A unifying framework for the definition of syntactic measures over conceptual schema diagrams (extended version)

There are many approaches that propose the use of measures for assessing the quality of conceptual schemas. Many of these measures focus purely on the syntactic aspects of the conceptual schema diagrams, e.g. their size, their shape, etc. Similarities among different measures may be found both at the intra-model level (i.e., several measures over the same type of diagram are defined following the same layout) and at the inter-model level (i.e., measures over different types of diagrams are similar considering an appropriate metaschema correspondence). In this paper we analyse these similarities for a particular family of diagrams used in conceptual modelling, those that can be ultimately seen as a combination of nodes and edges of different types. We propose a unifying measuring framework for this family and illustrate its application on a particular type, namely business process diagrams.Preprin

Towards a Unifying View of QoS-Enhanced Web Service Description and Discovery Approaches

The number of web services increased vastly in the last years. Various providers offer web services with the same functionality, so for web service consumers it is getting more complicated to select the web service, which best fits their requirements. That is why a lot of the research efforts point to discover semantic means for describing web services taking into account not only functional characteristics of services, but also the quality of service (QoS) properties such as availability, reliability, response time, trust, etc. This motivated us to research current approaches presenting complete solutions for QoS enabled web service description, publication and discovery. In this paper we present comparative analysis of these approaches according to their common principals. Based on such analysis we extract the essential aspects from them and propose a pattern for the development of QoS-aware service-oriented architectures

Practice, principles, and theory in the design of instructional text

This study is concerned with an analysis of the research arising from three quite different perspectives on instructional text - the `physical characteristics' research (legibility, layout, and readability), the `improvement of text' research (visual illustrations, adjunct aids, and typographical cueing), and the `learning theories' research (representation of knowledge, human memory, and quality of learning). From this analysis there is synthesised principles for the design of instructional text against which heuristic practice in text design is evaluated and from which a nascent theory of instructional text design is evolved. The principles derived from the various research perspectives provide a basis for the manipulation of text design elements in order to ensure that (a) existing knowledge in the reader can be activated, and (b) new knowledge can be assimilated in a manner facilitative of comprehension by (i) presentation in a structured and organised way, and (ii) appropriately highlighted through verbal and typographic cueing supported, as required, by verbal illustration and organisation. The emerging theory of instructional text design suggests: a topical analysis to determine the heirarchic relationship of ideas within the topic and the desired learning outcomes or objectives; a consideration of the linguistic aspects of the text; a consideration of the role of visual illustrations; and a consideration of the physical parameters of the text. These activities are concerned, respectively, with the design areas of structure and organisation, readability, visual illustration, and legibility, and are summed up in the acronym SORVIL

Design For Change: Ontology-Driven Knowledgebase Applications For Dynamic Biological Domains

Post-genomic biology is producing a plethora of rapidly changing complex data. Yet extracting useful information from this data is limited by current knowledge management methodologies. Biological knowledge management is complicated by ambiguous nomenclature, cultural differences between biologists and computer scientists, and conventional database technology that was not designed to support rapidly changing complex domains. A recent trend in ontology-driven database design has emerged to address this challenge. While ontologies provide effective knowledge models, attempts to transform ontologies into knowledgebases have revealed an impedance mismatch or ontology transformation gap. A unique methodology called Ultra-Structure Theory (UT) may provide an ontology transform solution that supports large scale, dynamic biological domains by expressing the complexity in data rather than programming code. This thesis aims to survey ontology and database theory and methodologies, and describe how UT integrates and extends them to provide a flexible, semantically expressive knowledgebase solution using standard relational database technology

XML Matchers: approaches and challenges

Schema Matching, i.e. the process of discovering semantic correspondences between concepts adopted in different data source schemas, has been a key topic in Database and Artificial Intelligence research areas for many years. In the past, it was largely investigated especially for classical database models (e.g., E/R schemas, relational databases, etc.). However, in the latest years, the widespread adoption of XML in the most disparate application fields pushed a growing number of researchers to design XML-specific Schema Matching approaches, called XML Matchers, aiming at finding semantic matchings between concepts defined in DTDs and XSDs. XML Matchers do not just take well-known techniques originally designed for other data models and apply them on DTDs/XSDs, but they exploit specific XML features (e.g., the hierarchical structure of a DTD/XSD) to improve the performance of the Schema Matching process. The design of XML Matchers is currently a well-established research area. The main goal of this paper is to provide a detailed description and classification of XML Matchers. We first describe to what extent the specificities of DTDs/XSDs impact on the Schema Matching task. Then we introduce a template, called XML Matcher Template, that describes the main components of an XML Matcher, their role and behavior. We illustrate how each of these components has been implemented in some popular XML Matchers. We consider our XML Matcher Template as the baseline for objectively comparing approaches that, at first glance, might appear as unrelated. The introduction of this template can be useful in the design of future XML Matchers. Finally, we analyze commercial tools implementing XML Matchers and introduce two challenging issues strictly related to this topic, namely XML source clustering and uncertainty management in XML Matchers.Comment: 34 pages, 8 tables, 7 figure

A framework for the analysis and evaluation of enterprise models

Bibliography: leaves 264-288.The purpose of this study is the development and validation of a comprehensive framework for the analysis and evaluation of enterprise models. The study starts with an extensive literature review of modelling concepts and an overview of the various reference disciplines concerned with enterprise modelling. This overview is more extensive than usual in order to accommodate readers from different backgrounds. The proposed framework is based on the distinction between the syntactic, semantic and pragmatic model aspects and populated with evaluation criteria drawn from an extensive literature survey. In order to operationalize and empirically validate the framework, an exhaustive survey of enterprise models was conducted. From this survey, an XML database of more than twenty relatively large, publicly available enterprise models was constructed. A strong emphasis was placed on the interdisciplinary nature of this database and models were drawn from ontology research, linguistics, analysis patterns as well as the traditional fields of data modelling, data warehousing and enterprise systems. The resultant database forms the test bed for the detailed framework-based analysis and its public availability should constitute a useful contribution to the modelling research community. The bulk of the research is dedicated to implementing and validating specific analysis techniques to quantify the various model evaluation criteria of the framework. The aim for each of the analysis techniques is that it can, where possible, be automated and generalised to other modelling domains. The syntactic measures and analysis techniques originate largely from the disciplines of systems engineering, graph theory and computer science. Various metrics to measure model hierarchy, architecture and complexity are tested and discussed. It is found that many are not particularly useful or valid for enterprise models. Hence some new measures are proposed to assist with model visualization and an original "model signature" consisting of three key metrics is proposed.Perhaps the most significant contribution ofthe research lies in the development and validation of a significant number of semantic analysis techniques, drawing heavily on current developments in lexicography, linguistics and ontology research. Some novel and interesting techniques are proposed to measure, inter alia, domain coverage, model genericity, quality of documentation, perspicuity and model similarity. Especially model similarity is explored in depth by means of various similarity and clustering algorithms as well as ways to visualize the similarity between models. Finally, a number of pragmatic analyses techniques are applied to the models. These include face validity, degree of use, authority of model author, availability, cost, flexibility, adaptability, model currency, maturity and degree of support. This analysis relies mostly on the searching for and ranking of certain specific information details, often involving a degree of subjective interpretation, although more specific quantitative procedures are suggested for some of the criteria. To aid future researchers, a separate chapter lists some promising analysis techniques that were investigated but found to be problematic from methodological perspective. More interestingly, this chapter also presents a very strong conceptual case on how the proposed framework and the analysis techniques associated vrith its various criteria can be applied to many other information systems research areas. The case is presented on the grounds of the underlying isomorphism between the various research areas and illustrated by suggesting the application of the framework to evaluate web sites, algorithms, software applications, programming languages, system development methodologies and user interfaces

Semantic Similarity of Spatial Scenes

The formalization of similarity in spatial information systems can unleash their functionality and contribute technology not only useful, but also desirable by broad groups of users. As a paradigm for information retrieval, similarity supersedes tedious querying techniques and unveils novel ways for user-system interaction by naturally supporting modalities such as speech and sketching. As a tool within the scope of a broader objective, it can facilitate such diverse tasks as data integration, landmark determination, and prediction making. This potential motivated the development of several similarity models within the geospatial and computer science communities. Despite the merit of these studies, their cognitive plausibility can be limited due to neglect of well-established psychological principles about properties and behaviors of similarity. Moreover, such approaches are typically guided by experience, intuition, and observation, thereby often relying on more narrow perspectives or restrictive assumptions that produce inflexible and incompatible measures. This thesis consolidates such fragmentary efforts and integrates them along with novel formalisms into a scalable, comprehensive, and cognitively-sensitive framework for similarity queries in spatial information systems. Three conceptually different similarity queries at the levels of attributes, objects, and scenes are distinguished. An analysis of the relationship between similarity and change provides a unifying basis for the approach and a theoretical foundation for measures satisfying important similarity properties such as asymmetry and context dependence. The classification of attributes into categories with common structural and cognitive characteristics drives the implementation of a small core of generic functions, able to perform any type of attribute value assessment. Appropriate techniques combine such atomic assessments to compute similarities at the object level and to handle more complex inquiries with multiple constraints. These techniques, along with a solid graph-theoretical methodology adapted to the particularities of the geospatial domain, provide the foundation for reasoning about scene similarity queries. Provisions are made so that all methods comply with major psychological findings about people’s perceptions of similarity. An experimental evaluation supplies the main result of this thesis, which separates psychological findings with a major impact on the results from those that can be safely incorporated into the framework through computationally simpler alternatives