Signifying ontology complexity for knowledge sharing

Ontologies are used in widespread application areas particularly to provide a shared semantically domain knowledge in a declarative formalism for intelligent reasoning. Even ontology enables knowledge sharing however complexity of knowledge being conceptualized in the ontology is critical to the success of knowledge sharing efforts. Other factor like trust in the source of knowledge can also affect knowledge transfer. In this paper we propose metrics to measure the complexity of ontology for knowledge sharing. We have chosen Software Engineering Ontology as our case study

An Automated System for the Assessment and Ranking of Domain Ontologies

As the number of intelligent software applications and the number of semantic websites continue to expand, ontologies are needed to formalize shared terms. Often it is necessary to either find a previously used ontology for a particular purpose, or to develop a new one to meet a specific need. Because of the challenge involved in creating a new ontology from scratch, the latter option is often preferable. The ability of a user to select an appropriate, high-quality domain ontology from a set of available options would be most useful in knowledge engineering and in developing intelligent applications. Being able to assess an ontology\u27s quality and suitability is also important when an ontology is developed from the beginning. These capabilities, however, require good quality assessment mechanisms as well as automated support when there are a large number of ontologies from which to make a selection. This thesis provides an in-depth analysis of the current research in domain ontology evaluation, including the development of a taxonomy to categorize the numerous directions the research has taken. Based on the lessons learned from the literature review, an approach to the automatic assessment of domain ontologies is selected and a suite of ontology quality assessment metrics grounded in semiotic theory is presented. The metrics are implemented in a Domain Ontology Rating System (DoORS), which is made available as an open source web application. An additional framework is developed that would incorporate this rating system as part of a larger system to find ontology libraries on the web, retrieve ontologies from them, and assess them to select the best ontology for a particular task. An empirical evaluation in four phases shows the usefulness of the work, including a more stringent evaluation of the metrics that assess how well an ontology fits its domain and how well an ontology is regarded within its community of users

A Requirements-Based Exploration of Open-Source Software Development Projects – Towards a Natural Language Processing Software Analysis Framework

Open source projects do have requirements; they are, however, mostly informal, text descriptions found in requests, forums, and other correspondence. Understanding such requirements provides insight into the nature of open source projects. Unfortunately, manual analysis of natural language requirements is time-consuming, and for large projects, error-prone. Automated analysis of natural language requirements, even partial, will be of great benefit. Towards that end, I describe the design and validation of an automated natural language requirements classifier for open source software development projects. I compare two strategies for recognizing requirements in open forums of software features. The results suggest that classifying text at the forum post aggregation and sentence aggregation levels may be effective. Initial results suggest that it can reduce the effort required to analyze requirements of open source software development projects. Software development organizations and communities currently employ a large number of software development techniques and methodologies. This implied complexity is also enhanced by a wide range of software project types and development environments. The resulting lack of consistency in the software development domain leads to one important challenge that researchers encounter while exploring this area: specificity. This results in an increased difficulty of maintaining a consistent unit of measure or analysis approach while exploring a wide variety of software development projects and environments. The problem of specificity is more prominently exhibited in an area of software development characterized by a dynamic evolution, a unique development environment, and a relatively young history of research when compared to traditional software development: the open-source domain. While performing research on open source and the associated communities of developers, one can notice the same challenge of specificity being present in requirements engineering research as in the case of closed-source software development. Whether research is aimed at performing longitudinal or cross-sectional analyses, or attempts to link requirements to other aspects of software development projects and their management, specificity calls for a flexible analysis tool capable of adapting to the needs and specifics of the explored context. This dissertation covers the design, implementation, and evaluation of a model, a method, and a software tool comprising a flexible software development analysis framework. These design artifacts use a rule-based natural language processing approach and are built to meet the specifics of a requirements-based analysis of software development projects in the open-source domain. This research follows the principles of design science research as defined by Hevner et. al. and includes stages of problem awareness, suggestion, development, evaluation, and results and conclusion (Hevner et al. 2004; Vaishnavi and Kuechler 2007). The long-term goal of the research stream stemming from this dissertation is to propose a flexible, customizable, requirements-based natural language processing software analysis framework which can be adapted to meet the research needs of multiple different types of domains or different categories of analyses

Dual-Aspect Monism, Mind-Matter Complementarity, Self-Continuity and Evolutionary Panentheism

Physicalism as a worldview and framework for a mechanistic and materialist science seems not to have integrated the tectonic shift created by the rise of quantum physics with its notion of the personal equation of the observer. Psyche had been deliberately removed from a post-Enlightenment science. This paper explores a post-materialist science within a dual-aspect monist conception of nature in which both the mental and the physical exist in a relationship of complementarity so that they mutually exclude one another and yet are together necessary to explain Reality while being irreducible to one another. Both mind and matter emerge from an underlying holistic domain known as the unus mundus in the Jung-Pauli formulation or as the analogous implicate order in the framing of physicist David Bohm and his colleagues. Kuhnian anomalies such as the role of reflective consciousness in evolution, and phenomena including so-called “near death experiences” (NDEs), are considered from the perspective of dual-aspect monism in conjunction with an emerging evolutionary panentheism

The coral Acropora loripes genome reveals an alternative pathway for cysteine biosynthesis in animals

The metabolic capabilities of animals have been derived from well-studied model organisms and are generally considered to be well understood. In animals, cysteine is an important amino acid thought to be exclusively synthesized through the transsulfuration pathway. Corals of the genus Acropora have lost cystathionine β-synthase, a key enzyme of the transsulfuration pathway, and it was proposed that Acropora relies on the symbiosis with dinoflagellates of the family Symbiodiniaceae for the acquisition of cysteine. Here, we identify the existence of an alternative pathway for cysteine biosynthesis in animals through the analysis of the genome of the coral Acropora loripes. We demonstrate that these coral proteins are functional and synthesize cysteine in vivo, exhibiting previously unrecognized metabolic capabilities of animals. This pathway is also present in most animals but absent in mammals, arthropods, and nematodes, precisely the groups where most of the animal model organisms belong to, highlighting the risks of generalizing findings from model organisms