Knowledge integration in One Health policy formulation, implementation and evaluation

The One Health concept covers the interrelationship between human, animal and environmental health and requires multistakeholder collaboration across many cultural, disciplinary, institutional and sectoral boundaries. Yet, the implementation of the One Health approach appears hampered by shortcomings in the global framework for health governance. Knowledge integration approaches, at all stages of policy development, could help to address these shortcomings. The identification of key objectives, the resolving of trade-offs and the creation of a common vision and a common direction can be supported by multicriteria analyses. Evidence-based decision-making and transformation of observations into narratives detailing how situations emerge and might unfold in the future can be achieved by systems thinking. Finally, transdisciplinary approaches can be used both to improve the effectiveness of existing systems and to develop novel networks for collective action. To strengthen One Health governance, we propose that knowledge integration becomes a key feature of all stages in the development of related policies. We suggest several ways in which such integration could be promoted

Distributed Holistic Clustering on Linked Data

Link discovery is an active field of research to support data integration in the Web of Data. Due to the huge size and number of available data sources, efficient and effective link discovery is a very challenging task. Common pairwise link discovery approaches do not scale to many sources with very large entity sets. We here propose a distributed holistic approach to link many data sources based on a clustering of entities that represent the same real-world object. Our clustering approach provides a compact and fused representation of entities, and can identify errors in existing links as well as many new links. We support a distributed execution of the clustering approach to achieve faster execution times and scalability for large real-world data sets. We provide a novel gold standard for multi-source clustering, and evaluate our methods with respect to effectiveness and efficiency for large data sets from the geographic and music domains

Ontology-based domain modelling for consistent content change management

Ontology-based modelling of multi-formatted software application content is a challenging area in content management. When the number of software content unit is huge and in continuous process of change, content change management is important. The management of content in this context requires targeted access and manipulation methods. We present a novel approach to deal with model-driven content-centric information systems and access to their content. At the core of our approach is an ontology-based semantic annotation technique for diversely formatted content that can improve the accuracy of access and systems evolution. Domain ontologies represent domain-specific concepts and conform to metamodels. Different ontologies - from application domain ontologies to software ontologies - capture and model the different properties and perspectives on a software content unit. Interdependencies between domain ontologies, the artifacts and the content are captured through a trace model. The annotation traces are formalised and a graph-based system is selected for the representation of the annotation traces

Linking factual and procedural knowledge in solving science problems: A case study in a thermodynamics course

Well-specified problems of the type presented boxed in the introduction to this article are extremely common in science courses. Unfortunately, this does not mean that students find them easy to solve, even when a teacher provides model answers to problems which differ only marginally (in the teacher's eyes) from those put before the students. The central difficulty with such courses is that they do not embody instructional principles that reflect students' need for “direction” in problem solving. In this article, we describe how the necessary heuristics and strategic knowledge were built into the remake of a conventional thermodynamics course. In contrast to mainstream American work on learning problem solving we chose to direct our curriculum reconstruction using the Gal'perin theory of stage-by-stage formation of mental actions and Landa's description of the “through” systematization of knowledge. As indicated by both, we first developed an integrated system of instructional objectives: a programme of actions and methods (PAM) to solve problems in thermodynamics. Then the plan of instruction was designed. This plan indicates which instructional procedures and materials should be used to realize the instructional functions, derived from the learning theory. The evaluation design contained two control and three experimental courses. In discussing our main findings, we consider the generalizability of the procedures we followed in constructing the PAM and the instructional plan

Using agriculture for development: Supply- and demand-side approaches

For most poor countries of today, using agriculture for development is widely recognized as a promising strategy. Yet, in these countries, investment in agriculture has mostly been lagging relative to international norms and recommendations. Current wisdom on how to use agriculture for development is that it requires asset building for smallholder farmers, productivity growth in staple foods, an agricultural transformation (diversification of farming systems toward high value crops), and a rural transformation (value addition through rural non-farm activities linked to agriculture). This sequence has too often been hampered by extensive market and government failures. We outline a theory of change where the removal of market and government failures to use this Agriculture for Development strategy can be addressed through two contrasted and complementary approaches. One is from the “supply-side” where public and social agents (governments, international and bilateral development agencies, NGOs, donors) intervene to help farmers overcome the major constraints to adoption: liquidity, risk, information, and access to markets. The other is from the “demand-side” where private agents (entrepreneurs, producer organizations) create incentives for smallholder farmers to modernize through contracting and vertical coordination in value chains. We review the extensive literature that has explored ways of using Agriculture for Development through these two approaches. We conclude by noting that the supply-side approach has benefited from extensive research but met with limited success. The demand-side approach has promise, but received insufficient attention and is in need of additional rigorous research which we outline

Measuring Shared Value: How to Unlock Value by Linking Social and Business Results

Measuring shared value allows companies to maximize opportunities for innovation, growth, and social impact at scale. This article explains the specific purpose of shared value measurement and offers a step-by-step process and pragmatic approaches to measurement with examples from leading companies