There is an increased use of problem representations (i.e. superstructures in synthesis problems; networks in route problems; graphs; ordered graphs in various systems representations) following on significant advances in optimization technologies that hold capabilities to solve, robustly, large-scale problems. In an attempt to systematically tackle disparate domains and build high-throughput functions, the paper contributes with a semantically-enabled approach systematized and engineered by ontologies. The aim is to develop an intelligent environment with capabilities to build and scale-up system representations, automatically. The work is demonstrated on problems akin to biorenewables and biorefineries; an identical approach is possible to the general problem. Using relations and rules defined among entities, semantics are deployed to model and expand domains (biorefinery pathways) whereas enabling extracting and creating knowledge. The repository, already on a web-based platform and available as open-source, essentially upgrades conventional representations with capabilities to share (import/export) and integrate its content externally.

随着优化技术的显着进步，问题表示（即综合问题中的上层建筑；路线问题中的网络；图形；有序图形在各种系统表示中）的使用得到了增强，这些技术具有强大的能力来解决大型问题。为了系统地解决不同的领域并建立高通量功能，本文提出了一种由本体论系统化和设计的语义支持方法。目的是开发一种具有自动构建和扩展系统表示能力的智能环境。这项工作在生物可再生能源和生物精炼厂等问题上得到了证明；对于一般问题，可以采用相同的方法。使用实体之间定义的关系和规则，部署语义来建模和扩展域（生物炼制途径），同时能够提取和创建知识。该存储库已经在基于Web的平台上并且可以作为开源使用，从根本上升级了传统表示形式，并具有在外部共享（导入/导出）和集成其内容的功能。