IS 2000 Kees Van Hemmen

This week in IS2000 we largely discussed ontologies. An ontology is the design of formal conceptual structures for a given domain of inquiry. The objective of ontologies, and building them, is to represent abstract, real world physical concepts and their relations in a tangible manner. OOIs represent ontologies within and with regard to information systems. Ontologies describe entities, their attributes, and the relationships between them. Entities are things, physical objects, and abstract concepts. Attributes are properties of entities, as well as measurements of quantitative data with regard to them. Examples of relationship matrices include taxonomies, partonomies and associations. Multiplicities and cardinalities are both examples of constraints. We also sought to answer the question of why we use ontologies. The creation of ontologies forces rigorous analysis and facilitates unambiguous discourse about domains. This is critical for information science, and within the field it i...

This week in IS2000 we focused on what information science is, and later upon elicitation and its importance to the field. Information scientists structure and organize data, as opposed to Data scientists who generally collect and analyze said data. Per Buckland (2012), Information science is with regard to computing, algorithms, and information technology, as well as the entropy of information. A type of information, generally understood to be insight, intuition, and contextualized information, is knowledge. There are two types of knowledge: tacit and explicit. Tacit knowledge is that which is internalized within individuals or organizations, while explicit knowledge is knowledge that has been externalized within books, articles, or operations manuals. The SECI model of knowledge posits that there are four ways that knowledge can be shared and conveyed: Socialization (tacit to tacit), Externalization (tacit to explicit), Combination (explicit to explicit), and Internalization (explici...