Applied Ontology: Focusing on content

Abstract

In a world that is overflowing with journals and other outlets for scientific publication, the appearance of any new periodical requires some justification. There are already more journals than we can read and more conferences than we can attend. In the case of Applied Ontology, we believe that the creation of a new journal not only is completely justifiable, it is downright exciting. For too long, workers in computer science have assumed that content comes for free. “Theory” in computer science has always meant the theory of processes and of computation. We measure the complexity of computer programs in terms of how long it takes machines to execute them, not in terms of how long it takes people to understand and to represent the data on which those programs might operate. We typically describe computer code in terms of algorithms that operate on formal parameters, often without pausing to discuss where the data that might satisfy those parameters come from. This journal was founded on the premise that workers in computer science, informatics, and information science are overdue in paying as much attention to content as they do to algorithms. There are journals that emphasize methods for representing knowledge and data. There are journals that emphasize processing of knowledge and data. Applied Ontology takes the position that, before we choose representation systems or algorithms, we first must create models of the world and clarify “what exists.” Ontology is no longer perceived as an arcane branch of metaphysics, the province only of philosophers; the study of ontology now fits squarely into the study of modern computer science and informatics. Building ontologies is now an essential activity that underlies nearly everything we do in the development of computational systems. The dramatic growth of information and communication technologies in recent years has led to a new focus on information content, and to an increasingly interdisciplinary approach to research and development activities in these fields. Linguists and philosophers now work hand-in-hand with traditional computer scientists to build complex information systems with explicit, examinable conceptual models of the environments in which they are intended to operate, of the organizations in which they will be used, and of the data and knowledge that they will process. In order to be understandable and reusable, these models need to combine the precision of formal semantics with the efficacy of cognitive transparency, as they incorporate increasingly sophisticated and heterogeneous modeling paradigms. The recent explosion of interest in ontologies is a fundamental component of this trend. Researchers in disciplines such as knowledge engineering, information-systems modeling, artificial intelligence, formal and computational linguistics, information retrieval, library science, and knowledge management have come to realize that a solid foundation for their research calls for serious work in ontology, understood as a general theory of the types of entities and relations that make up their respective domains of inquiry. The unification of these diverse disciplines by a shared desire to elucidate, to evaluate, to apply, and to