Long-term Sustainable Knowledge Classification with Scientific Computing: The Multi-disciplinary View on Natural Sciences and Humanities

This paper presents the methodological and technical results of creating long-term sustainable knowledge resources, which can be used for documentation, classification, and structuring as well as with scientific discovery and deployment of supercomputing resources for advanced information systems. The focus is on the multi-disciplinary knowledge view on disciplines from natural sciences and humanities. The basic requirements resulting from the long-years’ cases studies are long-term knowledge resources providing structure and universal classification features. The paper discusses the state-of-the-art implementation of information structures and object representations used with universal classification and computation algorithms for multidisciplinary, dynamical knowledge discovery. The combination of universal knowledge resources and computational workflows based on High End Computing (HEC) resources and Universal Decimal Classification (UDC) have been successfully used for the goal of creating efficient long-term sustainable Integrated Information and Computing System components. The paper presents practical implementation examples from a range of disciplines with references to natural sciences and humanities, e.g., geosciences, astrophysics, and archaeology. The long-term results show that the overall sustainability principally depends on the methodological and systematical creation of content, structure, and classification with the knowledge resources. Keywords–Scientific Computing; Sustainability; Knowledge Resources; Multi-disciplinarity; Integrated Systems; Information Systems; Classification; UDC; Natural Sciences; Humanities.