Ontology for Big Systems

How to Realize Interdisciplinary Collaboration


One of the challenges facing humanity in the 21st Century is that generalists, poly-maths, people with the ability to fully understand many fields of science have become far rarer, due to the vast proliferation and diversification of knowledge. Indeed, as knowledge has become more specialized, different communities have developed their own bodies of knowledge, vocabularies, or interpretations of common terms. Bridging these gaps can unleash a wealth of potential, foster innovation, reduce the duplicative efforts, and accelerate the development of better tools.

While each specialization may use its own terminology and technical language, the underlying reality is the same. Ontologies, in the form of explicit statement of the assumptions in each sub-field can help identify points of overlap and interest between different communities. The ontologies can serve as tools to facilitate search and discovery.

The Linked Science effort is a project that aims to create an “executable paper.” It hopes to combine publication of scientific data, metadata, results, and provenance information using Linked Data principles, alongside open source and web-based environments for executing, validating and exploring research, using Cloud Computing techniques for efficient and distributed computing and employing Creative Commons for its legal infrastructure.

Another project, the iPlant Collaborative, is building the requisite cyberinfrastructure to help cross-disciplinary, community-driven groups publish and share information, build models and aid in search. The vision is to develop a cyberinfrastructure that is accessible to all levels of expertise, ranging from students to traditional biology researchers and computational biology experts.