An Approach to enrich the Optimization of the Forest-based Supply Chain by Semantics

Johannes Scholz, Alexandra S. Marques

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Contemporary digital methods and techniques for optimizing the FbSC are getting growing attention, as the raw material wood is a climate-neutral good. In order to better utilize the resource forest and the subsequent Forest-based supply chain (FbSC) the digitization of the processes seems inevitable. In addition, digitization could enhance the horizontal and vertical cooperation between stakeholders in the FbSC. Nevertheless, institutional borders as well as IT-related limitations – especially syntactic (to a lesser degree) and semantic interoperability – hinder cooperation.
For the FbSC semantics could help to share data between stakeholders and IT-systems as well, in a way that the meaning of data are clearly defined. In particular a Linked Data representation enables (geo-) semantic queries on multiple datasets. Hence, Decision Support Systems and optimization systems could “crawl” the Linked Data Cloud for appropriate data for a specific purpose. The results of any Decision Support System, and optimization, could be made available to the stakeholders and their IT systems in a semantically enriched manner. This would pave the way to overcome interoperability issues, which are the result of different systems and/or data formats involved in the FbSC. This could be realized by describing data/formats with the help of a shared ontology, defining “what is” in a system independent way – e.g. as Ontology Web Language.
Original languageEnglish
Title of host publicationEURO 2019 - Abstract Book
Publication statusPublished - 2019
Event30th European Conference on Operational Research: 30th European Conference on Operational Research ​ - University College Dublin, Dublin, Ireland
Duration: 23 Jun 201926 Jun 2019


Conference30th European Conference on Operational Research
Abbreviated titleEURO 2019
Internet address


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