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This paper builds upon studies employing a syllabi‐based methodology that suggest a tendency for critical geographic information science (GIS) courses to emphasize reading/discussion about GIS without actually doing GIS, and for traditional GIS instruction courses to emphasize the technical capacities of GIS software without incorporating critical theory in substantive ways. However, through ethnographic evidence we reveal that there is likely more innovative theory‐practice transcending pedagogies being utilized than would necessarily show up in such a syllabi‐based methodology. There are also very real and differentially manifest pragmatic, departmental, and institutional barriers in place to effectively incorporating critical social theory into courses that actually do GIS. We first catalogue these barriers as a means of ascertaining what can (and cannot) be done to overcome them through GIS pedagogic innovation. We then outline the (often‐veiled) pedagogic strategies deployed by critical GIS scholars today to navigate and circumvent these barriers. Key Messages: Many traditional GIS courses do little to teach GIS critically and critical GIS courses are relatively rare.Several scholars are interviewed to identify key barriers to teaching GIS critically.Pedagogic strategies are presented to navigate and circumvent these barriers. [ABSTRACT FROM AUTHOR]

Spatial modeling is a core element in geographical information science. It incorporates geographic information to construct the relationship for interpreting the behavior of spatial phenomena. In this paper, a broad learning framework for nonparametric spatial modeling is presented. Broad learning overcomes the obstacle of expensive computational consumption in deep learning and provides a powerful computationally efficient alternative. In contrast to the deep learning architecture that is configured with stacks of hierarchical layers, broad learning networks are established in a flat manner that can be flexibly reconfigured with the inherited information from the trained network. To develop the broad learning network, a simple prototype network is established as the initial trial and it is modified incrementally to enhance its data fitting capacity. Consequently, complex relationship of unstructured spatial data can be modeled efficiently. To demonstrate the efficacy and applicability of the broad learning framework, we will present a simulated example and a real application using the strong ground motion records on the 2008 great Wenchuan earthquake. [ABSTRACT FROM AUTHOR]

GIScience and GISystems have been successful in tackling many geographical problems over the last 30 years. But technologies and associated theory can become limiting if they end up defining how we see the world and what we believe are worthy and tractable research problems. This paper explores some of the limitations currently impacting GISystems and GIScience from the perspective of technology and community, contrasting GIScience with other informatics communities and their practices. It explores several themes: (i) GIScience and the informatics revolution; (ii) the lack of a community‐owned innovation platform for GIScience research; (iii) the computational limitations imposed by desktop computing and the inability to scale up analysis; (iv) the continued failure to support the temporal dimension, and especially dynamic processes and models with feedbacks; (v) the challenge of embracing a wider and more heterogeneous view of geographical representation and analysis; and (vi) the urgent need to foster an active software development community to redress some of these shortcomings. A brief discussion then summarizes the issues and suggests that GIScience needs to work harder as a community to become more relevant to the broader geographic field and meet a bigger set of representation, analysis, and modelling needs. [ABSTRACT FROM AUTHOR]

This paper studies multiagent systems where each agent has access to local observations of a dynamic environment and needs to build from this partial information an hypothesis on the state of the system. Each agent ensures that its hypothesis is consistent with its observations, and communicates with other agents to refine this hypothesis by confronting them to their own views. However, these communications are restricted by temporal and topological constraints, and can only be bilateral. We first study in this paper an abstract model of this problem, identifying conditions under which satisfying states can (or will) be reached. We rely in particular on a compositional consistency relation. We then detail a case study involving agents able to reason abductively (with Theorist), and study how demanding are the conditions required in this context. Different bilateral protocols are finally introduced and formally studied, to account for both compositional and noncompositional settings. [ABSTRACT FROM AUTHOR]

As the flagship journal of the field, Conservation Biology represents a multidisciplinary, global constituency of conservation professionals—a constituency composed of more than 5200 authors representing 1500 organizations and 89 countries. Using bibliometric records of research published in Conservation Biology , I evaluated trends in authorship of research papers from 1987 to 2005. Authorship diversified and became increasingly collaborative over time. North Americans now compose one-half of primary authorship, down from 75% in the 1990s, and European primary authors contribute a quarter of the journal's contributed research. Forty-five countries were represented in volume 19 of the journal. The top three most-cited authors are Australian. The percentage of single-authored papers declined from 57% in 1987 to 18% in 2005. Collectively, academic institutions contribute the most research to Conservation Biology , although a government agency, the U.S. Department of Agriculture Forest Service, was the single most-productive organization. The maturing of conservation biology as a discipline, the complex geographic and multidisciplinary nature of conservation questions, and the increased ease of communication in a technologically connected world contribute to the increasingly diverse and collaborative Conservation Biology authorship. [ABSTRACT FROM AUTHOR]

With the rapid development of information techniques, the dimensionality of data in many application domains, such as text categorization and bioinformatics, is getting higher and higher. The high-dimensionality data may bring many adverse situations, such as overfitting, poor performance, and low efficiency, to traditional learning algorithms in pattern classification. Feature selection aims at reducing the dimensionality of data and providing discriminative features for pattern learning algorithms. Due to its effectiveness, feature selection is now gaining increasing attentions from a variety of disciplines and currently many efforts have been attempted in this field. In this paper, we propose a new supervised feature selection method to pick important features by using information criteria. Unlike other selection methods, the main characteristic of our method is that it not only takes both maximal relevance to the class labels and minimal redundancy to the selected features into account, but also works like feature clustering in an agglomerative way. To measure the relevance and redundancy of feature exactly, two different information criteria, i.e., mutual information and coefficient of relevance, have been adopted in our method. The performance evaluations on 12 benchmark data sets show that the proposed method can achieve better performance than other popular feature selection methods in most cases. [ABSTRACT FROM AUTHOR]

Collecting and managing data for clinical and translational research presents significant challenges for clinical and translational researchers, many of whom lack needed access to data management expertise, methods, and tools. At many institutions, funding constraints result in differential levels of research informatics support among investigators. In addition, the lack of widely shared models and ontologies for clinical research informatics and health information technology hampers the accurate assessment of investigators' needs and complicates the efficient allocation of crucial resources for research projects, ultimately affecting the quality and reliability of research. In this paper, we present a model for providing flexible, cost-efficient institutional support for clinical and translational research data management and informatics, the research management team, and describe our initial experiences with deploying this model at our institution. Clin Trans Sci 2012; Volume 5: 464-469 [ABSTRACT FROM AUTHOR]

Key policy drivers worldwide include optimizing patients' roles in managing their care; focusing services around patients' needs and preferences; and providing information to support patients' contributions and choices. The term information need penetrates many policy documents. Information need is espoused as the foundation from which to develop patient-centred or patient-led services. Yet there is no clear definition as to what the term means or how patients' information needs inform and shape information provision and patient care. The assimilation of complex theories originating from information science has much to offer considerations of patient information need within the context of health care. Health-related research often focuses on the content of information patients prefer, not why they need information. This paper extends and applies knowledge of information behaviour to considerations of information need in health, exposing a working definition for patient information need that reiterates the importance of considering the patient's goals and understanding the patient's context/situation. A patient information need is defined as ' recognition that their knowledge is inadequate to satisfy a goal, within the context/ situation that they find themselves at a specific point in the time'. This typifies the key concepts of national/international health policy, the centrality and importance of the patient. The proposed definition of patient information need provides a conceptual framework to guide health-care practitioners on what to consider and why when meeting the information needs of patients in practice. This creates a solid foundation from which to inform future research. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the needs and threats for digital preservation and summarizes the findings from project PARSE.Insight. This project, co-funded by the EU, contains one of the first large worldwide surveys about digital preservation including most players of the STM information chain: researchers, libraries, data managers, publishers, and research funders. One of the conclusions is that in the present data deluge, it is extremely important that all players in the information chain work together on proper digital preservation of all research output, to ensure its future usability, understandability, and authenticity. This poses a new role for publishers who can ensure better discoverability and citability via good linking and integration of data and publications. [ABSTRACT FROM AUTHOR]

Integration of ontologies of information sources and consumers is an important phase in achieving web-based interoperability. The present work describes an approach for identifying certain semantic conflicts while integrating ontologies of heterogeneous information sources. This paper is focused on the identification of homonymy and synonymy between elements in ontologies. In the present work the concepts of homonymy and synonymy are synonymous to naming conflicts and entity identifier conflicts, respectively, and partial synonymy is synonymous to schema isomorphism conflicts. The concept of the mask of interoperability is introduced for the identification of synonymy. The mask of interoperability is expressed in a declarative way as a set of rules, which can then be used for resolution of conflicts during integration of ontologies. As proof of concept, ontologies are implemented using the XML-based ontology language Ontology Web Language (OWL), and the rules are implemented using the emerging rule language Semantic Web Rule Language (SWRL). This representation in OWL and SWRL allows the ontology to be executable, flexibly extendable and platform-independent. The OWL facts and SWRL rules are used by the Jess and Bossam reasoning engine to identify semantic homonymy and synonymy. [ABSTRACT FROM AUTHOR]

Managing multiple ontologies is now a core question in most of the applications that require semantic interoperability. The semantic web is surely the most significant application of this report: the current challenge is not to design, develop and deploy domain ontologies but to define semantic correspondences among multiple ontologies covering overlapping domains. In this paper, we introduce a new approach of ontology matching named axiom-based ontology matching. As this approach is founded on the use of axioms, it is mainly dedicated to heavyweight ontologies, but it can also be applied to lightweight ontologies as a complementary approach to the current techniques based on the analysis of natural language expressions, instances and/or taxonomical structures of ontologies. This new matching paradigm is defined in the context of the conceptual graphs model, where the projection (i.e. the main operator for reasoning with conceptual graphs which corresponds to homomorphism of graphs) is used as a means to semantically match the concepts and the relations of two ontologies through the explicit representation of the axioms in terms of conceptual graphs. We also introduce an ontology of representation, called MetaOCGL, dedicated to the reasoning of heavyweight ontologies at the meta-level. [ABSTRACT FROM AUTHOR]

Card sorts are a knowledge elicitation technique in which participants are given a collection of items and are asked to partition them into groups based on their own criteria. Information about the participant's knowledge structure is inferred from the groups formed and the names used to describe the groups through various methods ranging from simple quantitative statistical measures (e.g. co-occurrence frequencies) to complex qualitative methods (e.g. content analysis on the group names). This paper introduces a new technique for analyzing card sort data that uses quantitative measures to discover rich qualitative results. This method is based upon a distance metric between sorts that allows one to measure the similarity of groupings and then look for clusters of closely related sorts across individuals. By using software for computing these clusters, it is possible to identify common concepts across individuals, despite the use of different terminology. [ABSTRACT FROM AUTHOR]

Knowledge is an inherently dynamic entity continuously changing and evolving. In many cases, the coexistence of different versions of the same core knowledge is a necessity. So is the availability of the proper environment and tools to deal with knowledge versioning. In this paper, a framework of knowledge versioning management is proposed and implemented dealing with hybrid knowledge representation models using frames and rules. This framework facilitates knowledge version handling and maintenance, improving, in parallel, knowledge sharing and reuse. Knowledge components are stored in a set of tables and handled as data under the auspices of a database management system. The proper structure of tables and their relationships allows the creation of independent knowledge modules. Several knowledge modules can be assembled to construct higher level modules, which finally form versions of knowledge. Corresponding knowledge base versions consist of several knowledge modules easy to handle and process in various application areas. The proposed framework has been implemented and thoroughly examined in an application area of great importance, such as pest management. [ABSTRACT FROM AUTHOR]

The evolution of the Information Age, in Canada, has meant an unheralded parallel social evolution —the development of a class structure, if you will, that is tied to data accessibility. While other countries have made data freely available for use by industry, education and the public, Canada has opted to follow a restrictive data policy under which data are essentially available to a select few —those who can afford the prices. While anyone can purchase the data, not everyone can pay the price . The implications of this in our society are immense and are felt throughout our social structures. One obvious example of this is the lack of quality, high-resolution Canadian data freely available for use in the Canadian education system, particularly in the university classes in which students today are usually introduced to GIS, visualization and data interpretation. Our students have data to work with, but often they are the freely available American data. They learn from examples derived in the mountains of Wyoming or the forests of Washington . How did this Canadian data restriction happen? In this paper, the evolution of GIS classicism is explored through examination of the evolution in Canada of GIS itself. The data situation elsewhere in the world is reviewed, the feasibility of ‘freeing’ data is discussed and a call for a radical change in the way data/information are handled in Canada is presented . [ABSTRACT FROM AUTHOR]

Abstract: Granular computing is a mathematical tool in artificial intelligence. An information system is an important model in the field of artificial intelligence, and an information structure is its basic structure. Set‐valued information systems are the generalization of single‐valued information systems. This paper investigates information structures in a set‐valued information system from granular computing viewpoint, that is, information structures are viewed as granular structures. Information structures in a set‐valued information system are first described through set vectors. Then, the dependence between information structures in the same set‐valued information system is depicted from 2 aspects, and information distance for calculating the difference between information structures in the same set‐valued information system is proposed. Next, properties of information structures in a set‐valued information system are given by means of inclusion degree, information distance, condition information amount, and lower approximation operator. Finally, group, mapping, and lattice characterizations of information structures in a set‐valued information system are obtained. These results will be helpful for understanding the essence of structure and uncertainty in set‐valued information systems. [ABSTRACT FROM AUTHOR]

This article identifies some of the important developments in GIS and spatial data analysis since the early 1950s. Although GIS and spatial data analysis started out as two more or less separate areas of research and application, they have grown closer together over time. We argue that the two areas meet in the field of geographic information science, with each supporting and adding value to the other. The article starts off providing a critical retrospective of developments over the past 50 years. Subsequently, we reflect on current challenges and speculate about the future. Finally, we comment on the potential for convergence of developments in GIS and spatial data analysis under the rubric of geographic information science (GIScience). [ABSTRACT FROM AUTHOR]