Fabian Neuhaus

Relations in biomedical ontologies

To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.

CARO – The Common Anatomy Reference Ontology

The Common Anatomy Reference Ontology (CARO) is being developed to facilitate interoperability between existing anatomy ontologies for different species, and will provide a template for building new anatomy ontologies. CARO has a structural axis of classification based on the top-level nodes of the Foundational Model of Anatomy. CARO will complement the developmental process sub-ontology of the GO Biological Process ontology, using the latter to ensure the coherent treatment of developmental stages, and to provide a common framework for the model organism communities to classify developmental structures. Definitions for the types and relationships are being generated by a consortium of investigators from diverse backgrounds to ensure applicability to all organisms. CARO will support the coordination of cross-species ontologies at all levels of anatomical granularity by crossreferencing types within the cell type ontology (CL) and the Gene Ontology (GO) Cellular Component ontology. A complete cross-species CARO could be utilized by other ontologies for cross-product generation.

Towards ontology evaluation across the life cycle: The Ontology Summit 2013

The goal of the Ontology Summit 2013 was to create guidance for ontology developers and users on how to evaluate ontologies. Over a period of four months a variety of approaches were discussed by participants, who represented a broad spectrum of ontology, software, and system developers and users. We explored how established best practices in systems engineering and in software engineering can be utilized in ontology development.

A strategy for building neuroanatomy ontologies

MOTIVATION Advancing our understanding of how nervous systems work will require the ability to store and annotate 3D anatomical datasets, recording morphology, partonomy and connectivity at multiple levels of granularity from subcellular to gross anatomy. It will also require the ability to integrate this data with other data-types including functional, genetic and electrophysiological data. The web ontology language OWL2 provides the means to solve many of these problems. Using it, one can rigorously define and relate classes of anatomical structure using multiple criteria. The resulting classes can be used to annotate datasets recording, for example, gene expression or electrophysiology. Reasoning software can be used to automate classification and error checking and to construct and answer sophisticated combinatorial queries. But for such queries to give consistent and biologically meaningful results, it is important that both classes and the terms (relations) used to relate them are carefully defined. RESULTS We formally define a set of relations for recording the spatial and connectivity relationships of neuron classes and brain regions in a broad range of species, from vertebrates to arthropods. We illustrate the utility of our approach via its application in the ontology that drives the Virtual Fly Brain web resource. AVAILABILITY AND IMPLEMENTATION The relations we define are available from http://purl.obolibrary.org/obo/ro.owl. They are used in the Drosophila anatomy ontology (http://purl.obolibrary.org/obo/fbbt/2011-09-06/), which drives the web resource http://www.virtualflybrain.org

Image schemas in computational conceptual blending

In cognitive science, image schemas are identified as fundamental patterns of cognition. They are schematic prelinguistic conceptualisations of events and serve as conceptual building blocks for concepts. This paper proposes that image schemas can play an important role in computational concept invention, namely within the computational realisation of conceptual blending. We propose to build a library of formalised image schemas, and illustrate how they can guide the search for a base space in the concept invention work flow. Their schematic nature is captured by the idea of organising image schemas into families. Formally, they are represented as heterogeneous, interlinked theories.

Choosing the Right Path: Image Schema Theory as a Foundation for Concept Invention

Abstract Image schemas are recognised as a fundamental ingredient in human cognition and creative thought. They have been studied extensively in areas such as cognitive linguistics. With the goal of exploring their potential role in computational creative systems, we here study the viability of the idea to formalise image schemas as a set of interlinked theories. We discuss in particular a selection of image schemas related to the notion of ‘path’, and show how they can be mapped to a formalised family of microtheories reflecting the different aspects of path following. Finally, we illustrate the potential of this approach in the area of concept invention, namely by providing several examples illustrating in detail in what way formalised image schema families support the computational modelling of conceptual blending.

Modelling Principles and Methodologies – Relations in Anatomical Ontologies

It is now increasingly accepted that many existing biological and medical ontologies can be improved by adopting tools and methods that bring a greater degree of logical and ontological rigor. In this chapter we will focus on the merits of a logically sound approach to ontologies from a methodological point of view. As we shall see, one crucial feature of a logically sound approach is that we have clear and functional definitions of the relational expressions such as ‘is_a’ and ‘part_of’. While this chapter is mainly concerned with the general issues of methodology, chapter 15, on ‘Spatial Representation and Reasoning’, will apply the methodology to the specific case of spatial relations. Although both chapters are self-contained, we recommend that they be seen as forming a unity.

Common Logic and the Horatio problem

Modules allow the reuse of an ontology as part of another ontology. If the ontologies do not share a common domain of discourse a simple ‘cut and paste’ approach to module reuse leads to unintended consequences, the Horatio problem. To solve this problem ISO/IEC 24707s Common Logic includes modules as a syntactic category. However, the semantics of modules is treated incongruently in ISO/IEC 24707. In this paper we propose an alternative semantics of modules, discuss their logical properties, and how they can be used in ontology development.

Modeling Principles and Methodologies - Spatial Representation and Reasoning

Spatial relations include mereological relations such as parthood and overlap, topological relations such as connectedness and one-pieceness, as well as location relations. The location and the arrangement of an anatomical structure within the human body can be further specified by means of relations that express spatial orderings in a qualitative way, e.g. superior, anterior, lateral, etc. In this chapter we give an overview of the various kinds of spatial relations and their properties. We particularly focus on properties of spatial relations that can be exploited for automated reasoning. We also discuss the distinction between so-called individual-level and type-level spatial relations.

Creating the ontologists of the future

The goal of the Ontology Summit 2010 was to address the current shortage of persons with ontology expertise by developing a strategy for the education of ontologists. To achieve this goal we studied how ontologists are currently trained, the requirements identified by organizations that hire ontologists, and developments that might impact the training of ontologists in the future. We developed recommendations for the body of knowledge that should be taught and the skills that should be developed by future ontologists; these recommendations are intended as guidelines for institutions and organizations that may consider establishing a program for training ontologists. Further, we recommend a number of specific actions for the community to pursue.