Suchergebnisse

Modern toxicology is evolving to leverage data science methodologies to better address complex public health and environmental concerns. Understanding the potential adverse impacts of environmental exposures requires working across a variety of domains and data types that are often siloed and require manual curation and extraction. Ontologies and semantic engineering can facilitate meaningful data integration, but existing semantic standards have not been widely used in toxicology. Development of semantic standards for toxicology requires sustained interdisciplinary collaborations. One place where the community came together to discuss this need is the "Computable Exposures" workshop, held at Oregon State University in September 2019. Ontologists, toxicologists, epidemiologists, exposure scientists, ecotoxicologists, clinicians, computer scientists, computational biologists, and data scientists from academia, government, and industry were in attendance. Here we describe community-building efforts, standards development, and plans for future work. Objectives include building a semantic exposure data model using the Environmental Conditions, Treatments, and Exposures Ontology (ECTO), developing toxicology-driven use cases and competency questions, creating a mailing list, and planning a larger computable exposures conference. Twelve use cases were developed during the workshop, for example, using semantic technology to complete Adverse Outcomes Pathway (AOP) and Aggregate Exposure Pathway (AEP) given the initiating and terminal key events. Broader adoption of ontologies, together with increased data sharing, has the potential to improve a toxicologist's ability to integrate, navigate, and analyze vast amounts of heterogeneous data—allowing for more rapid safety assessment of chemical and environmental exposures, and increased understanding of underlying biological mechanisms across species.

Given the growing centrality of interdisciplinarity to scientific research, gaining a better understanding of successful interdisciplinary collaborations has become imperative. Drawing on extensive case studies of nine research networks in the social, natural, and computational sciences, we propose a construct that captures the multidimensional character of such collaborations, that of a shared cognitive–emotional–interactional (SCEI) platform. We demonstrate its value as an integrative lens to examine markers of and conditions for successful interdisciplinary collaborations as defined by researchers involved in these groups. We show that (1) markers and conditions embody three different dimensions: cognitive, emotional, and interactional; (2) these dimensions are present in all networks, albeit to different degrees; (3) the dimensions are intertwined and mutually constitutive; and (4) they operate in conjunction with institutional conditions created by funders. We compare the SCEI platforms to available frameworks for successful interdisciplinary work.

Equitable interdisciplinary teamwork is easier said than done. For, it is not simply a matter of adding a "pinch" of social science into a larger interdisciplinary team, and stirring. Putting interdisciplinarity into action requires a more distilled and nuanced approach involving negotiation, bargaining and, sometimes, contestation and resistance between and among different domains of disciplinary actors, knowledge, meanings and understanding. The overarching goal for anthropologists and sociocultural scientists is to integrate theories, methodologies, and practices of the study of culture, politics, and social relations into agricultural and natural resource management research, as well as to integrate themselves into larger interdisciplinary teams on an equal footing. As McDonald argues in his call for a discussion on keeping the culture in agriculture, "by putting culture squarely at the center of any analysis of agriculture, we seek to "put people first" by exploring the complex ways that people conceptualize, give meaning to, and organize around agriculture" (McDonald 2005, p. 71). However, putting culture into the analysis of agriculture in research systems long dominated by biophysical scientists and approaches, such as within research centers of the Consultative Group for International Agricultural Research (CGIAR), is challenging. This chapter describes the various dilemmas, challenges, and opportunities encountered by sociocultural scientists in interdisciplinary projects within the CGIAR. It argues that to more effectively address the needs and realities of vulnerable women and men at the grassroots, agricultural research systems must take more steps to fully integrate social, cultural, and political lines of inquiry into their core mandates.

This article deals with interdisciplinary collaboration and conflicts concerning children in difficulties in school. By applying a practice approach to the multifarious, conflictual everyday life of interdisciplinary work, the article discusses and problematizes the dominant trope that quality assurance is best achieved through formal guidelines, strict organisation plans and clear legislation. This article suggests that we need to develop a conceptual framework that appreciates the situated, transformative, collaborative procedures through which interventions for children in difficulties are developed in practice; processes that are often overlooked in the endeavour, driven by a "longing for order", of producing standardized models. In the article, such transformative processes are described in terms of "corridor casework" and "politics of everyday life".

Sharing research data is not a new idea; the success of the Inter-University Consortium for Political and Social Science Research (ICPSR) data archive provides evidence of data sharing's utility in the social sciences, while recent articles (Piwowar, Becich, Bilofsky & Crowley, 2008; Piwowar, Day, & Fridsma, 2007) in the biomedical literature have reiterated the importance of data sharing to the advancement of science and knowledge. The American Psychological Association's Ethical Principles of Psychologists and Code of Conduct (APA, 2002)affirms the importance of making research data available – to the extent possible within legal and ethical boundaries – for the purposes of reanalysis by other professionals. The availability of data sets from researchers around the world in online repositories such as ICPSR and PsychData (www.zpid.de) encourages collaborative work across institutions and national boundaries. However, such large scale efforts to share data are not ideal for serving more local aims: the encouragement of intra-and interdisciplinary collaborative research withina single institution. To meet that need, this project focuses on the creation of a searchable database of existing faculty research data sets that can be accessed internally (within Pacific University) for the purposes of developing new uses of data for theses, dissertations and scholarly publications.

This article utilized survey research to examine where interdisciplinary collaboration is occurring and being taught in social work programs in three countries. Findings indicate that social work programs participate in high levels of interdisciplinary collaboration at the university—community level and the interdepartmental level and teach it through an array of courses.

Integrated human-Earth system models could be a useful tool for interdisciplinary collaboration on sustainability issues. However, it is challenging to integrate all disciplines equally. Considering modeling frameworks as boundary objects could help. In this perspective, a modeling
framework, while clearly defined in its basic function, could be adapted and reinterpreted by researchers from different disciplines according to their specific contexts and questions, yet the framework still remains a common reference point behind these different adaptations. This flexibility
and plasticity could contribute to the evolution of the modeling framework itself. The authors discuss how this might look, using the copan:CORE framework as an example.