CITATION: Smart Administrations in the Healthcare Sector

Abstract

CITATION (Citizen Information Tool in smart administrATIONs) provides an innovative information platform for improving and promoting the provision of electronic information in the health sector, ensuring that citizens have easy and direct access to essential public data (administrative procedures, legislation and available services). The system delivers mechanisms for the effective management, customization and flexible delivery of administrative information. CITATION embraces the initiative and effort to provide and promote health-related administrative information, in the framework of local or national government services. It facilitates the creation of `smart' governmental structures, capable of providing citizens with customized, added-value services. CITATION emphasizes its efforts in the advancement and integration of current state-of-the-art information technologies, with emphasis on knowledge engineering and semantics analysis. CITATION introduces models that allow for adequate representation of the semantics of the existing healthcare administrative information content.

References

1 Green Paper. Public sector information: a key resource for Europe.

2 Gustafson D, Robinson T N, Ansley D, Adler L, Brennan P F. Consumers and evaluation of interactive health communication applications. The Science Panel on Interactive Communication and Health . American Journal of Preventative Medicine 1999; 16: 23-29 .

3 Eysenbach G. Consumer health informatics . BMJ 2000; 320: 1713-1716 .

4 Eng T, Gustafson D. Wired for health and wellbeing; the emergence of interactive health communication. The Science Panel on Interactive Communication and Health. US Department of Health and Human Services, US Government Printing Office. Ref type: Report.

5 Pattrik K, Koss S. White Paper: Consumer health information.

6 Ganter B, Wille R. Formal concept analysis: mathematical foundations. New York: Springer , 1999.

7 Bateman J A. Ontology construction and natural language. Proc Int Formal Ontology and KR, 1993.

8 Thomas R.Gruber. A translation approach to portable ontology specifications. Knowledge Acquisition 1993; 5 (2): 199-220 .

9 Guarino N, Giaretta P. Ontologies and knowledge bases: towards a terminological clarification. In: N J I Mars (ed.) Towards very large knowledge bases. Amsterdam: IOS Press , 1995, pp. 25-32.

10.

10 Karp P, Chaudhri V, Thomere J. XOL: An XML-based ontology exchange language, 1999.

11.

11 Baclawski K, Cigna J, Kokar M, Mager P, Indurkhya B. Knowledge representation and indexing using the unified medical language system. http://www.jarg.com (accessed 20 january 2002). 20 January 2002.

12.

12 Leroy G, Chen H. Meeting medical terminology needs - the ontology-enhanced medical concept mapper . IEEE Transactions on Information Technology in Biomedicine 2001, 4 (4): 261-270 .

13.

13 Schweighofer E, Rauber A, Dittenbach M. Automatic Text Representation, classification and labeling in European Law . In: Proceedings of the International Conference on Al and Law 21-25 May, 2001, St Louis, MI.

14.

14 Dittenbach M, Merkl D, Rauber A. Hierarchical clustering of document archives with the growing hierarchical self-organising map . In: Proceedings of the International Conference on Artificial Neural Networks (ICANN01), 21-25 August 2001, Vienna, Austria.

15.

15 Klein M, Fensel D. Ontology versioning on the semantic web.

16.

16 Erdmann M, Studer R. How to structure and access XML documents with ontologies. Data and Knowledge Engineering (special issue on intelligent information integration).

17.

19 Cognitive science laboratoryIPrinceton UniversityI221 Nassau St. IPrinceton, nj08542, WordNet. http://www.cogsci.princeton.edu/~wn/online/ (accessed 27 January 2002).

18.

20 Dr Piek Vossen, Department of Computational Linguistics, University of Amsterdam, Euro WordNet. http://www.hum.uva.nl/~ewn/ (accessed June 1999).

19.

21 Box D (DevelopMentor), Ehnebuske D (IBM), Kakivaya G (Microsoft), Layman A (Microsoft), Mendelsohn N (Lotus), Frystyk Nielsen H (Microsoft), Thatte S (Microsoft), Winer D (UserLand Software). http://www.w3.org/TR/SOAP/

20.

22 Shaw W M Jr, Burgin R, Howell P. Performance standards and evaluations in IR test collections: vector space and other retrieval models . Information Process Management 1997; 33 (1): 1244-1245 .

21.

23 Hahn U, Romacker M, Schultz S. How knowledge drives understanding - matching medical ontologies with the needs for medical language processing . Artificial Intelligence in Medicine 1999; 15: 25-51 .

22.

24 Voorhees E M. Using WordNet to disambiguate word senses for text retrieval . In: Proceedings 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval and Linguistic Analysis, 27 June-1 July 1993, Pittsburgh, PA, pp. 171-180 .

23.

25 Carvalho Moura A M, Machado Campos M L, Barreto C M. A metadata architecture to represent electronic documents. http://computer.org/proceedings/meta/1999/papers/15/amoura.html (accessed 1999).

24.

26 Hillmann D. Using Dublin Core. http://dublincore.org/documents/2001/04/12/usageguide/ (accessed 2001).