@article {Katifori2007,
	title = {Ontology visualization methods - A survey},
	journal = {ACM Computing Surveys},
	volume = {39},
	number = {4},
	year = {2007},
	note = {cited By (since 1996) 21},
	pages = {10:1-10:43},
	abstract = {Ontologies, as sets of concepts and their interrelations in a specific domain, have proven to be a useful tool in the areas of digital libraries, the semantic web, and personalized information management. As a result, there is a growing need for effective ontology visualization for design, management and browsing. There exist several ontology visualization methods and also a number of techniques used in other contexts that could be adapted for ontology representation. The purpose of this article is to present these techniques and categorize their characteristics and features in order to assist method selection and promote future research in the area of ontology visualization. Β{\textcopyright} 2007 ACM.},
	keywords = {Digital libraries, Human computer interaction, Information management, Ontology, Ontology representation, Ontology visualization, Personalized information management, Semantic Web, visualization methods},
	doi = {10.1145/1287620.1287621},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-36048959880\&partnerID=40\&md5=a74cd76829bee9bb1cc21d6118e65340},
	author = {Akrivi Katifori and C. Halatsis and Giorgos Lepouras and Costas Vassilakis and E.G. Giannopoulou}
}
@conference {Golemati200662,
	title = {A context-based adaptive visualization environment},
	booktitle = {Proceedings of the International Conference on Information Visualisation},
	year = {2006},
	note = {cited By (since 1996) 0},
	month = {7},
	pages = {62-67},
	abstract = {Digital libraries and historical archives are increasingly employing visualization systems to facilitate the information retrieval and knowledge extraction tasks of their users. Typically, each organization employs a single visualization system, which may not suit best the needs of certain user groups, specific tasks, or properties of document collections to be visualized. In this paper we present a context-based adaptive visualization environment, which embeds a set of visualization methods into a visualization library, from which the most appropriate one is selected for presenting information to the user. Methods are selected by examining parameters related to the user profile, system configuration and the set of data to be visualized, and employing a set of rules to assess the suitability of each method. The presented environment additionally monitors user behavior and preferences to adapt the visualization method selection criteria. Β{\textcopyright} 2006 IEEE.},
	keywords = {(PL) properties, Adaptive systems, Adaptive visualization, Behavioral research, Digital libraries, document collections, Extraction, Information analysis, Information science, Information services, Information systems, Information visualization, Knowledge extraction, Libraries, Retrieval (MIR), Search engines, Selection criterion, Set of rules, Solvent extraction, Specific tasks, System configurations, User behaviors, User groups, user profiling, Visualization, visualization methods, Visualization systems},
	doi = {10.1109/IV.2006.5},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-45149121827\&partnerID=40\&md5=ec45ad555b132faaf0bd2ca53e3292dc},
	author = {M. Golemati and C. Halatsis and Costas Vassilakis and Akrivi Katifori and Giorgos Lepouras}
}
