Natural Language-based Approach for Helping in the Reuse of Ontology Design Patterns

Experiments in the reuse of Ontology Design Patterns (ODPs) have revealed that users with different levels of expertise in ontology modelling face difficulties when reusing ODPs. With the aim of tackling this problem we propose a method and a tool for supporting a semi-automatic reuse of ODPs that takes as input formulations in natural language (NL) of the domain aspect to be modelled, and obtains as output a set of ODPs for solving the initial ontological needs. The correspondence between ODPs and NL formulations is done through Lexico-Syntactic Patterns, linguistic constructs that convey the semantic relations present in ODPs, and which constitute the main contribution of this paper. The main benefit of the proposed approach is the use of non-restricted NL formulations in various languages for obtaining ODPs. The use of full NL poses challenges in the disambiguation of linguistic expressions that we expect to solve with user interaction, among other strategies

A Double Classification of Common Pitfalls in Ontologies

The application of methodologies for building ontologies has improved the ontology quality. However, such a quality is not totally guaranteed because of the difficulties involved in ontology modelling. These difficulties are related to the inclusion of anomalies or worst practices in the modelling. In this context, our aim in this paper is twofold: (1) to provide a catalogue of common worst practices, which we call pitfalls, and (2) to present a double classification of such pitfalls. These two products will serve in the ontology development in two ways: (a) to avoid the appearance of pitfalls in the ontology modelling, and (b) to evaluate and correct ontologies to improve their quality

Ontology Population via NLP Techniques in Risk Management

In this paper we propose an NLP-based method for Ontology Population from texts and apply it to semi automatic instantiate a Generic Knowledge Base (Generic Domain Ontology) in the risk management domain. The approach is semi-automatic and uses a domain expert intervention for validation. The proposed approach relies on a set of Instances Recognition Rules based on syntactic structures, and on the predicative power of verbs in the instantiation process. It is not domain dependent since it heavily relies on linguistic knowledge. A description of an experiment performed on a part of the ontology of the PRIMA project (supported by the European community) is given. A first validation of the method is done by populating this ontology with Chemical Fact Sheets from Environmental Protection Agency . The results of this experiment complete the paper and support the hypothesis that relying on the predicative power of verbs in the instantiation process improves the performance.Information Extraction, Instance Recognition Rules, Ontology Population, Risk Management, Semantic Analysis

OOPS! – OntOlogy Pitfalls Scanner!

The application of methodologies for building ontologies has improved the ontology quality. However, such a quality is not totally guaranteed because of the difficulties involved in ontology modelling. These difficulties are related to the inclusion of anomalies or worst practices in the modelling. Several authors have provided lists of typical anomalies detected in ontologies during the last decade. In this context, our aim in this technical report is to describe OOPS! (OntOlogy Pitfalls Scanner!), a tool for pitfalls detection in ontology developments

Approaches Regarding Business Logic Modeling in Service Oriented Architecture

As part of the Service Oriented Computing (SOC), Service Oriented Architecture (SOA) is a technology that has been developing for almost a decade and during this time there have been published many studies, papers and surveys that are referring to the advantages of projects using it. In this article we discuss some ways of using SOA in the business environment, as a result of the need to reengineer the internal business processes with the scope of moving forward towards providing and using standardized services and achieving enterprise interoperability.Business Rules, Business Processes, SOA, BPM, BRM, Semantic Web, Semantic Interoperability

Approaches to ontology development by non ontology experts

Untrained users in the development of ontologies are challenged by the formal representation languages that underlie the most common ontology editing tools. To reduce that barrier, many efforts have gone in the creation of Controlled Languages (CL) translatable into ontology structures. However, CLs fall short of addressing a more profound problem: the selection of the most appropriate ontology modelling component for a certain modelling problem, regardless of the underlying representation paradigm. With the aim of approaching non ontology expert's difficulties in selecting the most appropriate modelling solution, we propose a Natural Language (NL) guided approach based on a repository of Lexico-Syntactic Patterns associated to consensual modelling solutions, i.e., Ontology Design Patterns. By relying on this repository, untrained users can formulate in NL what they want to model in the ontology, and obtain the corresponding design pattern for the modelling issue

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

Using Linguistic Patterns to Enhance Ontology Development

In this paper we describe how linguistic patterns can contribute to ontology development by enabling an easier reuse of some ontological resources. In particular, our research focuses on the reuse of ontology design patterns and ontology statements by relying on linguistic constructs at different stages of the reuse process. With this aim, we propose the employment of lexico-syntactic patterns with two objectives: 1) the reuse of ontology design patterns, and 2) the validation of ontology statements for their subsequent reuse in the ontology development. To illustrate the proposed approaches, we will present some examples of lexico-syntactic patterns and their employment in the reuse of ontology design patterns and in the validation of ontology statements

Models for Learning (Mod4L) Final Report: Representing Learning Designs

The Mod4L Models of Practice project is part of the JISC-funded Design for Learning Programme. It ran from 1 May – 31 December 2006. The philosophy underlying the project was that a general split is evident in the e-learning community between development of e-learning tools, services and standards, and research into how teachers can use these most effectively, and is impeding uptake of new tools and methods by teachers. To help overcome this barrier and bridge the gap, a need is felt for practitioner-focused resources which describe a range of learning designs and offer guidance on how these may be chosen and applied, how they can support effective practice in design for learning, and how they can support the development of effective tools, standards and systems with a learning design capability (see, for example, Griffiths and Blat 2005, JISC 2006). Practice models, it was suggested, were such a resource. The aim of the project was to: develop a range of practice models that could be used by practitioners in real life contexts and have a high impact on improving teaching and learning practice. We worked with two definitions of practice models. Practice models are: 1. generic approaches to the structuring and orchestration of learning activities. They express elements of pedagogic principle and allow practitioners to make informed choices (JISC 2006) However, however effective a learning design may be, it can only be shared with others through a representation. The issue of representation of learning designs is, then, central to the concept of sharing and reuse at the heart of JISC’s Design for Learning programme. Thus practice models should be both representations of effective practice, and effective representations of practice. Hence we arrived at the project working definition of practice models as: 2. Common, but decontextualised, learning designs that are represented in a way that is usable by practitioners (teachers, managers, etc).(Mod4L working definition, Falconer & Littlejohn 2006). A learning design is defined as the outcome of the process of designing, planning and orchestrating learning activities as part of a learning session or programme (JISC 2006). Practice models have many potential uses: they describe a range of learning designs that are found to be effective, and offer guidance on their use; they support sharing, reuse and adaptation of learning designs by teachers, and also the development of tools, standards and systems for planning, editing and running the designs. The project took a practitioner-centred approach, working in close collaboration with a focus group of 12 teachers recruited across a range of disciplines and from both FE and HE. Focus group members are listed in Appendix 1. Information was gathered from the focus group through two face to face workshops, and through their contributions to discussions on the project wiki. This was supplemented by an activity at a JISC pedagogy experts meeting in October 2006, and a part workshop at ALT-C in September 2006. The project interim report of August 2006 contained the outcomes of the first workshop (Falconer and Littlejohn, 2006). The current report refines the discussion of issues of representing learning designs for sharing and reuse evidenced in the interim report and highlights problems with the concept of practice models (section 2), characterises the requirements teachers have of effective representations (section 3), evaluates a number of types of representation against these requirements (section 4), explores the more technically focused role of sequencing representations and controlled vocabularies (sections 5 & 6), documents some generic learning designs (section 8.2) and suggests ways forward for bridging the gap between teachers and developers (section 2.6). All quotations are taken from the Mod4L wiki unless otherwise stated