Ontologies in the Time of Linked Data

This paper discusses some of the methodological issues one encounters when creating and using ontologies in the rapidly expanding Linked Open Data (LOD) landscape. Over the years the notion of applied ontologies has transitioned from that of a logically formalized knowledge system with varying degrees of inferencing power to that of a lightweight knowledge representation tool. This shift is reflected in the current lexicon where different actors in the LOD community use the term ontology interchangeably with more generic terms like vocabulary or even namespace or data schema. Applied ontologies have been a key area of research in the context of Semantic Web initiative since the late 1990s. The Semantic Web has recently found a new stream of development in the Linked Data initiative, which is considered its natural evolution (Allemang and Hendler, 2011). While a good deal of literature has been devoted to investigating ontology engineering for the Semantic Web, not enough attention has yet been paid to understanding the nature and role that ontologies play in the linked data context, especially from the lens of knowledge organization research. Based on our ongoing work creating Linked Open Data applications and services for digital resources in the domain of the performing arts, we describe methodological steps and lessons learned in line with the spirit of the linked data initiative, where an agile and pragmatic approach to development is combined with the practice of learning from one another

Semantic Interoperability of Geospatial Ontologies: A Model-theoretic Analysis

People sometimes misunderstand each other, even when they use the same language to communicate. Often these misunderstandings happen when people use the same words to mean different things, in effect disagreeing about meanings. This thesis investigates such disagreements about meaning, considering them to be issues of semantic interoperability. This thesis explores semantic interoperability via a particular formal framework used to specify people’s conceptualizations of a given domain. This framework is called an ‘ontology,’ which is a collection of data and axioms written in a logical language equipped with a modeltheoretic semantics. The domain under consideration is the geospatial domain. Specifically, this thesis investigates to what extent two geospatial ontologies are semantically interoperable when they ‘agree’ on the meanings of certain basic terms and statements, but ‘disagree’ on others. This thesis defines five levels of semantic interoperability that can exist between two ontologies. Each of these levels is, in turn, defined in terms of six ‘compatibility conditions,’ which precisely describe how the results of queries to one ontology are compatible with the results of queries to another ontology. Using certain assumptions of finiteness, the semantics of each ontology is captured by a finite number of models, each of which is also finite. The set of all models of a given ontology is called its model class. The five levels of semantic interoperability are proven to correspond exactly to five particular relationships between the model classes of the ontologies. The exact level of semantic interoperability between ontologies can in some cases be computed; in other cases a heuristic can be used to narrow the possible levels of semantic interoperability. The main results are: (1) definitions of five levels of semantic interoperability based on six compatibility conditions; (2) proofs of the correspondence between levels of semantic interoperability and the model-class relation between two ontologies; and (3) a method for computing, given certain assumptions of finiteness, the exact level of semantic interoperability between two ontologies. These results define precisely, in terms of models and queries, the often poorly defined notion of semantic interoperability, thus providing a touchstone for clear definitions of semantic interoperability elsewhere

Architecture of Sysperanto: A Model-Based Ontology of the IS Field

The challenge of defining the domain and core concepts of the IS field is a perennial topic at major IS conferences. This paper describes the architecture of Sysperanto, a model-based ontology of the IS field. Sysperanto is being developed as part of an ongoing effort to create methods that typical business professionals can use to analyze systems and system-related projects for themselves at whatever level of depth is appropriate. The name Sysperanto is meant as a metaphor combining generality (covering the IS field), vocabulary (identification of terms), and structure (internally consistent organization) to create an ontology more powerful and useful than a list of keywords or propositions. Sysperanto\u27s architecture provides an organizing framework for codifying the disparate and inconsistent propositions, methods, and findings that constitute the current state of IS knowledge and, in combination, form a major obstacle to knowledge accumulation and use in the IS field. Instead of yet another discussion of whether the IS field lacks a conceptual core and what might be the consequences of such a shortcoming, this paper proposes an architecture and preliminary details of a plausible set of core concepts for the IS field. It starts by summarizing Sysperanto\u27s goals and explaining why work system concepts, rather than information system concepts, are the core of Sysperanto. It presents Sysperanto as a terminological ontology and explains the underlying meta-model. The meta-model is designed to support tools for analyzing systems from a business viewpoint and to help in codifying and organizing knowledge in the IS field. It uses a conceptual map based on extensiveness and guidance in application to compare Sysperanto with other efforts to organize ideas in the IS field. It may be several years before a complete version of Sysperanto is tested through its use in a formal method for analyzing systems or through comparison with other attempts to codify knowledge in the IS field. Nonetheless, its architecture is well enough defined to be compared to the architecture (or lack of architecture) in previous and future approaches for understanding and organizing the basic concepts about information systems

The Orbital Space Environment and Space Situational Awareness Domain Ontology – Towards an International Information System for Space Data

The orbital space environment is home to natural and artificial satellites, debris, and space weather phenomena. As the population of orbital objects grows so do the potential hazards to astronauts, space infrastructure and spaceflight capability. Orbital debris, in particular, is a universal concern. This and other hazards can be minimized by improving global space situational awareness (SSA). By sharing more data and increasing observational coverage of the space environment we stand to achieve that goal, thereby making spaceflight safer and expanding our knowledge of near-Earth space. To facilitate data-sharing interoperability among distinct orbital debris and space object catalogs, and SSA information systems, I proposed ontology in (Rovetto, 2015) and (Rovetto and Kelso, 2016). I continue this effort toward formal representations and models of the overall domain that may serve to improve peaceful SSA and increase our scientific knowledge. This paper explains the project concept introduced in those publications, summarizing efforts to date as well as the research field of ontology development and engineering. I describe concepts for an ontological framework for the orbital space environment, near-Earth space environment and SSA domain. An ontological framework is conceived as a part of a potential international information system. The purpose of such a system is to consolidate, analyze and reason over various sources and types of orbital and SSA data toward the mutually beneficial goals of safer space navigation and scientific research. Recent internationals findings on the limitations of orbital data, in addition to existing publications on collaborative SSA, demonstrate both the overlap with this project and the need for data-sharing and integration

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

On the Role of Assertions for Conceptual Modeling as Enablers of Composable Simulation Solutions

This research provides a much needed systematic review of the roles that assertions play in model composability and simulation interoperability. In doing so, this research contributes a partial solution to one of the problems of model composability and simulation interoperability—namely, why do simulation systems fail to achieve the maximum level of interoperability possible? It demonstrates the importance of the assertions that are made during model development and simulation implementation, particularly as they reflect the unique viewpoint of each developer or user. It hypothesizes that it is possible to detect composability conflicts by means of a four-step process developed by the author for capturing and comparing assertions. It demonstrates the process using a well understood example problem—the Falling Body Problem—developing a formal model of assertion, a strategy for assertion comparison, an inventory of forces, and a catalog of significant assertions that might be made for each term in the solution to the problem. Finally, it develops a software application to implement the strategy for comparing sets of assertions. The software successfully detects potential conflicts between ontologies that were otherwise determined to be ontologically consistent, thus proving the hypothesis

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

Do Process Modelling Techniques Get Better? A Comparative Ontological Analysis of BPMN

Current initiatives in the field of Business Process Management (BPM) strive for the development of a BPM standard notation by pushing the Business Process Modeling Notation (BPMN). However, such a proposed standard notation needs to be carefully examined. Ontological analysis is an established theoretical approach to evaluating modelling techniques. This paper reports on the outcomes of an ontological analysis of BPMN and explores identified issues by reporting on interviews conducted with BPMN users in Australia. Complementing this analysis we consolidate our findings with previous ontological analyses of process modelling notations to deliver a comprehensive assessment of BPMN