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Semantic and pragmatic annotation for government information discovery, sharing and collaboration
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ACM International Conference Proceeding Series; Vol. 390 archive
Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government table of contents
SESSION: Knowledge management and collaboration table of contents
Pages 199-205  
Year of Publication: 2009
ISBN:978-1-60558-535-2
Authors
Janice Warner  Georgian Court University, Lakewood, NJ
Soon Ae Chun  City University of NY, Staten Island, NY
Sponsor
: Digital Government Society of North America
Publisher
Bibliometrics
Downloads (6 Weeks): 20,   Downloads (12 Months): 69,   Citation Count: 0
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ABSTRACT

Collaboration and information sharing between organizations that share a common goal is becoming increasingly important. Effective sharing promotes efficiency and productivity as well as enhances customer service. With Internet connectivity widely available, sharing and access to information is relatively simple to implement. However, the abundance causes another problem - the difficulty of determining where truly useful and relevant information is housed. Information resources, such as data, documents, multimedia objects and services stored in different agencies need to be easily discovered and shared. We propose a collaborative semantic and pragmatic annotation environment where resources of each agency can be annotated by users in the government social network. This collaborative annotation captures not only the semantics but also the pragmatics of the resources, such as who, when, where, how and why the resources are used. The benefits of semantic and pragmatic annotation tags will include an ability to filter, discover and search new and dynamic as well as hidden resources, to navigate between resources in a search by traversing semantic relationships, and to recommend the most relevant government information distributed over different agencies. A distributed architecture of a tagging system is shown and tag-based search is illustrated.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Janice Warner: colleagues
Soon Ae Chun: colleagues