Ontology for Big Systems

Ontology for Big Systems


The Cambrian explosion occurred 530 million years ago, as life on earth experienced a sudden increase in diversity and the rate of evolution. Over the past half century, we’ve entered the Cambrian age for information, knowledge and systems, coupled with a constantly evolving technology landscape. The amount of knowledge that is produced, published and shared by humanity has been growing exponentially each year. In the past decade more data has been collected, more video has been produced and more information has been published than in all of previous human history.

At the same time, with the advent of the computer, digital representations, and the Internet, it has been possible to model more of the complexity of systems, connect more people. Moreover, an increasing number of people and organizations are driven to connect their systems to one another. With all this new information (aka Big Data) and all these new systems (aka Big Systems), there has also be an attendant growth in the complexity of systems that model physical phenomena and handle information, their size, their scale, their scope and their interdependence.

To address the problems that have arisen during the current period of information and knowledge, we need novel tools and approaches. Some of the major challenges facing Big Systems stem not only from their scale, but also their scope and complexity. At the same time, there are novel challenges for Big Systems when different, dispersed groups work together toward a common goal, for instance in understanding Climate Change. This leads to a need for better solutions for interoperability among federated systems and for fostering interdisciplinary collaboration. For example, we would expect that systems developed to help evacuate a city in anticipation of a tsunami to operate seamlessly with our navigation systems.

This year's Ontology Summit is titled "Ontology for Big Systems" and seeks to explore, identify and articulate how ontological methods can benefit the various disciplines required to engineer a "big system." The term "big system" is intended to cover a large scope that includes many of the terms encountered in the media such as big data, complex techno-socio-economic systems, intelligent or smart systems, cloud computing, net-centricity and collective intelligence. Established disciplines that fall within the summit scope include (but not limited to) systems engineering, software engineering, information systems modelling, and data mining.   

The principal goal of the summit was to bring together and foster collaboration between the ontology community, systems community, and stakeholders of Big Systems. Together, summit participants exchanged ideas on how ontological analysis and ontology engineering might make a difference, when applied in these "big systems." We produced recommendations describing how ontologies fit into Big Systems, as well as providing examples where ontological techniques have been, or could be applied, in domains such as: bioinformatics, electronic health records, intelligence, the smart electrical grid, manufacturing and supply chains, earth and environmental, e-science, cyber-physical systems and e-government. As is traditional with the Ontology Summit series, the results will be captured in the form of a communique, with expanded supporting material provided on the web.