Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.

Knowledge-based Chord Embeddings

This thesis develops AI methods as a contribution to computational musicology, an interdisciplinary field that studies music with computers. In systematic musicology a composition is defined as the combination of harmony, melody and rhythm. According to de La Borde, harmony alone "merits the name of composition". This thesis focuses on analysing the harmony from a computational perspective. We concentrate on symbolic music representation and address the problem of formally representing chord progressions in western music compositions. Informally, chords are sets of pitches played simultaneously, and chord progressions constitute the harmony of a composition. Our approach combines ML techniques with knowledge-based techniques. We design and implement the Modal Harmony ontology (MHO), using OWL. It formalises one of the most important theories in western music: the Modal Harmony Theory. We propose and experiment with different types of embedding methods to encode chords, inspired by NLP and adapted to the music domain, using both statistical (extensional) knowledge by relying on a huge dataset of chord annotations (ChoCo), intensional knowledge by relying on MHO and a combination of the two. The methods are evaluated on two musicologically relevant tasks: chord classification and music structure segmentation. The former is verified by comparing the results of the Odd One Out algorithm to the classification obtained with MHO. Good performances (accuracy: 0.86) are achieved. We feed a RNN for the latter, using our embeddings. Results show that the best performance (F1: 0.6) is achieved with embeddings that combine both approaches. Our method outpeforms the state of the art (F1 = 0.42) for symbolic music structure segmentation. It is worth noticing that embeddings based only on MHO almost equal the best performance (F1 = 0.58). We remark that those embeddings only require the ontology as an input as opposed to other approaches that rely on large datasets.

Expert system application on preliminary design of water retaining structures

Design of liquid retaining structures involves many decisions to be made by the designer based on rules of thumb, heuristics, judgment, code of practice and previous experience. Various design parameters to be chosen include configuration, material, loading, etc. A novice engineer may face many difficulties in the design process. Recent developments in artificial intelligence and emerging field of knowledge-based system (KBS) have made widespread applications in different fields. However, no attempt has been made to apply this intelligent system to the design of liquid retaining structures. The objective of this study is, thus, to develop a KBS that has the ability to assist engineers in the preliminary design of liquid retaining structures. Moreover, it can provide expert advice to the user in selection of design criteria, design parameters and optimum configuration based on minimum cost. The development of a prototype KBS for the design of liquid retaining structures (LIQUID), using blackboard architecture with hybrid knowledge representation techniques including production rule system and object-oriented approach, is presented in this paper. An expert system shell, Visual Rule Studio, is employed to facilitate the development of this prototype system. (C) 2002 Elsevier Science Ltd. All rights reserved.

Improving discovery in the life sciences using semantic Web technologies and linked data: design principles for life sciences knowledge organization systems

Dissertation presented to obtain the Ph.D degree in Bioinformatics

Histological and histochemical evaluation of human oral mucosa constructs developed by tissue engineering

Reconstruction of large oral mucosa defects is often challenging, since the shortage of healthy oral mucosa to replace the excised tissues is very common. In this context, tissue engineering techniques may provide a source of autologous tissues available for transplant in these patients. In this work, we developed a new model of artificial oral mucosa generated by tissue engineering using a fibrin-agarose scaffold. For that purpose, we generated primary cultures of human oral mucosa fibroblasts and keratinocytes from small biopsies of normal oral mucosa using enzymatic treatments. Then we determined the viability of the cultured cells by electron probe quantitative X-ray microanalysis, and we demonstrated that most of the cells in the primary cultures were alive and had high K/Na ratios. Once cell viability was determined, we used the cultured fibroblasts and keratinocytes to develop an artificial oral mucosa construct by using a fibrin-agarose extracellular matrix and a sequential culture technique using porous culture inserts. Histological analysis of the artificial tissues showed high similarities with normal oral mucosa controls. The epithelium of the oral substitutes had several layers, with desmosomes and apical microvilli and microplicae. Both the controls and the oral mucosa substitutes showed high suprabasal expression of cytokeratin 13 and low expression of cytokeratin 10. All these results suggest that our model of oral mucosa using fibrin-agarose scaffolds show several similarities with native human oral mucosa.

Coculture of bladder urothelial and smooth muscle cells on small intestinal submucosa: potential applications for tissue engineering technology.

PURPOSE: Small intestinal submucosa is a xenogenic, acellular, collagen rich membrane with inherent growth factors that has previously been shown to promote in vivo bladder regeneration. We evaluate in vitro use of small intestinal submucosa to support the individual and combined growth of bladder urothelial cells and smooth muscle cells for potential use in tissue engineering techniques, and in vitro study of the cellular mechanisms involved in bladder regeneration. MATERIALS AND METHODS: Primary cultures of human bladder urothelial cells and smooth muscle cells were established using standard enzymatic digestion or explant techniques. Cultured cells were then seeded on small intestinal submucosa at a density of 1 x 105 cells per cm.2, incubated and harvested at 3, 7, 14 and 28 days. The 5 separate culture methods evaluated were urothelial cells seeded alone on the mucosal surface of small intestinal submucosa, smooth muscle cells seeded alone on the mucosal surface, layered coculture of smooth muscle cells seeded on the mucosal surface followed by urothelial cells 1 hour later, sandwich coculture of smooth muscle cells seeded on the serosal surface followed by seeding of urothelial cells on the mucosal surface 24 hours later, and mixed coculture of urothelial cells and smooth muscle cells mixed and seeded together on the mucosal surface. Following harvesting at the designated time points small intestinal submucosa cell constructs were formalin fixed and processed for routine histology including Masson trichrome staining. Specific cell growth characteristics were studied with particular attention to cell morphology, cell proliferation and layering, cell sorting, presence of a pseudostratified urothelium and matrix penetrance. To aid in the identification of smooth muscle cells and urothelial cells in the coculture groups, immunohistochemical analysis was performed with antibodies to alpha-smooth muscle actin and cytokeratins AE1/AE3. RESULTS: Progressive 3-dimensional growth of urothelial cells and smooth muscle cells occurred in vitro on small intestinal submucosa. When seeded alone urothelial cells and smooth muscle cells grew in several layers with minimal to no matrix penetration. In contrast, layered, mixed and sandwich coculture methods demonstrated significant enhancement of smooth muscle cell penetration of the membrane. The layered and sandwich coculture techniques resulted in organized cell sorting, formation of a well-defined pseudostratified urothelium and multilayered smooth muscle cells with enhanced matrix penetration. With the mixed coculture technique there was no evidence of cell sorting although matrix penetrance by the smooth muscle cells was evident. Immunohistochemical studies demonstrated that urothelial cells and smooth muscle cells maintain the expression of the phenotypic markers of differentiation alpha-smooth muscle actin and cytokeratins AE1/AE3. CONCLUSIONS: Small intestinal submucosa supports the 3-dimensional growth of human bladder cells in vitro. Successful combined growth of bladder cells on small intestinal submucosa with different seeding techniques has important future clinical implications with respect to tissue engineering technology. The results of our study demonstrate that there are important smooth muscle cell-epithelial cell interactions involved in determining the type of in vitro cell growth that occurs on small intestinal submucosa. Small intestinal submucosa is a valuable tool for in vitro study of the cell-cell and cell-matrix interactions that are involved in regeneration and various disease processes of the bladder.

Application of metabolic engineering to the production of scopolamine

Scopolamine is an alkaloid widely used in medicine for its anticholinergic activity. The aim of this review is to show that metabolic engineering techniques constitute a suitable tool to improve the production of tropane alkaloids, focusing in particular on scopolamine. We present an overview of results obtained by various research groups, including our own, who have studied the overexpression of genes involved in the biosynthesis of scopolamine in different plant species that produce tropane alkaloids. Experiments carried out to improve production in hairy root cultures will also be described, as well as those attempting to biotransform hyoscyamine into scopolamine in roots and transgenic tobacco cells.

Using Analogy to Acquire Commonsense Knowledge from Human Contributors

The goal of the work reported here is to capture the commonsense knowledge of non-expert human contributors. Achieving this goal will enable more intelligent human-computer interfaces and pave the way for computers to reason about our world. In the domain of natural language processing, it will provide the world knowledge much needed for semantic processing of natural language. To acquire knowledge from contributors not trained in knowledge engineering, I take the following four steps: (i) develop a knowledge representation (KR) model for simple assertions in natural language, (ii) introduce cumulative analogy, a class of nearest-neighbor based analogical reasoning algorithms over this representation, (iii) argue that cumulative analogy is well suited for knowledge acquisition (KA) based on a theoretical analysis of effectiveness of KA with this approach, and (iv) test the KR model and the effectiveness of the cumulative analogy algorithms empirically. To investigate effectiveness of cumulative analogy for KA empirically, Learner, an open source system for KA by cumulative analogy has been implemented, deployed, and evaluated. (The site "1001 Questions," is available at http://teach-computers.org/learner.html). Learner acquires assertion-level knowledge by constructing shallow semantic analogies between a KA topic and its nearest neighbors and posing these analogies as natural language questions to human contributors. Suppose, for example, that based on the knowledge about "newspapers" already present in the knowledge base, Learner judges "newspaper" to be similar to "book" and "magazine." Further suppose that assertions "books contain information" and "magazines contain information" are also already in the knowledge base. Then Learner will use cumulative analogy from the similar topics to ask humans whether "newspapers contain information." Because similarity between topics is computed based on what is already known about them, Learner exhibits bootstrapping behavior --- the quality of its questions improves as it gathers more knowledge. By summing evidence for and against posing any given question, Learner also exhibits noise tolerance, limiting the effect of incorrect similarities. The KA power of shallow semantic analogy from nearest neighbors is one of the main findings of this thesis. I perform an analysis of commonsense knowledge collected by another research effort that did not rely on analogical reasoning and demonstrate that indeed there is sufficient amount of correlation in the knowledge base to motivate using cumulative analogy from nearest neighbors as a KA method. Empirically, evaluating the percentages of questions answered affirmatively, negatively and judged to be nonsensical in the cumulative analogy case compares favorably with the baseline, no-similarity case that relies on random objects rather than nearest neighbors. Of the questions generated by cumulative analogy, contributors answered 45% affirmatively, 28% negatively and marked 13% as nonsensical; in the control, no-similarity case 8% of questions were answered affirmatively, 60% negatively and 26% were marked as nonsensical.

Knowledge Technologies

An overview of COMP3028 Knowledge Technologies

Involving users in expert system development

The ultimate criterion of success for interactive expert systems is that they will be used, and used to effect, by individuals other than the system developers. A key ingredient of success in most systems is involving users in the specification and development of systems as they are being built. However, until recently, system designers have paid little attention to ascertaining user needs and to developing systems with corresponding functionality and appropriate interfaces to match those requirements. Although the situation is beginning to change, many developers do not know how to go about involving users, or else tackle the problem in an inadequate way. This paper discusses the need for user involvement and considers why many developers are still not involving users in an optimal way. It looks at the different ways in which users can be involved in the development process and describes how to select appropriate techniques and methods for studying users. Finally, it discusses some of the problems inherent in involving users in expert system development, and recommends an approach which incorporates both ethnographic analysis and formal user testing.

Translational research and therapeutic applications of neural crest-derived stem cells in regenerative periodontology

Regeneration of periodontal tissues aims to utilize tissue engineering techniques to restore lost periodontal tissues including the cementum, periodontal ligament and alveolar bone. Regenerative dentistry and its special field regenerative periodontology represent relatively new and emerging branches of translational stem cell biology and regenerative medicine focusing on replacing and regenerating dental tissues to restore or re-establish their normal function lost during degenerative diseases or acute lesions. The regeneration itself can be achieved through transplantation of autologous or allogenic stem cells, or by improving the tissue self-repair mechanisms (e.g. by application of growth factors). In addition, a combination of stem cells or stem cell-containing tissue with bone implants can be used to improve tissue integration and the clinical outcome. As the oral cavity represents a complex system consisting of teeth, bone, soft tissues and sensory nerves, regenerative periodontology relies on the use of stem cells with relatively high developmental potential. Notably, the potential use of pluripotent stem cell types such as human embryonic stem cells or induced pluripotent stem cells is still aggravated by ethical and practical problems. Thus, other cellular sources such as those readily available in the postnatal craniofacial area and particularly in oral structures offer a much better and realistic alternative as cellular regenerative sources. In this review, we summarize current knowledge on the oral neural crest-derived stem cell populations (oNCSCs) and discuss their potential in regenerative periodontology.

Prototype Generation from Ontology Charts

Semantic Analysis is a business analysis method designed to capture system requirements. While these requirements may be represented as text, the method also advocates the use of Ontology Charts to formally denote the system's required roles, relationships and forms of communication. Following model driven engineering techniques, Ontology Charts can be transformed to temporal Database schemas, class diagrams and component diagrams, which can then be used to produce software systems. A nice property of these transformations is that resulting system design models lend themselves to complicated extensions that do not require changes to the design models. For example, resulting databases can be extended with new types of data without the need to modify the database schema of the legacy system. Semantic Analysis is not widely used in software engineering, so there is a lack of experts in the field and no design patterns are available. This make it difficult for the analysts to pass organizational knowledge to the engineers. This study describes an implementation that is readily usable by engineers, which includes an automated technique that can produce a prototype from an Ontology Chart. The use of such tools should enable developers to make use of Semantic Analysis with minimal expertise of ontologies and MDA.