Using ontological contexts to assess the relevance of statements in ontology evolution

Ontology evolution tools often propose new ontological changes in the form of statements. While different methods exist to check the quality of such statements to be added to the ontology (e.g., in terms of consistency and impact), their relevance is usually left to the user to assess. Relevance in this context is a notion of how well the statement fits in the target ontology. We present an approach to automatically assess such relevance. It is acknowledged in cognitive science and other research areas that a piece of information flowing between two entities is relevant if there is an agreement on the context used between the entities. In our approach, we derive the context of a statement from online ontologies in which it is used, and study how this context matches with the target ontology. We identify relevance patterns that give an indication of rele- vance when the statement context and the target ontology fulfill specific conditions. We validate our approach through an experiment in three dif- ferent domains, and show how our pattern-based technique outperforms a naive overlap-based approach

Investigating the use of background knowledge for assessing the relevance of statements to an ontology in ontology evolution

The tasks of learning and enriching ontologies with new concepts and relations have attracted a lot of attention in the research community, leading to a number of tools facilitating the process of building and updating ontologies. These tools often discover new elements of information to be included in the considered ontology from external data sources such as text documents or databases, transforming these elements into ontology compatible statements or axioms. While some techniques are used to make sure that statements to be added are compatible with the ontology (e.g. through conflict detection), such tools generally pay little attention to the relevance of the statement in question. It is either assumed that any statement extracted from a data source is relevant, or that the user will assess whether a statement adds value to the ontology. In this paper, we investigate the use of background knowledge about the context where statements appear to assess their relevance. We devise a methodology to extract such a context from ontologies available online, to map it to the considered ontology and to visualize this mapping in a way that allows to study the intersection and complementarity of the two sources of knowledge. By applying this methodology on several examples, we identified an initial set of patterns giving strong indications concerning the relevance of a statement, as well as interesting issues to be considered when applying such techniques

Harvesting online ontologies for ontology evolution

Ontologies need to evolve to keep their domain representation adequate. However, the process of identifying new domain changes, and applying them to the ontology is tedious and time-consuming. Our hypothesis is that online ontologies can provide background knowledge to decrease user efforts during ontology evolution, by integrating new domain concepts through automated relation discovery and relevance assessment techniques, while resulting in ontologies of similar qualities to when the ontology engineers' knowledge is solely used. We propose, implement and evaluate solutions that exploit the conceptual connections and structure of online ontologies to first, automatically suggest new additions to the ontology in the form of concepts derived from domain data, and their corresponding connections to existing elements in the ontology; and second, to automatically evaluate the proposed changes in terms of relevance with respect to the ontology under evolution, by relying on a novel pattern-based technique for relevance assessment. We also present in this thesis various experiments to test the feasibility of each proposed approach separately, in addition to an overall evaluation that validates our hypothesis that user time during evolution is indeed decreased through the use of online ontologies, with comparable results to a fully manual ontology evolution

An Ontological Approach to Representing the Product Life Cycle

The ability to access and share data is key to optimizing and streamlining any industrial production process. Unfortunately, the manufacturing industry is stymied by a lack of interoperability among the systems by which data are produced and managed, and this is true both within and across organizations. In this paper, we describe our work to address this problem through the creation of a suite of modular ontologies representing the product life cycle and its successive phases, from design to end of life. We call this suite the Product Life Cycle (PLC) Ontologies. The suite extends proximately from The Common Core Ontologies (CCO) used widely in defense and intelligence circles, and ultimately from the Basic Formal Ontology (BFO), which serves as top level ontology for the CCO and for some 300 further ontologies. The PLC Ontologies were developed together, but they have been factored to cover particular domains such as design, manufacturing processes, and tools. We argue that these ontologies, when used together with standard public domain alignment and browsing tools created within the context of the Semantic Web, may offer a low-cost approach to solving increasingly costly problems of data management in the manufacturing industry

Ontology evolution: a process-centric survey

Ontology evolution aims at maintaining an ontology up to date with respect to changes in the domain that it models or novel requirements of information systems that it enables. The recent industrial adoption of Semantic Web techniques, which rely on ontologies, has led to the increased importance of the ontology evolution research. Typical approaches to ontology evolution are designed as multiple-stage processes combining techniques from a variety of fields (e.g., natural language processing and reasoning). However, the few existing surveys on this topic lack an in-depth analysis of the various stages of the ontology evolution process. This survey extends the literature by adopting a process-centric view of ontology evolution. Accordingly, we first provide an overall process model synthesized from an overview of the existing models in the literature. Then we survey the major approaches to each of the steps in this process and conclude on future challenges for techniques aiming to solve that particular stage

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Concrete utopianism in integrated assessment models: Discovering the philosophy of the shared socioeconomic pathways

The Shared Socioeconomic Pathways (SSPs) are at the forefront of climate change science today. As an influential methodology and method, the SSPs guide the framing of numerous climate change research questions and how these are investigated. Although the SSPs were developed by an interdisciplinary group of scientists in a well-documented process, there is no apparent consensus in the literature that answers the question, "What is the philosophy of science behind the SSPs?" To investigate, the paper applies a systematic thematic qualitative content analysis to the dataset of published papers that establish the rules and expectations for using the SSPs. The research determines that there is no obvious and concise statement on the epistemological and ontological foundation of the SSPs. However, based on the evidence identified in the dataset, SSPs are implicitly, though not explicitly, consistent with a critical realist and concrete utopian philosophy as coined by Roy Bhaskar. This is the first paper to discuss the philosophical underpinning of the SSPs

Benchmarking Ontologies: Bigger or Better?

A scientific ontology is a formal representation of knowledge within a domain, typically including central concepts, their properties, and relations. With the rise of computers and high-throughput data collection, ontologies have become essential to data mining and sharing across communities in the biomedical sciences. Powerful approaches exist for testing the internal consistency of an ontology, but not for assessing the fidelity of its domain representation. We introduce a family of metrics that describe the breadth and depth with which an ontology represents its knowledge domain. We then test these metrics using (1) four of the most common medical ontologies with respect to a corpus of medical documents and (2) seven of the most popular English thesauri with respect to three corpora that sample language from medicine, news, and novels. Here we show that our approach captures the quality of ontological representation and guides efforts to narrow the breach between ontology and collective discourse within a domain. Our results also demonstrate key features of medical ontologies, English thesauri, and discourse from different domains. Medical ontologies have a small intersection, as do English thesauri. Moreover, dialects characteristic of distinct domains vary strikingly as many of the same words are used quite differently in medicine, news, and novels. As ontologies are intended to mirror the state of knowledge, our methods to tighten the fit between ontology and domain will increase their relevance for new areas of biomedical science and improve the accuracy and power of inferences computed across them.</p

The Relevance of Rigour for Design Practise

Design is an inverted discipline. The concept of rigour, as understood within the natural sciences, cannot be applied to Design Practice. Rigour for the natural sciences is a quality assurance mechanism ensuring that the knowledge bases of the disciplines are developed to an accepted set of standards. Design’s ontology is not like the natural sciences and as such an understanding of rigour for Design must proceed from an appropriate standpoint about the nature of Design Practice. This paper builds upon Harfield’s [1] ontological assessment of Design, Schön’s [2] [3] work on Reflective Practice and Spencer’s [4] investigation into the experience and practise of designing to develop a standpoint about Design Practice and make a proposition about the relevance of rigour for Design Practise. This paper considers how individual Reflective Practice practitioners, within the context of Design Practice, manage and ensure quality control through the application of care and thoroughness. This paper argues that rigour for Design Practise is the personal and phenomenological quality control of a design inquiry: a process of managing expanding mental chaos and restricting order