Ebook: Formal Ontology in Information Systems

This volume collects the papers presented at the 9th edition of the Formal Ontology in Information Systems conference, FOIS 2016, held July 6–9, 2016, in Annecy, France. As in the previous editions, FOIS 2016 included keynote addresses, full paper presentations, an Ontology Competition, an Early Career Symposium in its scientific program and was preceded by the Interdisciplinary Summer School on Ontological Analysis, now at its third edition and held June 27–July 1 in Bolzano-Bozen, Italy.

A new entry in FOIS 2016 has been the Demo Session, an excellent forum to advertise the applicability of results and software —both ontology based and for the ontology life-cycle— as well as to receive feedback from the international ontology research community.

The Ontology Competition was firstly introduced to the conference series at FOIS 2014 and the topic for this year was “Representing Change in Ontologies”; its aim was to spread best practices in the ontology community and in fact ontologies where evaluated according to predefined criteria, such as expressivity, performance with automatic reasoners, reusability, philosophical soundness etc.; all ontologies accepted for presentation have been made publicly available at ontohub.org/fois-ontology-competition.

The Early Career Symposium, in turn, provided early career scientists the opportunity to present their work and obtain fist-hand feedback and mentorship from senior scientists in their field as well as to meet and discuss their work with each other at a PhD Lounge.

The main conference track received 80 full papers, marking a continuation of the high submission numbers reached in the 2014 and previous editions, while 8 submissions were received for the Ontology Competition, 5 for the Early Career Symposium, and 4 for the Demonstration Session. Together, these submissions came from 29 countries in all continents. Based on the reviews we received from the Program Committee, we accepted 25 full papers (an acceptance rate of 30.9%) for the main track. The Ontology Competition track included 3 papers, the Early Career Symposium accepted 5 proposals for presentation as posters and lightning talks in a dedicated session of the conference, and 3 systems were accepted for live demonstration.

In addition, the conference hosted 4 specialized workshops: International Workshop on Ontology Modularity, Contextuality and Evolution (WOMoCoE), CAOS (First International Workshop on Cognition and Ontologies), New Standards for the Working Ontologist: Common Logic and DOL, and Onto.Com (Ontologies and Conceptual Modeling).

The full papers show the liveliness and growth of formal ontology as a body of theories and methods informing (and informed by) the design and use of information systems, including the semantic web. The application domains addressed include geography, biomedicine, economics, social reality and engineering. The dimensions of space, time and measurement, as well as human cognition and language, continue to pose ontological challenges and elicit novel ideas.

Workshops, finally, united researchers and practitioners working on a particular research challenge, method, or application. Winners of the Ontology Competition as well as of the FOIS Best Paper Award were announced during the conference. Awards and runners-up can be found at iaoa.org/fois2016/.

Scientific conferences are kept alive by the authors submitting reports on their work, whether these get accepted or not. The scientific standards, in turn, are collectively defined and enforced by the program committee. We want to sincerely thank both groups (which, of course, overlap in fruitful ways) for their hard work and dedication to FOIS.

This edition of the conference has been organized by the University Savoie-Mt Blanc and has received the support of AfIA (Association franaise pour l'Intelligence Artificielle), and we express our gratitude to both. FOIS 2016, like all of its predecessors, has been scientifically promoted by the International Association for Ontologies and its Applications (IAOA – iaoa.org), which has also encouraged the participation of students by financing several student grants. Last but not least, we would like to thank our three invited speakers, Gilberto Câmara, Stephen Mumford, and Friederike Moltmann, for delivering inspiring keynotes, as well as the Conference Chair, Giancarlo Guizzardi, and the Local Chairs, Patrick Barlatier and Richard Dapoigny, for managing all of the strategies and details that have made the conference a productive interaction of researchers from the growing range of disciplines that contribute to formal ontology.

Roberta Ferrario

Werner Kuhn

Classifying and describing the Earth's land use and land cover present unique challenges, leading to a lack of harmonization between existing land classification systems. These problems arise partly because current classification systems take a static view of the world. As such, they aim to support unambiguous definitions of land cover and land use classes at one particular moment. Since the Earth's land cover is continuously changing, such static definitions are limited. This talk considers how large Earth Observation data sets can help to define a new generation of spatio-temporal ontologies of land use and land cover. These ontologies will distinguish terms such as “forest” and “savanna”, associated to continuants, from terms such as “deforestation” and “degradation”, related to occurrents. This novel approach is better suited to describe the land dynamics of our ever-changing planet.

Philosophers have long struggled to understand the notion of strong, as opposed to merely epistemic, emergence. One such genuinely metaphysical way would be to accept that the powers of wholes can under certain conditions be more than the sums of the powers of the parts. But what are the conditions under which emergence occurs and can we be sure that the suggested sense of emergence is strong enough? Arrangement of component powers will be crucial as the same powers differently arranged can constitute different resultant powers of their wholes. This shows that the composition of powers is not always linear and is non-mereological but it also shows an inadequacy of the vector model. On the plus side, it gives us a model for composition that is apt for technical artefacts and complex socio-technical systems. This version of emergentism also permits plausible cases of top-down causation given that causes and effects are simultaneous on the powers view.

This talk will outline a novel semantics of modals based not on possible worlds and quantifiers ranging over them, but on what I will call ‘modal objects’, entities of the sort of permissions, obligations, needs, abilities, and essences. According to that semantics, modal predicates take modal objects as their implicit (Davidsonian) argument and the complement clause (or prejacent) of the modal acts as a predicate characterizing the modal object in terms of its satisfiers (truthmakers) and possibly violators (falsifiers), in roughly the sense of Fine's recent truthmaker semantics. On this approach, the difference between modals of necessity and possibility is made a matter of ontology as are inferential relations among modal sentences.

The reuse of ontologies is critical to their value as a means of knowledge representation. Unfortunately, reuse also still poses a considerable challenge for the ontological community. One reason for this is the lack of a formal definition of reuse. How can we attempt to perform or even assist this sort of ontology design, if we have no clear understanding of what constitutes reuse, and what does not? In this work we aim to remedy this situation by providing a formal definition of the concepts of reuse and reusability. Beyond providing a clear understanding of these concepts, part of the resulting definition is a characterization of the operations of reuse that can be leveraged to determine how a given ontology(s) must be reused to satisfy some specified requirements. This serves not only to provide direction for the task of reuse, but also to assess the implications of reusing an ontology(s), a priori. Collectively, the solutions presented in this paper serve as a major step in improving the current state of reuse.

This paper aims to lay a foundation for a systematic study of mechanisms for construction of definitions within a formal theory, by investigating operators for incremental construction of definitions of new relations from an existing set of primitives and previously defined relations. To illustrate our method, we apply it to two of the best known relation sets studied in KRR: Allen's Interval Algebra and Region Connection Calculus. We also show that systematic exploration of definitional possibilities can yield interesting insights into relation sets that were originally defined in a more ad hoc way, and opens the possibility for discovering new vocabulary for extending or refining existing calculi or for developing completely new calculi.

To understand what ontologies do through their definitions, we propose a theoretical explanation of the functions of definitions in ontologies backed by empirical neuropsychological studies. Our goal is to show how these functions should motivate (i) the systematic inclusion of definitions in ontologies and (ii) the adaptation of definition content and form to the specific context of use of ontologies.

Space and time are basic categories of any top-level ontology. They account for fundamental assumptions of the modes of existence of those individuals that are said to be in space and time. The present paper is devoted to GFO-Space, the ontology of space in the General Formal Ontology (GFO). This ontology is introduced by a set of axioms formalized in first-order logic and further elucidated by consequences of the axiomatization.

The theory is based on four primitives: the category of space regions, the relations of being a spatial part and being a spatial boundary, as well as the relation of spatial coincidence. The presence of boundaries and the notion of coincidence witness an inspiration of the ontology by well-motivated ideas of Franz Brentano on space, time and the continuum. Taking up a line of prior investigations of his approach, the present work contributes a further step in establishing a corresponding ontology of space, employing rigorous logical methods.

How can data analysts identify spatio-temporal datasets that are suitable for their task? Answering this question is not only dependent on the aim of the analysis and the semantic contents of the data, but also on knowing whether the required data combinations and transformations, spatio-temporal analysis methods, charts and map visualizations are meaningfully applicable to the data. Operators need to assess whether they can meaningfully apply analytical operations to data to derive the information required. Answering this question in a general and computationally executable way is a crucial step on our way towards supporting data analysts and their research practice in e-Science. We propose an ontology design pattern for spatio-temporal information that enables to reason about the applicability of a number of fundamental classes of analyses in relation to given data, i.e., whether data sets can be compared, transformed, combined, and whether summary statistics can be applied to them. We demonstrate this ontology implemented in OWL through a set of corresponding SPARQL queries applied to meta-data of datasets from the AURIN portal.

This paper presents a new mereological approach to formalizing geometric notions of incidence, congruence, and parallelism over extended regions. The axiomatization was built extending a decidable pre-mereological base language, showing where the geometric framework requires first-order extension. Important outcomes are in the investigation of how to define incidence between extended geometric objects that are suitable candidates to replace points, lines, and planes in a purely region-based first-order framework. Moreover, the mereogeometric approach proposed is shown to have a key advantage in allowing dimensionality to be a relative concept in contrast to it being an absolute concept encoded in the types of geometric entities. Especially this property, one may conclude, could make mereogeometry attractive for formalizing geometric relations in a cognitively adequate manner for applications that require the same flexibility of switching between conceptualizations of space of different dimensionality as human beings show in language use.

Land use and urban development surveys involve the interpretation of a large volume of data coming from satellite images processing as well as from remote sensors networks. In order to facilitate this interpretation, the development of a multipurpose Intelligent Data Analysis (IDA) framework for supporting geographical data perception is proposed here. The framework makes use of semantic technologies and relies on a novel knowledge model composed by a foundational ontology (DOLCE Ultra-Lite, also called DUL), three core reference ontologies (the Temporal Abstraction Ontology or TAO, the Semantic Sensor Network ontology or SSN and the SWRL Temporal Ontology or SWRLTO) and two specific domain ontologies (the Urban Ontology or URO and the Geographic Data ontology or GeoD, developed by our team). They play different and well specific roles in the whole process of perception. The paper shows how to apply SSN to manage measurements of geographical regions provided by satellite images processing software. In a similar way, TAO has been extended to deal with the abstractions resulting from geographical data interpretation. An example shows a SWRL based implementation of a perception process that gradually abstracts geographical features and objects.

Many software systems rely on ontologies for semantic interoperation. However, ontologies which admit unintended models might cause misunderstandings that hinder interoperability because their vocabularies are ambiguously defined. Foundational ontologies, such as SUMO, provide rich characterizations for general concepts that underly every knowledge representation enterprise. Those ontologies are intended to be broadly reused as a reference for semantics. Ontology verification is the process by which a theory is checked to rule out unintended models by means of further axiomatization, and characterize missing intended ones. In this paper, we verify the subtheory of core temporal concepts of the SUMO foundational ontology and relate its axiomatization via ontology mapping with other time ontologies, the foundational ontology DOLCE, and the generic ontology PSL. As a result, we propose the addition of some missing axioms that we have identified during our verification task, and the correction of others.

This article presents a formalization of velocity in the context of a realist and perspectivalist upper ontology like BFO. It argues that the term “velocity” can refer to two different entities: a motion-velocity, which is a process profile characterizing a motion process; and an object-velocity, which is a disposition inhering in the moving object. Three different kinds of motion-velocity are presented: left-velocity, right-velocity and bilateral velocity. Motion-velocity could exist without object-velocity, as revealed by a thought experiment presented by Tooley; but in our world, Newton's first law of inertia implies that every object has both an inertial disposition and a closely related but different disposition that we call “object-velocity.” Those two dispositions are realized by the right-velocity. The left-velocity is a trigger of the inertial disposition, and brings into existence the object-velocity.

We argue that a cognitive semantics has to take into account the possibly partial information that a cognitive agent has of the world. After discussing Gärdenfors's view of objects in conceptual spaces, we offer a number of viable treatments of partiality of information and we formalize them by means of alternative predicative logics. Our analysis shows that understanding the nature of simple predicative sentences is crucial for a cognitive semantics.

So far, most of the work in Knowledge Representation has modelled concepts as classes, i.e., as sets of instances. However, as from the work in Teleosemantics, concepts can also be thought as abilities of performing certain (biological) functions. The shift is from the study of the means by which the world is represented to the study of the reasons and means by which such representations are generated. In this paper, which is grounded in the seminal contribution by the philosopher Ruth Millikan, we focus on substance concepts, namely on concepts as on recognition abilities, and on how this notion can be mapped to that of concepts as classes. The ultimate goal is to provide a unified theory of perception and knowledge representation that, eventually, will allow us to go beyond the limitations and lack of robustness of current Artificial Intelligence (AI) systems. We provide three main contributions: i) a model of concepts as abilities, with a focus on recognition abilities, ii) an early version of an Ontology of (Recognition) Abilities (called RAO) and iii) the beginning of a methodology for how to use RAO for discovering which classes, among those contained in the state of the art ontologies, correspond to recognition abilities.

Adjectives carry a lot of discourse semantics, often being the core elements to understand the literal, emotional, cultural, and metaphoric meaning of a sentence. Their formal semantics has been investigated specially in lexical semantics and formal linguistics, with some contributions from formal ontology and the semantic web. However, no standard formal treatment of adjectives is available yet, which is capable to address the concerns of both theoretical and computational natural language understanding. In this paper we summarize the existing approaches, present some alternative solutions to approximate a rigorous but pragmatic representation, and describe an implementation of a lightweight adjective ontology as a core resource in FRED, a state-of-the-art open knowledge extraction tool.

Events are a recurring topic in ontological modeling and the diversity of their encoding in the semantic web ontological language OWL is immense. We provide a lightweight comparative survey of approaches to event modeling in both foundational and semantic web ontologies, and build upon it a tentative system of four categories of what is commonly called ‘event’. A substantial part of the categorization has to do with the distinction between an object and an relationship, as conceived in the lightweight ontological background modeling language PURO.

We introduce a first-oder theory where observations are reified into the domain of quantification. Observations have an epistemological nature, they describe how the world appears, not as the world is. Our primitive notions allow to represent how some observations are explained in terms of more simple ones or how they are aggregated into macro-indexes. We analyze in detail the cases of measurement and testing where observations are collected through calibrated devices and eventually aggregated into scores. Our framework is based on a decoupling between the observations and the propositions that belong to the temporally qualified A-box. It allows contradictory observations, but it requires these disagreements to be resolved via a merging process that identifies, among the contradictory observations, the most plausible one that can then be safely transferred into the A-box.

Comprehension of justifications is known to be difficult for even experienced ontology engineers, and much more so for other stakeholders. In this paper, we present two methods for displaying justifications using concept diagrams: using multiple concept diagrams to represent the justification (one diagram for each axiom); and using a merged concept diagram to represent all axioms in the justification. We performed an empirical evaluation of both methods along with a textual representation of the justification using Protégé. The results were that novice users could both more accurately and more quickly identify an incoherence when using merged diagrams than using multiple diagrams or Protégé statements.