Evaluating and extending the Informed Consent Ontology for representing permissions from the clinical domain

The purpose of this study was to evaluate, revise, and extend the Informed Consent Ontology (ICO) for expressing clinical permissions, including reuse of residual clinical biospecimens and health data. This study followed a formative evaluation design and used a bottom-up modeling approach. Data were collected from the literature on US federal regulations and a study of clinical consent forms. Eleven federal regulations and fifteen permission-sentences from clinical consent forms were iteratively modeled to identify entities and their relationships, followed by community reflection and negotiation based on a series of predetermined evaluation questions. ICO included fifty-two classes and twelve object properties necessary when modeling, demonstrating appropriateness of extending ICO for the clinical domain. Twenty-six additional classes were imported into ICO from other ontologies, and twelve new classes were recommended for development. This work addresses a critical gap in formally representing permissions clinical permissions, including reuse of residual clinical biospecimens and health data. It makes missing content available to the OBO Foundry, enabling use alongside other widely-adopted biomedical ontologies. ICO serves as a machine-interpretable and interoperable tool for responsible reuse of residual clinical biospecimens and health data at scale.

UFO: Unified Foundational Ontology

The Unified Foundational Ontology (UFO) was developed over the last two decades by consistently putting together theories from areas such as formal ontology in philosophy, cognitive science, linguistics, and philosophical logics. It comprises a number of micro-theories addressing fundamental conceptual modeling notions, including entity types and relationship types. The aim of this paper is to summarize the current state of UFO, presenting a formalization of the ontology, along with the analysis of a number of cases to illustrate the application of UFO and facilitate its comparison with other foundational ontologies in this special issue. (The cases originate from the First FOUST Workshop – the Foundational Stance, an international forum dedicated to Foundational Ontology research.)

DOLCE: A descriptive ontology for linguistic and cognitive engineering1

dolce, the first top-level (foundational) ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. dolce is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. dolce clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, and is built according to well-established ontological methodologies, e.g. OntoClean. Because of these features, it has inspired most of the existing top-level ontologies and has been used to develop or improve standards and public domain resources (e.g. CIDOC CRM, DBpedia and WordNet). Being a foundational ontology, dolce is not directly concerned with domain knowledge. Its purpose is to provide the general categories and relations needed to give a coherent view of reality, to integrate domain knowledge, and to mediate across domains. In these 20 years dolce has shown that applied ontologies can be stable and that interoperability across reference and domain ontologies is a reality. This paper briefly introduces the ontology and shows how to use it on a few modeling cases.

YAMATO: Yet-another more advanced top-level ontology

yamato sharply distinguishes itself from other existing upper ontologies in the following respects. (1) Most importantly, yamato is designed with both engineering and philosophical minds. (2) yamato is based on a sophisticated theory of roles, given that the world is full of roles. (3) yamato has a tenable theory of functions which helps to deal with artifacts effectively. (4) Information is a ‘content-bearing’ entity and it differs significantly from the entities that philosophers have traditionally discussed. Taking into account the modern society in which a flood of information occurs, yamato has a sophisticated theory of informational objects (representations). (5) Quality and quantity are carefully organized for the sake of greater interoperability of real-world data. (6) The philosophical contribution of yamato includes a theory of objects, processes, and events. Those features are illustrated with several case studies. These features lead to the intensive application of yamato in some domains such as biomedicine and learning engineering.

GUM: The generalized upper model

GUM is a linguistically-motivated ontology originally developed to support natural language processing systems by offering a level of representation intermediate between linguistic forms and domain knowledge. Whereas modeling decisions for individual domains may need to be responsive to domain-specific criteria, a linguistically-motivated ontology offers a characterization that generalizes across domains because its design criteria are derived independently both of domain and of application. With respect to this mediating role, the use of GUM resembles (and partially predates) the adoption of upper ontologies as tools for mediating across domains and for supporting domain modeling. This paper briefly introduces the ontology, setting out its origins, design principles and applications. The example cases for this special issue are then described, illustrating particularly some of the principal differences and similarities of GUM to non-linguistically motivated upper ontologies.

BFO-based ontology enhancement to promote interoperability in BIM

Building Information Modelling (BIM) is a process for managing construction project information in such a way as to provide a basis for enhanced decision-making and for collaboration in a construction supply chain. One impediment to the uptake of BIM is the limited interoperability of different BIM systems. To overcome this problem, a set of Industry Foundation Classes (IFC) has been proposed as a standard for the construction industry. Building on IFC, the ifcOWL ontology was developed in order to facilitate representation of building data in a consistent fashion across the Web by using the Web Ontology Language (OWL). This study presents a critical analysis of the ifcOWL ontology and of the associated interoperability issues. It shows how these issues can be resolved by using Basic Formal Ontology (ISO/IEC 21838-2) as top-level architecture. A set of competency questions is used as the basis for comparison of the original ifcOWL with the enhanced ontology, and the latter is used to align with a second ontology – the ontology for building intelligent environments (DOGONT) – in order to demonstrate the added value derived from BFO by showing how querying the enhanced ifcOWL yields useful additional information.

Ontologies in human–computer interaction: A systematic literature review

Human–Computer Interaction (HCI) is a multidisciplinary area that involves a diverse body of knowledge and a complex landscape of concepts, which can lead to semantic problems, hampering communication and knowledge transfer. Ontologies have been successfully used to solve semantics and knowledge-related problems in several domains. This paper presents a systematic literature review that investigated the use of ontologies in the HCI domain. The main goal was to find out how HCI ontologies have been used and developed. 35 ontologies were identified. As a result, we noticed that they cover different HCI aspects, such as user interface, interaction phenomenon, pervasive computing, user modeling / profile, HCI design, interaction experience and adaptive interactive system. Although there are overlaps, we did not identify reuse among the 35 analyzed ontologies. The ontologies have been used mainly to support knowledge representation and reasoning. Although ontologies have been used in HCI for more than 25 years, their use became more frequent in the last decade, when ontologies address a higher number of HCI aspects and are represented as both conceptual and computational models. Concerning how ontologies have been developed, we noticed that some good practices of ontology engineering have not been followed. Considering that the quality of an ontology directly influences the quality of the solution built based on it, we believe that there is an opportunity for HCI and ontology engineering professionals to get closer to build better and more effective ontologies, as well as ontology-based solutions.

Formalizing commitments using the event calculus and RuleML

Smart Contracts enable the automated execution of exchanges on the blockchain. From an ontological perspective, smart contracts create and automate the fulfillment of social commitments between actors. Whereas traditional deontic logic is used to make a legal determination in contractual multi-actor interactions, this paper focuses on the consequences of these actions resulting from that determination, thereby shifting the focus from monitoring to execution. The interactions between actors and the consequences in terms of commitments have not yet been formalized for smart contracts. The perspective of smart contracts is interesting, since they are considered to be autonomous agents, able to generate automated actions. We use the Event Calculus as a formal logic to represent and reason about the effects of these automated actions and the resulting commitments. Since the Event Calculus deals with local events and the consideration of time, this approach enables the uniform representation of commitments, including their operations and reasoning rules.

Identitas: Semantics-free and human-readable identifiers

In this article, we present a new approach to identifiers, one that aims to improve the management of ontologies. This approach overcomes some of the main flaws associated with the existing approaches, providing alternative solutions. Ontology identifiers are the key for each entity defined in an ontology, and enable a unique and persistent reference to each term. The form of identifiers has been the subject of discussion, which has resulted in a number of different schemes. It is often recommended that identifiers for ontology terms should be semantics-free or meaningless. One practice is to use numeric identifiers, starting at one and working upwards. However, this has a number of disadvantages: it does not allow for concurrent development, is relatively hard to read, and it is difficult to detect errors when an identifier is misused. From the perspective of development, solving these issues could facilitate the process of building and managing ontologies. Here, we suggest random identifiers to enable concurrent development, while exploiting the proquint library to overcome the problems of memorability and pronounceability. Finally, a checksum is implemented to prevent the occurrence of errors while accessing relatively similar identifiers. Availability and Implementation: The software is available from https://github.com/Nizal-Shammry/identitas-j. It has been integrated into environments for ontology development such as Tawny-OWL and Protégé.

A validation & verification driven ontology: An iterative process

Designing an ontology that meets the needs of end-users, e.g., a medical team, is critical to support the reasoning with data. Therefore, an ontology design should be driven by the constant and efficient validation of end-users needs. However, there is not an existing standard process in knowledge engineering that guides the ontology design with the required quality. There are several ontology design processes, which range from iterative to sequential, but they fail to ensure the practical application of an ontology and to quantitatively validate end-user requirements through the evolution of an ontology. In this paper, an ontology design process is proposed, which is driven by end-user requirements, defined as Competency Questions (CQs). The process is called CQ-Driven Ontology DEsign Process (CODEP) and it includes activities that validate and verify the incremental design of an ontology through metrics based on defined CQs. CODEP has also been applied in the design and development of an ontology in the context of a Mexican Hospital for supporting Neurologist specialists. The specialists were involved, during the application of CODEP, in collecting quality measurements and validating the ontology increments. This application can demonstrate the feasibility of CODEP to deliver ontologies with similar requirements in other contexts.