Developing a Taxonomy for Scientific Concepts
Intelligent Information Management
Dipl.-Inf. André Langer
Prof. Dr.-Ing. Martin Gaedke
Linked Data heaviliy relies on the usage of well-known uniform concept identifiers. For common entities, these URIs already exist through projects such as DBpedia, Wikidata or Conceptnet.io. However, when somebody wants to specify fine-grained data for a scientific artefact such as the type of publication, area of research, problem domain, used methodology, metrics of interest, evaluation or even license information, simple literals are commonly used again.
In this project we focus on a generic approach to store common concepts for scientific work in a hierarchical fashion so that they can be found and referenced easily by unexperienced users. After a State of the Art and Requirement analysis, relevant concepts and appropriate URIs have to be collected and classified so that a preselection for concepts of interest can be done in advance. The classification shall be easily extensible in the future. An evaluation has to show, that URIs for common usage scenarios in scientific daily work are provided.