CONCEPTUALIZATION AND VISUAL KNOWLEDGE ORGANIZATION: A SURVEY OF ONTOLOGY-BASED SOLUTIONS
1 Hungarian Academy of Sciences and MMATT Ltd. (HUNGARY)
2 WikiNizer (UNITED KINGDOM)
About this paper:
Appears in:
INTED2014 Proceedings
Publication year: 2014
Pages: 4609-4619
ISBN: 978-84-616-8412-0
ISSN: 2340-1079
Conference name: 8th International Technology, Education and Development Conference
Dates: 10-12 March, 2014
Location: Valencia, Spain
Abstract:
Conceptualization and Visual Knowledge Organization are overlapping research areas of Intellect Augmentation with hot topics at their intersection which are enhanced by proliferating issues of ontology integration (matching, alignment, merging, mapping, revision, dynamic evolution). Knowledge organization is more closely related to the content of concepts and to the actual knowledge items than taxonomic structures and ‘ontologies’ understood as “explicit specifications of a conceptualization” (Gruber). Yet, the alignment of the structure and relationship of knowledge items of a domain of interest require similar operations. This paper is a reconsideration of ontology-based approaches to collaborative conceptualization from the point of view of user interaction in the context of augmented visual knowledge organization. Until recently, ontology engineering proceeded either by expert-based or automated/semi-automated methods of Knowledge-based Systems for solving problems of conceptualization and ontology reconciliation for the Semantic Web. Human-Agent Negotiation techniques and protocols came to the fore partially as a result of the poor record of automatic ontology generation and partly as a reaction to the rise of new issues of collective conceptualization in emergent semantics. The requirements of live visualization and collaboration for a wiki-like concept organizer of a global giant graph knowledge base, called “Conceptipedia”, emerging concepts and their intellectual manageability become central issues. After considering several formal ontology based approaches, alternative matching operations are discussed and a new approach is proposed that is based on the traversal frequency and the dynamics of the concept lattice. It is argued that negotiation games played at the meta-level of knowledge items supported by a reputation system mechanism can support emergent conceptualization until workable ideas win out and taxonomic structures are settled. Conceptualization can be improved by social interaction, cooperative learning and through collaborative sense-making. Consequently, co-evolving visualization of concepts and learning objects are needed both at the object and meta-level to handle the social aspects of learning and knowledge work in the framework of an Exploratory Epistemology. Current systems tend to separate the conceptual level from the content, and the context of logical understanding from the intent and use of concepts. Besides, they usually consider the unification of individual contributions in an ubiquitous global representation. As opposed to this God's eye view we are exploring new alternatives that aim to provide Morphic-like live, tinkerable, in situ visualization and direct manipulation based authoring capabilities. They are uniformly applicable and user-extendable through meta-design both at the content, as well as all emergent conceptual meta-levels, within the collaborative framework of Conceptipedia. Morphic integrates verbal and pictorial models of conceptualization in its graphics system of intentful workflows as flexible, reusable building blocks for collaborative work. Distributing the workload and responsibility through Crowd Authoring, concept alignment and contributions from an online community filters out errors and misconceptions. This way, challenges of social and collaborative concept matching can be addressed in a knowledge management kernel that is also capable to supplement education technology.Keywords:
Conceptualization, Visual Knowledge Organization, Exploratory Epistemology, Ontology Engineering, Ontology Integration, Traversal Frequency, Concept Lattice.