1. by ANDREW ZITZELBERGER A Framework for Extraction Ontology Based Information Management

2. Problem Scientific Research  Wide range of documents  Require high precision (on extraction)

3. Solution Proposed Solution  Develop a tool for semi-automatic “pay-as-you-go” information extraction and integration that provides incrementally improved querying. Evaluation  Compute accuracy of the suggestions  Time saved using bootstrapped ontologies

4. Data Co-existence Data Integration Systems  Require semantic integration Dataspace Systems  Data co-existence approach  Immediate functionality  “pay-as-you-go” improvement

5. Dataspaces User Interface -Form Builder -Suggestions -Queries -Ontos -FOCIH -Schema Mapping - Meta-data - Keyword Search

6. System Local Storage - Set of Extraction Ontologies Form Builder – Hand annotation Personal Assistant - Suggestions for improvement Querying - Free form queries

7. Ontology

8. Forms Structure Keywords Values

9. Suggestions WordNet Data Frame Library RegExLib

10. Suggestions Reuse extraction ontology set (Ontos, FOCIH) Possible schema matching (Li Xu)

11. Contributions Framework for research focused semi-supervised data extraction and management Heuristics for computing suggestions based on regular expressions