam Chapman, K-Now and the University of Sheffield 20 FORM-BASED KNOWLEDGE CAPTURE The technical view

21. © 2008, Sam Chapman, K-Now and the University of Sheffield 21 Knowledge Capturing  When a form is released users receive it to fill  capture locally(no intranet connection)  upload to central repository in a later time  Final Word/Excel document automatically generated  Can be read and printed and sent by email  as before  Knowledge immediately available for search on the intranet

22. © 2008, Sam Chapman, K-Now and the University of Sheffield 22 Filling forms  Semantics are assigned to the field values  All the inputted values are transformed into RDF statements related to the form ontology  Filling forms creates RDF triples  Different types of documents can be generated from the triples FormA Person Name...Feedback...

23. © 2008, Sam Chapman, K-Now and the University of Sheffield 23 How about Legacy Data?  Legacy data in unstructured sources must be recovered  Access to knowledge captured with K- Forms must be seamlessly integrated with that extracted from legacy data (when possible)  Requirement: extracting information from existing forms  Method:  Use of automatic semantic annotation techniques  Mainly from Information Extraction from text

24. © 2008, Sam Chapman, K-Now and the University of Sheffield 24 KNOWLEDGE SHARING AND REUSE K-Search

25. © 2008, Sam Chapman, K-Now and the University of Sheffield 25 K-Search  Ontology based search for documents and knowledge  Seamlessly searching forms and knowledge extracted  Fully integrated with K-Forms & K-Extraction  Ontology associated to a form is made available to K- Search

26. © 2008, Sam Chapman, K-Now and the University of Sheffield 26 Hybrid Search  Keywords and ontology-based search can be mixed within the same query  Pure ontology-based searching  When metadata covers information precisely  Keyword-in-context of annotation  To match strings in text annotated with semantics (textual form fields)  e.g. “fuel” is matched only on snippets of texts annotated as removed parts  General Keyword querying  For searching on the document/form as a whole Vitaveska Lanfranchi, Ravish Bhagdev, Sam Chapman, Fabio Ciravegna, Daniela Petrelli: Extracting and Searching Knowledge for the Aerospace Industry, in Proc. of 1st European Semantic Technology Conference, Vienna, May 2007

27. © 2008, Sam Chapman, K-Now and the University of Sheffield 27 Support for dynamic communities  K-Search enables searching multiple repositories at once using one of the available ontologies  Query a specific resource via the original ontology  Query a resource using a different ontology interconnected to the original one  Query multiple repositories using one specific ontology.

28. © 2008, Sam Chapman, K-Now and the University of Sheffield 28 Support for dynamic communities  When an ontology different from the original is used  the original query is mapped to the original ontology via the formal links.  For the parts that are not mapped the restrictions can be turned into keywords

29. © 2008, Sam Chapman, K-Now and the University of Sheffield 29 Bookmarking in Search

30. © 2008, Sam Chapman, K-Now and the University of Sheffield 30 Bookmarking (ctd)

31. © 2008, Sam Chapman, K-Now and the University of Sheffield 31 © 2008, Sam Chapman, K-Now and the University of Sheffield User Evaluation: K-Forms  6 Users from our university  Users reused in average 60% of the possible concepts.  Many individual variations, with a peak of 80% and a minimum of 30% concepts reuse.  All the users happily reused their own concepts  Reuse of concepts was appreciated by 90% of the users as it saves time  Users found easy or very easy (66.7% ) to design a form using the system (33.3 % rated it average)  Industrial:  Rolls-Royce forms, + (all k-now) + weknowit

32. © 2008, Sam Chapman, K-Now and the University of Sheffield 32 © 2008, Sam Chapman, K-Now and the University of Sheffield User Evaluation: K-Search  32 Users at Rolls-Royce plc  Finalist at Rolls-Royce directors’ creativity award STANDARDISED EVALUATION ISO DIS 9241-11

33. © 2008, Sam Chapman, K-Now and the University of Sheffield 33 © 2008, Sam Chapman, K-Now and the University of Sheffield Conclusions  K-Forms and K-Search provide support for KM in dynamic communities  K-Forms enables the intuitive design and deployment of web-based forms that capture semantic information.  K-Search enables accessing multiple repositories using multiple ontologies  K-Forms and K-Search satisfy modern KM supporting  Principle of Autonomy  Principle of coordination

34. © 2008, Sam Chapman, K-Now and the University of Sheffield 34 © 2008, Sam Chapman, K-Now and the University of Sheffield Future Work  Further development of the concept of the networked ontologies and their impact on knowledge management.  Explore the impact of changes to the existing form schema when some forms have been already filled.  Industrial Applications  2 projects: Support to design and manufacturing of Rolls Royce Engine for Airbus 350  International Procurement Analysis  Sports & Entertainments Industry Customer Management

35. © 2008, Sam Chapman, K-Now and the University of Sheffield 35 Acknowledgments.  The work was supported by :  IPAS, a project jointly funded by the UK DTI (Ref. TP/2/IC/6/I/10292) and Rolls-Royce plc and  X-Media, an Integrated Project on large scale knowledge management across media, funded by the European Commission as part of the IST programme (IST-FP6-026978), (www.x-media-project.org). All images © (K-Now or Rolls Royce)

36. © 2008, Sam Chapman, K-Now and the University of Sheffield 36 Thank you and Questions? sam@k-now.co.uk