The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open (...) Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers. (shrink)

The Plant Ontology (PO) is a community resource consisting of standardized terms, definitions, and logical relations describing plant structures and development stages, augmented by a large database of annotations from genomic and phenomic studies. This paper describes the structure of the ontology and the design principles we used in constructing PO terms for plant development stages. It also provides details of the methodology and rationale behind our revision and expansion of the PO to cover development stages for all plants, particularly (...) the land plants (bryophytes through angiosperms). As a case study to illustrate the general approach, we examine variation in gene expression across embryo development stages in Arabidopsis and maize, demonstrating how the PO can be used to compare patterns of expression across stages and in developmentally different species. Although many genes appear to be active throughout embryo development, we identified a small set of uniquely expressed genes for each stage of embryo development and also between the two species. Evaluating the different sets of genes expressed during embryo development in Arabidopsis or maize may inform future studies of the divergent developmental pathways observed in monocotyledonous versus dicotyledonous species. The PO and its annotation databasemake plant data for any species more discoverable and accessible through common formats, thus providing support for applications in plant pathology, image analysis, and comparative development and evolution. (shrink)

Bio-ontologies are essential tools for accessing and analyzing the rapidly growing pool of plant genomic and phenomic data. Ontologies provide structured vocabularies to support consistent aggregation of data and a semantic framework for automated analyses and reasoning. They are a key component of the Semantic Web. This paper provides background on what bio-ontologies are, why they are relevant to botany, and the principles of ontology development. It includes an overview of ontologies and related resources that are relevant to plant science, (...) with a detailed description of the Plant Ontology (PO). We discuss the challenges of building an ontology that covers all green plants (Viridiplantae). Key results: Ontologies can advance plant science in four keys areas: 1. comparative genetics, genomics, phenomics, and development, 2. taxonomy and systematics, 3. semantic applications and 4. education. Conclusions: Bio-ontologies offer a flexible framework for comparative plant biology, based on common botanical understanding. As genomic and phenomic data become available for more species, we anticipate that the annotation of data with ontology terms will become less centralized, while at the same time, the need for cross-species queries will become more common, causing more researchers in plant science to turn to ontologies. (shrink)

The Plant Ontology (PO) (http://www.plantontology.org) (Jaiswal et al., 2005; Avraham et al., 2008) was designed to facilitate cross-database querying and to foster consistent use of plant-specific terminology in annotation. As new data are generated from the ever-expanding list of plant genome projects, the need for a consistent, cross-taxon vocabulary has grown. To meet this need, the PO is being expanded to represent all plants. This is the first ontology designed to encompass anatomical structures as well as growth and developmental stages (...) across such a broad taxonomic range. While other ontologies such as the Gene Ontology (GO) (The Gene Ontology Consortium, 2010) or Cell Type Ontology (CL) (Bard et al., 2005) cover all living organisms, they are confined to structures at the cellular level and below. The diversity of growth forms and life histories within plants presents a challenge, but also provides unique opportunities to study developmental and evolutionary homology across organisms. (shrink)

Plants from a handful of species provide the primary source of food for all people, yet this source is vulnerable to multiple stressors, such as disease, drought, and nutrient deficiency. With rapid population growth and climate uncertainty, the need to produce crops that can tolerate or resist plant stressors is more crucial than ever. Traditional plant breeding methods may not be sufficient to overcome this challenge, and methods such as highOthroughput sequencing and automated scoring of phenotypes can provide significant new (...) insights. Ontologies are essential tools for accessing and analysing the large quantities of data that come with these newer methods. As part of a larger project to develop ontologies that describe plant phenotypes and stresses, we are developing a plant disease extension of the Infectious Disease Ontology (IDOPlant). The IDOPlant is envisioned as a reference ontology designed to cover any plant infectious disease. In addition to novel terms for infectious diseases, IDOPlant includes terms imported from other ontologies that describe plants, pathogens, and vectors, the geographic location and ecology of diseases and hosts, and molecular functions and interactions of hosts and pathogens. To encompass this range of data, we are suggesting inOhouse ontology development complemented with reuse of terms from orthogonal ontologies developed as part of the Open Biomedical Ontologies (OBO) Foundry. The study of plant diseases provides an example of how an ontological framework can be used to model complex biological phenomena such as plant disease, and how plant infectious diseases differ from, and are similar to, infectious diseases in other organism. (shrink)

The Plant Ontology (PO; http://www.plantontology.org/) is a publicly-available, collaborative effort to develop and maintain a controlled, structured vocabulary (“ontology”) of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded (...) to include all green plants. The PO was the first multi-species anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontologies that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. There are about 2.2 million annotations linking PO terms to over 110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and Quantitative Traits Loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users, and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs. (shrink)

Conference paper delivered at the Maison de la recherche in October 2016, at an international colloquium scheduled to mark Lev Shestov's 150th anniversary. The article provides a comparative analysis of Shestov's and Pascal's conceptions of the relationship between faith and reason.

This article addresses the general ethical issues of accessing online personal data for research purposes. The authors discuss the practical aspects of online research with a specific case study that illustrates the ethical challenges encountered when accessing data from Kooth, an online youth web-counselling service. This paper firstly highlights the relevance of a process-based approach to ethics when accessing highly sensitive data and then discusses the ethical considerations and potential challenges regarding the accessing of public data from Digital Mental Health (...) services. It presents solutions that aim to protect young DMH service users as well as the DMH providers and researchers mining such data. Special consideration is given to service users’ expectations of what their data might be used for, as well as their perceptions of whether the data they post is public, private or open. We provide recommendations for planning and designing online research in an ethical manner that includes vulnerable young people as research participants. We emphasise the distinction between public, private and open data, which is crucial to comprehend the ethical challenges in accessing DMH data. Among our key recommendations, we foreground the need to consider a collaborative approach with the DMH providers while respecting service users’ control over personal data, and we propose the implementation of digital solutions embedded within the platform for explicit opt-out/opt-in recruitment strategies and ‘read more’ options. (shrink)

Biological ontologies are used to organize, curate, and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies Foundry was created to address this by facilitating the development, harmonization, application, and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the (...) OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data FAIR. Competing Interest StatementThe authors have declared no competing interest. (shrink)

Currently, there are many advocacy interventions aimed at reducing animal consumption. We report results from a lab (N = 267) and a field experiment (N = 208) exploring whether, and to what extent, some of those educational interventions are effective at shifting attitudes and behavior related to animal consumption. In the lab experiment, participants were randomly assigned to read a philosophical ethics paper, watch an animal advocacy video, read an advocacy pamphlet, or watch a control video. In the field experiment, (...) we measured the impact of college classes with animal ethics content versus college classes without animal ethics content. Using a pretest, post-test matched control group design, humane educational interventions generally made people more knowledgeable about animals used as food and reduced justifications and speciesist attitudes supporting animal consumption. None of the interventions in either experiment had a direct, measurable impact on self-reported animal consumption. These results suggest that while some educational interventions can change beliefs and attitudes about animal consumption, those same interventions have small impacts on animal consumption. (shrink)

Knowledge of human uses of animals is an important, but understudied, aspect of how humans treat animals. We developed a measure of one kind of knowledge of human uses of animals – knowledge of factory farming. Studies 1 (N = 270) and 2 (N = 270) tested an initial battery of objective, true or false statements about factory farming using Item Response Theory. Studies 3 (N = 241) and 4 (N = 278) provided evidence that responses to a 10-item Knowledge (...) of Factory Farming Scale predicted a reduction in consumption of animal products (rs = −.17- −.27) and approval of political actions aimed at factory farming (rs = .2 – .24). Path models from Studies 3 and 4 suggested that different kinds of knowledge uniquely predicted different outcomes. The Knowledge of Factory Farming scale was a unique predictor of approval of political actions concerning factory farmed animals but not animal consumption. Knowledge of Animals Used as Food predicted animal consumption but not political actions concerning farmed animals. These results highlight that different kinds of knowledge can be relevant for different animal related outcomes. (shrink)

Tato studie se snaží o filosofickou analýzu problematických aspektů neurogeneze. V první řadě se zaměřuje na moderní historii neurogeneze, která je obecně považována za historii dogmatického přesvědčení, které předpokládalo, že v mozku dospělého savce nemohou vzniknout nové neurony. Tato konvence přežívala v neurovědě po několik desítek let a její kořeny sahají až do dob Ramóna y Cajala. Důležitá část této filosofické analýzy se zaměřuje na aspekt tzv. zaštiťování dogmatu pomocí ad hoc hypotéz. Analýza se dále věnuje implicitním definicím, které hrají (...) roli axiomů neurovědy, a problematice falsifikace potenciálních falsifikátorů. Na konci této filosofické analýzy jsou prezentovány argumenty, které dospívají k tomu, že historie neurogeneze není historií dogmatického uvažování, jak většina autorů předpokládá, ale že jde o historii vědeckého pragmatismu. (shrink)