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This paper presents the recent results of the integration of computational and conceptual solutions for the complex case of environmental information management. The solution for the major goal of creating and developing long-term multi-disciplinary knowledge resources and conceptual and computational support was achieved by implementing and integrating key components. The key components are long-term knowledge resources providing required structures for universal knowledge creation, documentation, and preservation, universal multi-disciplinary and multi-lingual conceptual knowledge and classification, especially, references to Universal Decimal Classification (UDC), sustainable workflows for environmental information management, and computational support for dynamical use, processing, and advanced scientific computing with Integrated Information and Computing System (IICS) components and High End Computing (HEC) resources. [ABSTRACT FROM AUTHOR]

This paper presents the up-to-date results concerning the integration of scientific classification and computation deploying long-term knowledge resources. The knowledge resources are the central component in universal multi-disciplinary and multi-lingual knowledge management. While the research focus is on universal knowledge creation, documentation, and preservation, the architecture allows efficient dynamical use and processing as well as computational utilisation, e.g., in advanced scientific computing with Integrated Information and Computing System (IICS) components and High End Computing (HEC) resources. The knowledge resources' goal is to address a major gap for long-term knowledge and to provide structure, references, and classification for any type of data, knowledge, and context. Based on the implementation, the case study depicts concepts of references to Universal Decimal Classification (UDC) views, e.g., for workflows. The key results are benefits for knowledge management and documentation, the sustainable integration of long-term documentation, data, and workflow vitality for improved knowledge gathering, computational purposes, and evaluation based on big data. [ABSTRACT FROM AUTHOR]