The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to (...) existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource providing details on the people, policies, and issues being addressed in association with OBI. (shrink)
A number of researchers have begun to demonstrate that the widely discussed ?Knobe effect? (wherein participants are more likely to think that actions with bad side-effects are brought about intentionally than actions with good or neutral side-effects) can be found in theory of mind judgments that do not involve the concept of intentional action. In this article we report experimental results that show that attributions of knowledge can be influenced by the kinds of (non-epistemic) concerns that drive the Knobe effect. (...) Our findings suggest there is good reason to think that the epistemic version of the Knobe effect is a theoretically significant and robust effect, and that the goodness or badness of side-effects can often have greater influence on participant knowledge attributions than explicit information about objective probabilities. Thus, our work sheds light on important ways in which participant assessments of actions can affect the epistemic assessments participants make of agents? beliefs. (shrink)
Mental and behavioral disorders represent a significant portion of the public health burden in all countries. The human cost of these disorders is immense, yet treatment options for sufferers are currently limited, with many patients failing to respond sufficiently to available interventions and drugs. High quality ontologies facilitate data aggregation and comparison across different disciplines, and may therefore speed up the translation of primary research into novel therapeutics. Realism-based ontologies describe entities in reality and the relationships between them in such (...) a way that – once formulated in a suitable formal language – the ontologies can be used for sophisticated automated reasoning applications. Reference ontologies can be applied across different contexts in which different, and often mutually incompatible, domain-specific vocabularies have traditionally been used. In this contribution we describe the Mental Functioning Ontology (MF) and Mental Disease Ontology (MD), two realism-based ontologies currently under development for the description of humanmental functioning and disease. We describe the structure and upper levels of the ontologies and preliminary application scenarios, and identify some open questions. (shrink)
We are developing the Neurological Disease Ontology (ND) to provide a framework to enable representation of aspects of neurological diseases that are relevant to their treatment and study. ND is a representational tool that addresses the need for unambiguous annotation, storage, and retrieval of data associated with the treatment and study of neurological diseases. ND is being developed in compliance with the Open Biomedical Ontology Foundry principles and builds upon the paradigm established by the Ontology for General Medical Science (OGMS) (...) for the representation of entities in the domain of disease and medical practice. Initial applications of ND will include the annotation and analysis of large data sets and patient records for Alzheimer’s disease, multiple sclerosis, and stroke. (shrink)
We have begun work on two separate but related ontologies for the study of neurological diseases. The first, the Neurological Disease Ontology (ND), is intended to provide a set of controlled, logically connected classes to describe the range of neurological diseases and their associated signs and symptoms, assessments, diagnoses, and interventions that are encountered in the course of clinical practice. ND is built as an extension of the Ontology for General Medical Sciences — a high-level candidate OBO Foundry ontology that (...) provides a set of general classes that can be used to describe general aspects of medical science. ND is being built with classes utilizing both textual and axiomatized definitions that describe and formalize the relations between instances of other classes within the ontology itself as well as to external ontologies such as the Gene Ontology, Cell Ontology, Protein Ontology, and Chemical Entities of Biological Interest. In addition, references to similar or associated terms in external ontologies, vocabularies and terminologies are included when possible. Initial work on ND is focused on the areas of Alzheimer’s and other diseases associated with dementia, multiple sclerosis, and stroke and cerebrovascular disease. Extensions to additional groups of neurological diseases are planned. The second ontology, the Neuro-Psychological Testing Ontology (NPT), is intended to provide a set of classes for the annotation of neuropsychological testing data. The intention of this ontology is to allow for the integration of results from a variety of neuropsychological tests that assay similar measures of cognitive functioning. Neuro-psychological testing is an important component in developing the clinical picture used in the diagnosis of patients with a range of neurological diseases, such as Alzheimer’s disease and multiple sclerosis, and following stroke or traumatic brain injury. NPT is being developed as an extension to the Ontology for Biomedical Investigations. (shrink)
We discuss recent progress in the development of cognitive ontologies and summarize three challenges in the coordinated development and application of these resources. Challenge 1 is to adopt a standardized definition for cognitive processes. We describe three possibilities and recommend one that is consistent with the standard view in cognitive and biomedical sciences. Challenge 2 is harmonization. Gaps and conflicts in representation must be resolved so that these resources can be combined for mark-up and interpretation of multi-modal data. Finally, Challenge (...) 3 is to test the utility of these resources for large-scale annotation of data, search and query, and knowledge discovery and integration. As term definitions are tested and revised, harmonization should enable coordinated updates across ontologies. However, the true test of these definitions will be in their community-wide adoption which will test whether they support valid inferences about psychological and neuroscientific data. (shrink)
The Neurological Disease Ontology (ND) is being developed to provide a comprehensive framework for the representation of neurological diseases (Diehl et al., 2013). ND utilizes the model established by the Ontology for General Medical Science (OGMS) for the representation of entities in medicine and disease (Scheuermann et al., 2009). The goal of ND is to include information for each disease concerning its molecular, genetic, and environmental origins, the processes involved in its etiology and realization, as well as its clinical presentation (...) including signs and symptoms. (shrink)
Integrating and building on the constitutional ethics paradigm proposed by Paul Roush and the neo-intuitionist moral decision-making scheme proposed by Robert Audi, I defend a novel decisionmaking procedure for hard moral choices in the military. The key to Roush’s model of justifiable disobedience is a soldier’s ability to recognize when an ostensibly legal order constitutes a ‘fundamental violation of justice’. However, the nature and structure of this act of moral recognition requires more elucidation than Roush has provided. In order to (...) avoid grounding moral recognition and decision-making on a narrowly partisan account of moral theory, I appeal to Audi’s neo-intuitionist account of prima facie moral duties. I then repurpose and develop further a decision procedure that Audi proposed for the business context. When faced with an ethical dilemma in military service, a soldier should classify his/her obligations; identify the conflicts between his/her obligations; assess the weightiness of his/ her obligations; determine ethically viable options; and then make a decision. I close the discussion with an examination of the practical problems one might face in adopting the proposal. (shrink)
We discuss recent progress in the development of cognitive ontologies and summarize three challenges in the coordinated development and application of these resources. Challenge 1 is to adopt a standardized definition for cognitive processes. We describe three possibilities and recommend one that is consistent with the standard view in cognitive and biomedical sciences. Challenge 2 is harmonization. Gaps and conflicts in representation must be resolved so that these resources can be combined for mark-up and interpretation of multi-modal data. Finally, Challenge (...) 3 is to test the utility of these resources for large-scale annotation of data, search and query, and knowledge discovery and integration. As term definitions are tested and revised, harmonization should enable coordinated updates across ontologies. However, the true test of these definitions will be in their community-wide adoption which will test whether they support valid inferences about psychological and neuroscientific data. (shrink)
Following the recent decisions by Western militaries to pursue greater integration of women into combat roles, this paper examines the principles that motivate integration and organizes them into a theoretically coherent scheme that could serve as a roadmap for policymakers as they rebuild military institutions and their combat units in an integrated fashion. The strategy of the paper is Rawlsian: the right relationship between the principles that motivate integration can be derived through an application of Rawls's methodology as described in (...) A Theory of Justice. The result is a lexically ordered set of principles that begin with gender-blind equal opportunity but permit adjustments that take gender into account when these adjustments serve the interests of military institutions. The paper concludes with a discussion of two concerns, one practical and one theoretical, that one might have about the account. (shrink)
In this contribution to contemporary political philosophy, Jensen aims to develop a model of civil society for deliberative democracy. In the course of developing the model, he also provides a thorough account of the meaning and use of "civil society" in contemporary scholarship as well as a critical review of rival models, including those found in the work of scholars such as John Rawls, Jurgen Habermas, Michael Walzer, Benjamin Barber, and Nancy Rosenblum. Jensen's own ideal treats civil society as both (...) the context in which citizens live out their comprehensive views of the good life as well as the context in which citizens learn to be good deliberative democrats. According to his idealization, groups of citizens in civil society are actively engaged in a grand conversation about the nature of the good life. Their commitment to this conversation grounds dispositions of epistemic humility, tolerance, curiosity, and moderation. Moreover, their regard for the grand conversation explains their interest in deliberative democracy and their regard for democratic virtues, principles, and practices. Jensen is not a naive utopian, however; he argues that this ideal must be realized in stages, that it faces a variety of barriers, and that it cannot be realized without luck. (shrink)