An Ontological Account of the Action Theory of Economic Exchanges

In recent years, there has been an increasing interest in thedevelopment of ontologically well-founded conceptual models for Information Systems in areas such as Service Management, Accounting Information Systems and Financial Reporting. Economic exchanges are central phenomena in these areas. For this reason, they occupy a prominent position in modelling frameworks such as the REA (Resource-EventAction) ISO Standard as well as the FIBO (Financial Industry BusinessOntology). In this paper, we begin a well-founded ontological analysisof economic exchanges inspired by a recent ontological view on the nature of economic transactions. According to this view, what counts asan economic transaction is based on an agreement on the actions thatthe agents are committed to perform. The agreement is in turn based on convergent preferences about the course of action to bring about. This view enables a unified treatment of economic exchanges, regardless the object of the transaction, and complies with the view that all economictransactions are about services. In this paper, we start developing our analysis in the framework of the Unified Foundational Ontology (UFO)

An ontology-based approach to engineering ethicality requirements

In a world where Artificial Intelligence (AI) is pervasive, humans may feel threatened or at risk by giving up control to machines. In this context, ethicality becomes a major concern to prevent AI systems from being biased, making mistakes, or going rogue. Requirements Engineering (RE) is the research area that can exert a great impact in the development of ethical systems by design. However, proposing concepts, tools and techniques that support the incorporation of ethicality into the software development processes as explicit requirements remains a great challenge in the RE field. In this paper, we rely on Ontology-based Requirements Engineering (ObRE) as a method to elicit and analyze ethicality requirements (‘Ethicality requirements’ is adopted as a name for the class of requirements studied in this paper by analogy to other quality requirements studied in software engineering, such as usability, reliability, and portability, etc. The use of this term (as opposed to ‘ethical requirements’) highlights that they represent requirements for ethical systems, analogous to how ‘trustworthiness requirements’ represent requirements for trustworthy systems. To put simply: the predicates ‘ethical’ or ‘trustworthy’ are not meant to be predicated over the requirements themselves). ObRE applies ontological analysis to ontologically unpack terms and notions that are referred to in requirements elicitation. Moreover, this method instantiates the adopted ontology and uses it to guide the requirements analysis activity. In a previous paper, we presented a solution concerning two ethical principles, namely Beneficence and Non-maleficence. The present paper extends the previous work by targeting two other important ethicality principles, those of Explicability and Autonomy. For each of these new principles, we do ontological unpacking of the relevant concepts, and we present requirements elicitation and analysis guidelines, as well as examples in the context of a driverless car case. Furthermore, we validate our approach by analysing the requirements elicitation made for the driverless car case in contrast with a similar case, and by assessing our method’s coverage w.r.t European Union guidelines for Trustworthy AI.</p

Semantics, Ontology and Explanation

The terms 'semantics' and 'ontology' are increasingly appearing together with 'explanation', not only in the scientific literature, but also in organizational communication. However, all of these terms are also being significantly overloaded. In this paper, we discuss their strong relation under particular interpretations. Specifically, we discuss a notion of explanation termed ontological unpacking, which aims at explaining symbolic domain descriptions (conceptual models, knowledge graphs, logical specifications) by revealing their ontological commitment in terms of their assumed truthmakers, i.e., the entities in one's ontology that make the propositions in those descriptions true. To illustrate this idea, we employ an ontological theory of relations to explain (by revealing the hidden semantics of) a very simple symbolic model encoded in the standard modeling language UML. We also discuss the essential role played by ontology-driven conceptual models (resulting from this form of explanation processes) in properly supporting semantic interoperability tasks. Finally, we discuss the relation between ontological unpacking and other forms of explanation in philosophy and science, as well as in the area of Artificial Intelligence

Foundational Ontologies meet Ontology Matching: A Survey

Ontology matching is a research area aimed at finding ways to make different ontologies interoperable. Solutions to the problem have been proposed from different disciplines, including databases, natural language processing, and machine learning. The role of foundational ontologies for ontology matching is an important one. It is multifaceted and with room for development. This paper presents an overview of the different tasks involved in ontology matching that consider foundational ontologies. We discuss the strengths and weaknesses of existing proposals and highlight the challenges to be addressed in the future

A Reference Meta-model to Understand DNA Variant Interpretation Guidelines

Determining the role of a DNA variant in patients’ health status – a process known as variant interpretation – is highly critical for precision medicine applications. Variant interpretation involves a complex process where, regrettably, there is still debate on how to combine and weigh diverse available evidence to achieve proper and consistent answers. Indeed, at the time of writing, 22 different variant interpretation guidelines are available to the scientific community, each of them attempting to establish a framework for standardizing the interpretation process. However, these guidelines are qualitative and vague by nature, which hinders their streamlined application and potential automation. Consequently, more precise definitions are needed. Conceptual modeling provides the means to bring clarification within this domain. This paper presents our efforts to define and use a UML meta-model that describes the main concepts involved in the definition of variant interpretation guidelines and the constructs they evaluate. The precise conceptual definition of the guidelines allowed us to identify four common misinterpretation patterns that hamper the correct interpretation process and that can consequently affect classification results. In several proposed examples, the use of the meta-model provides support in identifying the inconsistencies in the observed process; this result paves the way for further proposing reconciliation strategies for the existing guidelines

On the use of requirement patterns to analyse request for proposal documents

Requirements reuse is still today a difficult goal to achieve. One particular context in which requirements reuse may give more benefits than costs is that of call for tenders projects, due to the similarity of the requirements documents (which take the form of requests for proposal documents, RfPs) from one project to another. In this paper, we present an approach aimed at making systematic the assessment of RfPs that technology providers need to conduct in order to decide whether they present a bid or not in a call for tenders project. The approach extends a metamodel we already defined for the former PABRE method, which has a similar goal but from the perspective of the organization that issues the call for tenders. The method is illustrated with an exploratory case study in the field of the railway systems domain.Peer ReviewedPostprint (author's final draft

O4OA Specification

This document is the reference ontology specification for the Ontology for Ontological Analysis (O4OA) version 2.6.This work has been developed under the project Digital Knowledge Graph – Adaptable Analytics API with the financial support of Accenture LTD, the Generalitat Valenciana through the CoMoDiD project (CIPROM/2021/023), the Spanish State Research Agency through the DELFOS (PDC2021-121243-I00) and SREC (PID2021-123824OB-I00) projects, MICIN/AEI/10.13039/501 100011033 and co-financed with ERDF and the European Union Next Generation EU/PRTR.Franco Martins Souza, B.; Guizzardi, R.; Pastor López, O. (2023). O4OA Specification. http://hdl.handle.net/10251/19672

Fostering Sustainability through Visualization Techniques for Real-Time IoT Data: A Case Study Based on Gas Turbines for Electricity Production

Improving sustainability is a key concern for industrial development. Industry has recently been benefiting from the rise of IoT technologies, leading to improvements in the monitoring and breakdown prevention of industrial equipment. In order to properly achieve this monitoring and prevention, visualization techniques are of paramount importance. However, the visualization of real-time IoT sensor data has always been challenging, especially when such data are originated by sensors of different natures. In order to tackle this issue, we propose a methodology that aims to help users to visually locate and understand the failures that could arise in a production process.This methodology collects, in a guided manner, user goals and the requirements of the production process, analyzes the incoming data from IoT sensors and automatically derives the most suitable visualization type for each context. This approach will help users to identify if the production process is running as well as expected; thus, it will enable them to make the most sustainable decision in each situation. Finally, in order to assess the suitability of our proposal, a case study based on gas turbines for electricity generation is presented.This work has been co-funded by the ECLIPSE-UA (RTI2018-094283-B-C32) project funded by Spanish Ministry of Science, Innovation, and Universities and the DQIoT (INNO-20171060) project funded by the Spanish Center for Industrial Technological Development, approved with an EUREKA quality seal (E!11737DQIOT). Ana Lavalle holds an Industrial PhD Grant (I-PI 03-18) co-funded by the University of Alicante and the Lucentia Lab Spin-off Company

Operationalizing and automating data governance

The ability to cross data from multiple sources represents a competitive advantage for organizations. Yet, the governance of the data lifecycle, from the data sources into valuable insights, is largely performed in an ad-hoc or manual manner. This is specifically concerning in scenarios where tens or hundreds of continuously evolving data sources produce semi-structured data. To overcome this challenge, we develop a framework for operationalizing and automating data governance. For the first, we propose a zoned data lake architecture and a set of data governance processes that allow the systematic ingestion, transformation and integration of data from heterogeneous sources, in order to make them readily available for business users. For the second, we propose a set of metadata artifacts that allow the automatic execution of data governance processes, addressing a wide range of data management challenges. We showcase the usefulness of the proposed approach using a real world use case, stemming from the collaborative project with the World Health Organization for the management and analysis of data about Neglected Tropical Diseases. Overall, this work contributes on facilitating organizations the adoption of data-driven strategies into a cohesive framework operationalizing and automating data governance.This work was partly supported by the DOGO4ML project, funded by the Spanish Ministerio de Ciencia e Innovación under project PID2020-117191RB-I00/AEI/10.13039/501100011033. Sergi Nadal is partly supported by the Spanish Ministerio de Ciencia e Innovación, as well as the European Union - NextGenerationEU, under project FJC2020-045809-I/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version