Content-specific auditing of a large scale anatomy ontology

Biomedical ontologies are envisioned to be usable in a range of research and clinical applications. The requirements for such uses include formal consistency, adequacy of coverage, and possibly other domain specific constraints. In this report we describe a case study that illustrates how application specific requirements may be used to identify modeling problems as well as data entry errors in ontology building and evolution. We have begun a project to use the UW Foundational Model of Anatomy (FMA) in a clinical application in radiation therapy planning. This application focuses mainly (but not exclusively) on the representation of the lymphatic system in the FMA, in order to predict the spread of tumor cells to regional metastatic sites. This application requires that the downstream relations associated with lymphatic system components must only be to other lymphatic chains or vessels, must be at the appropriate level of granularity, and that every path through the lymphatic system must terminate at one of the two well known trunks of the lymphatic system. It is possible through a programmable query interface to the FMA to write small programs that systematically audit the FMA for compliance with these constraints. We report on the design of some of these programs, and the results we obtained by applying them to the lymphatic system. The algorithms and approach are generalizable to other network organ systems in the FMA such as arteries and veins. In addition to illustrating exact constraint checking methods, this work illustrates how the details of an application may reflect back a requirement to revise the design of the ontology itself

New VISTAs in Science Education

In the summer of 2012, a colleague and I attended the four-week Virginia Initiative for Science Teaching and Achievement (VISTA) Elementary Summer Science Institute where we were trained to conduct inquiry-based science teaching in a problem-based learning setting. We then implemented our training in our own academic classrooms by developing a Problem-Based Learning unit meeting the objectives of our Virginia standards-based science curriculum and selecting a topic with tics to our local community. Toward demonstrating that students, teachers, and educational systems stand to benefit from the implementation of this methodology, this article clarifies the following aspects: 1) outlines the problem, scenario, and process of developing a Problem-Based Leaming unit; 2) explains the delivery in the classroom; 3) analyzes ongoing formative and summative assessments; 4) and, discusses the influence on students, teachers, and instruction as a whole

Ecient Inference-aware RDB2RDF Query Rewriting

RDB2RDF systems generate RDF from relational databases, operating in two dierent manners: materializing the database content into RDF or acting as virtual RDF datastores that transform SPARQL queries into SQL. In the former, inferences on the RDF data (taking into account the ontologies that they are related to) are normally done by the RDF triple store where the RDF data is materialised and hence the results of the query answering process depend on the store. In the latter, existing RDB2RDF systems do not normally perform such inferences at query time. This paper shows how the algorithm used in the REQUIEM system, focused on handling run-time inferences for query answering, can be adapted to handle such inferences for query answering in combination with RDB2RDF systems

The RR Project – a framework for relationship network viewing and management

The Relationship Networks Project (RR - Redes de Relacionamento) is an innovative project, which intends to create a framework, which allows - through a fast data modeling - implementing interface elements that describe in a clearly visual way, in two-dimensional presentation, a relationship network among heterogeneous items. This environment also allows the machine to do operations over these relations, such as to find paths or sets, to help the implementation of AI algorithms, or data extraction by the final user. Through graph theory, with visual items, it is possible to find elements with specific characteristics and relationships between them, by the application of filters, refining searches inside an extreme large datasets, or showing differentiated connection maps. Two prototypes were created with this framework: A system which allows seeing telephonic calls sets and financial transactions, and a system for ontology viewing for a digital dictionary inside a semantic network. Another software, in prototypical phase, also for semantic network vision, is being constructed. This document will present the basic RR structure, showing and justifying the creation of the two referred software above.Applications in Artificial Intelligence - Ontologies and Intelligent WebRed de Universidades con Carreras en Informática (RedUNCI

The Politics of Scale, Position, and Place in the Governance of Water Resources in the Mekong Region

The appropriate scales for science, management, and decision making cannot be unambiguously derived from physical characteristics of water resources. Scales are a joint product of social and biophysical processes. The politics-of-scale metaphor has been helpful in drawing attention to the ways in which scale choices are constrained overtly by politics, and more subtly by choices of technologies, institutional designs, and measurements. In doing so, however, the scale metaphor has been stretched to cover a lot of different spatial relationships. In this paper, we argue that there are benefits to understanding—and actions to distinguish—issues of scale from those of place and position. We illustrate our arguments with examples from the governance of water resources in the Mekong region, where key scientific information is often limited to a few sources. Acknowledging how actors’ interests fit along various spatial, temporal, jurisdictional, and other social scales helps make the case for innovative and more inclusive means for bringing multi-level interests to a common forum. Deliberation can provide a check on the extent of shared understanding and key uncertainties

Policy Is What We Make of It : an Interpretive Study of Governance in an Urban Watershed

This study explores the governance of an urban watershed using a combination of interpretive approach and resilience framework. The key idea within resilience and social ecological systems (SESs) discourse is to link \u27human systems\u27 (e.g. communities, society, economy) with \u27natural systems\u27 (e.g. ecosystems, biophysical elements) and to understand the interconnections and feedbacks between these systems. Under resilience thinking SESs (e.g. urban environmental) are viewed as complex adaptive systems, therefore, adaptive governance is key for maintaining long-term sustainability of these systems. With this study, I examine the case of the Cuyahoga River in Northeast Ohio, an urban watershed with legacy pollution and water quality issues, which in the recent times has also been recognized as an icon in water management. To do so, I conducted an interpretive analysis using a combination of political ethnography, interpretive phenomenological analysis (IPA), and social network mapping. Specifically, I conduct a characterization and analysis of an urban watershed, bringing the resilience and SES frameworks to the study of urban SESs. I also develop a conceptual framework for analyzing urban watersheds based on SES dynamics and resilience attributes that are critical for building adaptive capacity, explicitly focusing on governance and management influences. Further, I explore what the networked approach to watershed governance in the Cuyahoga River watershed mean to the governance actors in terms of building long-term adaptive capacity. I suggest that using approach and through continued dialogue and discourse, governance actors create and bind policy meanings that overtime transforms governance. I suggest that the lessons drawn from this study will provide insights for watershed managers, public agencies, and non-governmental organizations to enhance their long-term capacity-building mechanisms and processes that support watershed planning, policy development, implementation and decision-making

Expert Systems for Environmental Screening. An Application in the Lower Mekong Basin

This research report describes MEXSES, a rule-based expert system for environmental impact assessment at a screening level, implemented for the analysis of water resources development projects in the Lower Mekong Basin. The report makes a brief review of environmental impact assessment methods and tools. It discusses expert systems technology, with emphasis on environmental applications. The Lower Mekong Basin and its specific environmental problems, as well as the Mekong Secretariat's environmental policy are examined. Subsequently, the software system is described from a user's perspective, followed by a detailed description of the methodology employed and its implementation. In the final chapter, a number of issues around the successful application of such a system are discussed, including a number of suggested improvements and extensions to the current operational prototype

An Interactive Multi-Criteria Decision Model for Reservoir Management: The Shellmouth Reservoir Case

Reservoir management is inherently multi-criterial, since any release decision involves implicit trade-offs between various conflicting objectives. The release decision reflects concerns such as flood protection, hydroelectric power generation, dilution of downstream wastewater and heat effluents, downstream municipal, agricultural and industrial water supply, environmental standards and recreational needs. This paper presents a framework for analysing trade-offs between several decision criteria, and includes the management of heated effluents from downstream thermoelectric power generation in an optimisation model for reservoir management. The model is formulated and analysed in an interactive multi-criteria decision making (MCDM) modelling framework. Rather than providing specific target levels or ad hoc constants in a Goal Programming framework, as proposed elsewhere, our multi-criteria framework suggests a systematic way of evaluating trade-offs by progressive preference assessment. The MCDM model, based on a Tchebycheff metric and a contracted cone approach, is learning-oriented and permits a natural exploration of the decision space while maintaining non-dominated decisions. A detailed case study of the Shellmouth Reservoir in Manitoba, Canada, serves as an illustration of the model