An ontology co-design method for the co-creation of a continuous care ontology

Ontology engineering methodologies tend to emphasize the role of the knowledge engineer or require a very active role of domain experts. In this paper, a participatory ontology engineering method is described that holds the middle ground between these two 'extremes'. After thorough ethnographic research, an interdisciplinary group of domain experts closely interacted with ontology engineers and social scientists in a series of workshops. Once a preliminary ontology was developed, a dynamic care request system was built using the ontology. Additional workshops were organized involving a broader group of domain experts to ensure the applicability of the ontology across continuous care settings. The proposed method successfully actively engaged domain experts in constructing the ontology, without overburdening them. Its applicability is illustrated by presenting the co-created continuous care ontology. The lessons learned during the design and execution of the approach are also presented

The evolution of ontology in AEC: A two-decade synthesis, application domains, and future directions

Ontologies play a pivotal role in knowledge representation, particularly beneficial for the Architecture, Engineering, and Construction (AEC) sector due to its inherent data diversity and intricacy. Despite the growing interest in ontology and data integration research, especially with the advent of knowledge graphs and digital twins, a noticeable lack of consolidated academic synthesis still needs to be addressed. This review paper aims to bridge that gap, meticulously analysing 142 journal articles from 2000 to 2021 on the application of ontologies in the AEC sector. The research is segmented through systematic evaluation into ten application domains within the construction realm- process, cost, operation/maintenance, health/safety, sustainability, monitoring/control, intelligent cities, heritage building information modelling (HBIM), compliance, and miscellaneous. This categorisation aids in pinpointing ontologies suitable for various research objectives. Furthermore, the paper highlights prevalent limitations within current ontology studies in the AEC sector. It offers strategic recommendations, presenting a well-defined path for future research to address these gaps

A manufacturing core concepts ontology to support knowledge sharing

Knowledge sharing across domains is key to bringing down the cost of production and the time to market of products. This thesis is directed to improve the knowledge sharing capability of the present systems that use information and communication technologies. Systems for different domains have structures that are made up of concepts and relations with different semantic interpretations. Therefore, knowledge sharing across such domains becomes an issue. Knowledge sharing across multiple domains can be facilitated through a system that can provide a shared understanding across multiple domains. This requires a rigorous common semantic base underlying the domains across which to share knowledge. [Continues.

Verification of knowledge shared across design and manufacture using a foundation ontology

Seamless computer-based knowledge sharing between departments of a manufacturing enterprise is useful in preventing unnecessary design revisions. A lack of interoperability between independently developed knowledge bases, however, is a major impediment in the development of a seamless knowledge sharing system. Interoperability, being an ability to overcome semantic and syntactic differences during computer-based knowledge sharing can be enhanced through the use of ontologies. Ontologies in computer science terms are hierarchical structures of knowledge stored in a computer-based knowledge base. Ontologies have been accepted by all as an interoperable medium to provide a non-subjective way of storing and sharing knowledge across diverse domains. Some semantic and syntactic differences, however, still crop up when these ontological knowledge bases are developed independently. A case study in an aerospace components manufacturing company suggests that shape features of a component are perceived differently by the designing and manufacturing departments. These differences cause further misunderstanding and misinterpretation when computer-based knowledge sharing systems are used across the two domains. Foundation or core ontologies can be used to overcome these differences and to ensure a seamless sharing of knowledge. This is because these ontologies provide a common grounding for domain ontologies to be used by individual domains or department. This common grounding can be used by the mediation and knowledge verification systems to authenticate the meaning of knowledge understood across different domains. For this reason, this research proposes a knowledge verification framework for developing a system capable of verifying knowledge between those domain ontologies which are developed out of a common core or foundation ontology. This framework makes use of ontology logic to standardize the way concepts from a foundation and core-concepts ontology are used in domain ontologies and then by using the same principles the knowledge being shared is verified. The Knowledge Frame Language which is based on Common Logic is used for formalizing example ontologies. The ontology editor used for browsing and querying ontologies is the Integrated Ontology Development Environment (IODE) by Highfleet Inc. An ontological product modelling technique is also developed in this research, to test the proposed framework in the scenario of manufacturability analysis. The proposed framework is then validated through a Java API specially developed for this purpose. Real industrial examples experienced during the case study are used for validation

Social Network Data Management

With the increasing usage of online social networks and the semantic web's graph structured RDF framework, and the rising adoption of networks in various fields from biology to social science, there is a rapidly growing need for indexing, querying, and analyzing massive graph structured data. Facebook has amassed over 500 million users creating huge volumes of highly connected data. Governments have made RDF datasets containing billions of triples available to the public. In the life sciences, researches have started to connect disparate data sets of research results into one giant network of valuable information. Clearly, networks are becoming increasingly popular and growing rapidly in size, requiring scalable solutions for network data management. This thesis focuses on the following aspects of network data management. We present a hierarchical index structure for external memory storage of network data that aims to maximize data locality. We propose efficient algorithms to answer subgraph matching queries against network databases and discuss effective pruning strategies to improve performance. We show how adaptive cost models can speed up subgraph matching query answering by assigning budgets to index retrieval operations and adjusting the query plan while executing. We develop a cloud oriented social network database, COSI, which handles massive network datasets too large for a single computer by partitioning the data across multiple machines and achieving high performance query answering through asynchronous parallelization and cluster-aware heuristics. Tracking multiple standing queries against a social network database is much faster with our novel multi-view maintenance algorithm, which exploits common substructures between queries. To capture uncertainty inherent in social network querying, we define probabilistic subgraph matching queries over deterministic graph data and propose algorithms to answer them efficiently. Finally, we introduce a general relational machine learning framework and rule-based language, Probabilistic Soft Logic, to learn from and probabilistically reason about social network data and describe applications to information integration and information fusion

A Knowledge Graph Based Integration Approach for Industry 4.0

The fourth industrial revolution, Industry 4.0 (I40) aims at creating smart factories employing among others Cyber-Physical Systems (CPS), Internet of Things (IoT) and Artificial Intelligence (AI). Realizing smart factories according to the I40 vision requires intelligent human-to-machine and machine-to-machine communication. To achieve this communication, CPS along with their data need to be described and interoperability conflicts arising from various representations need to be resolved. For establishing interoperability, industry communities have created standards and standardization frameworks. Standards describe main properties of entities, systems, and processes, as well as interactions among them. Standardization frameworks classify, align, and integrate industrial standards according to their purposes and features. Despite being published by official international organizations, different standards may contain divergent definitions for similar entities. Further, when utilizing the same standard for the design of a CPS, different views can generate interoperability conflicts. Albeit expressive, standardization frameworks may represent divergent categorizations of the same standard to some extent, interoperability conflicts need to be resolved to support effective and efficient communication in smart factories. To achieve interoperability, data need to be semantically integrated and existing conflicts conciliated. This problem has been extensively studied in the literature. Obtained results can be applied to general integration problems. However, current approaches fail to consider specific interoperability conflicts that occur between entities in I40 scenarios. In this thesis, we tackle the problem of semantic data integration in I40 scenarios. A knowledge graphbased approach allowing for the integration of entities in I40 while considering their semantics is presented. To achieve this integration, there are challenges to be addressed on different conceptual levels. Firstly, defining mappings between standards and standardization frameworks; secondly, representing knowledge of entities in I40 scenarios described by standards; thirdly, integrating perspectives of CPS design while solving semantic heterogeneity issues; and finally, determining real industry applications for the presented approach. We first devise a knowledge-driven approach allowing for the integration of standards and standardization frameworks into an Industry 4.0 knowledge graph (I40KG). The standards ontology is used for representing the main properties of standards and standardization frameworks, as well as relationships among them. The I40KG permits to integrate standards and standardization frameworks while solving specific semantic heterogeneity conflicts in the domain. Further, we semantically describe standards in knowledge graphs. To this end, standards of core importance for I40 scenarios are considered, i.e., the Reference Architectural Model for I40 (RAMI4.0), AutomationML, and the Supply Chain Operation Reference Model (SCOR). In addition, different perspectives of entities describing CPS are integrated into the knowledge graphs. To evaluate the proposed methods, we rely on empirical evaluations as well as on the development of concrete use cases. The attained results provide evidence that a knowledge graph approach enables the effective data integration of entities in I40 scenarios while solving semantic interoperability conflicts, thus empowering the communication in smart factories

User driven modelling: Visualisation and systematic interaction for end-user programming with tree-based structures

This thesis addresses certain problems encountered by teams of engineers when modelling complex structures and processes subject to cost and other resource constraints. The cost of a structure or process may be ‘read off’ its specifying model, but the language in which the model is expressed (e.g. CAD) and the language in which resources may be modelled (e.g. spreadsheets) are not naturally compatible. This thesis demonstrates that a number of intermediate steps may be introduced which enable both meaningful translation from one conceptual view to another as well as meaningful collaboration between team members. The work adopts a diagrammatic modelling approach as a natural one in an engineering context when seeking to establish a shared understanding of problems.Thus, the research question to be answered in this thesis is: ‘To what extent is it possible to improve user-driven software development through interaction with diagrams and without requiring users to learn particular computer languages?’ The goal of the research is to improve collaborative software development through interaction with diagrams, thereby minimising the need for end-users to code directly. To achieve this aim a combination of the paradigms of End-User Programming, Process and Product Modelling and Decision Support, and Semantic Web are exploited and a methodology of User Driven Modelling and Programming (UDM/P) is developed, implemented, and tested as a means of demonstrating the efficacy of diagrammatic modelling.In greater detail, the research seeks to show that diagrammatic modelling eases problems of maintenance, extensibility, ease of use, and sharing of information. The methodology presented here to achieve this involves a three step translation from a visualised ontology, through a modelling tool, to output to interactive visualisations. An analysis of users groups them into categories of system creator, model builder, and model user. This categorisation corresponds well with the three-step translation process where users develop the ontology, modelling tool, and visualisations for their problem.This research establishes and exemplifies a novel paradigm of collaborative end-user programming by domain experts. The end-user programmers can use a visual interface where the visualisation of the software exactly matches the structure of the software itself, making translation between user and computer, and vice versa, much more direct and practical. The visualisation is based on an ontology that provides a representation of the software as a tree. The solution is based on translation from a source tree to a result tree, and visualisation of both. The result tree shows a structured representation of the model with a full visualisation of all parts that leads to the computed result.In conclusion, it is claimed that this direct representation of the structure enables an understanding of the program as an ontology and model that is then visualised, resulting in a more transparent shared understanding by all users. It is further argued that our diagrammatic modelling paradigm consequently eases problems of maintenance, extensibility, ease of use, and sharing of information. This method is applicable to any problem that lends itself to representation as a tree. This is considered a limitation of the method to be addressed in a future project

An integration framework for managing rich organisational process knowledge

The problem we have addressed in this dissertation is that of designing a pragmatic framework for integrating the synthesis and management of organisational process knowledge which is based on domain-independent AI planning and plan representations. Our solution has focused on a set of framework components which provide methods, tools and representations to accomplish this task.In the framework we address a lifecycle of this knowledge which begins with a methodological approach to acquiring information about the process domain. We show that this initial domain specification can be translated into a common constraint-based model of activity (based on the work of Tate, 1996c and 1996d) which can then be operationalised for use in an AI planner. This model of activity is ontologically underpinned and may be expressed with a flexible and extensible language based on a sorted first-order logic. The model combines perspectives covering both the space of behaviour as well as the space of decisions. Synthesised or modified processes/plans can be translated to and from the common representation in order to support knowledge sharing, visualisation and mixed-initiative interaction.This work united past and present Edinburgh research on planning and infused it with perspectives from design rationale, requirements engineering, and process knowledge sharing. The implementation has been applied to a portfolio of scenarios which include process examples from business, manufacturing, construction and military operations. An archive of this work is available at: http://www.aiai.ed.ac.uk/~oplan/cpf