Linking geographic vocabularies through WordNet

The linked open data (LOD) paradigm has emerged as a promising approach to structuring and sharing geospatial information. One of the major obstacles to this vision lies in the difficulties found in the automatic integration between heterogeneous vocabularies and ontologies that provides the semantic backbone of the growing constellation of open geo-knowledge bases. In this article, we show how to utilize WordNet as a semantic hub to increase the integration of LOD. With this purpose in mind, we devise Voc2WordNet, an unsupervised mapping technique between a given vocabulary and WordNet, combining intensional and extensional aspects of the geographic terms. Voc2WordNet is evaluated against a sample of human-generated alignments with the OpenStreetMap (OSM) Semantic Network, a crowdsourced geospatial resource, and the GeoNames ontology, the vocabulary of a large digital gazetteer. These empirical results indicate that the approach can obtain high precision and recall

Development of a national pain management competency profile to guide entry-level physiotherapy education in Canada

Background: National strategies from North America call for substantive improvements in entry-level pain management education to help reduce the burden of chronic pain. Past work has generated a valuable set of interprofessional pain management competencies to guide the education of future health professionals. However, there has been very limited work that has explored the development of such competencies for individual professions in different regions. Developing profession-specific competencies tailored to the local context is a necessary first step to integrate them within local regulatory systems. Our group is working toward this goal within the context of entry-level physiotherapy (PT) programs across Canada. Aims: This study aimed to create a consensus-based competency profile for pain management, specific to the Canadian PT contextMethods: A modified Delphi was used to achieve consensus across Canadian university-based and clinical pain educators. Results: Representatives from 14 entry-level PT programs (93% of Canadian programs) and six clinical educators were recruited. After two rounds, a total of 15 competencies reached the pre-determined endorsement threshold (75%). Most participants (85%) reported being "very satisfied" with the process. Conclusions: This process achieved consensus on a novel pain management competency profile specific to the Canadian PT context. The resulting profile delineates the necessary abilities required by physiotherapists to manage pain upon entry-to-practice. Participants were very satisfied with the process. This study also contributes to the emerging literature on integrated research in pain management by profiling research methodology that can be used to inform related work in other health professions and regions

Differences between Pygmy and Non-Pygmy hunting in Congo Basin forests

We use data on game harvest from 60 Pygmy and non-Pygmy settlements in the Congo Basin forests to examine whether hunting patterns and prey profiles differ between the two hunter groups. For each group, we calculate hunted animal numbers and biomass available per inhabitant, P, per year (harvest rates) and killed per hunter, H, per year (extraction rates). We assess the impact of hunting of both hunter groups from estimates of numbers and biomass of prey species killed per square kilometre, and by examining the proportion of hunted taxa of low, medium and high population growth rates as a measure of their vulnerability to overhunting. We then map harvested biomass (kg-1P-1Yr-1) of bushmeat by Pygmies and non-Pygmies throughout the Congo Basin. Hunting patterns differ between Pygmies and non-Pygmies; Pygmies take larger and different prey and non-Pygmies sell more for profit. We show that non-Pygmies have a potentially more severe impact on prey populations than Pygmies. This is because non-Pygmies hunt a wider range of species, and twice as many animals are taken per square kilometre. Moreover, in non-Pygmy settlements there was a larger proportion of game taken of low population growth rate. Our harvest map shows that the non-Pygmy population may be responsible for 27 times more animals harvested than the Pygmy population. Such differences indicate that the intense competition that may arise from the more widespread commercial hunting by non-Pygmies is a far more important constraint and source of conflict than are protected areas

When to Reach for the Cloud: Using Parallel Hardware for Link Discovery

Abstract. With the ever-growing amount of RDF data available across the Web, the discovery of links between datasets and deduplication of resources within knowledge bases have become tasks of crucial importance. Over the last years, several link discovery approaches have been developed to tackle the runtime and complexity problems that are intrinsic to link discovery. Yet, so far, little attention has been paid to the management of hardware resources for the execution of link discovery tasks. This paper addresses this research gap by investigating the efficient use of hardware resources for link discovery. We implement the HR 3 approach for three different parallel processing paradigms including the use of GPUs and MapReduce platforms. We also perform a thorough performance comparison for these implementations. Our results show that certain tasks that appear to require cloud computing techniques can actually be accomplished using standard parallel hardware. Moreover, our evaluation provides break-even points that can serve as guidelines for deciding on when to use which hardware for link discovery

MINTE: Semantically integrating RDF graphs

The nature of the RDF data model allows for numerous descriptions of the same entity. For example, different RDF vocabularies may be utilized to describe pharmacogenomic data, and the same drug or gene is represented by different RDF graphs in DBpedia or Drugbank. To provide a unified representation of the same real-world entity, RDF graphs need to be semantically integrated. Semantic integration requires the management of knowledge encoded in RDF vocabularies to determine the relatedness of different RDF representations of the same entity, e.g., axiomatic definition of vocabulary properties or resource equivalences. We devise MINTE, an integration technique that relies on both: knowledge stated in RDF vocabularies and semantic similarity measures to merge semantically equivalent RDF graphs, i.e., graphs corresponding to the same real-world entity. MINTE follows a two-fold approach to solve the problem of integrating RDF graphs. In the first step, MINTE implements a 1-1 weighted perfect matching algorithm to identify semantically equivalent RDF entities in different graphs. Then, MINTE relies on different fusion policies to merge triples from these semantically equivalent RDF entities. We empirically evaluate the performance of MINTE on data from DBpedia, Wikidata, and Drugbank. The experimental results suggest that MINTE is able to accurately integrate semantically equivalent RDF graphs

Introduction to Linked Data and Its Lifecycle on the Web

With linked data, a very pragmatic approach towards achieving the vision of the semantic web has gained some traction in the last years. The term linked data refers to a set of best practices for publishing and interlinking structured data on the web. While many standards, methods and technologies developed within by the semantic web community are applicable for linked data, there are also a number of specific characteristics of linked data, which have to be considered. In this article we introduce the main concepts of linked data. We present an overview of the linked data lifecycle and discuss individual approaches as well as the state-of-the-art with regard to extraction, authoring, linking, enrichment as well as quality of linked data. We conclude the chapter with a discussion of issues, limitations and further research and development challenges of linked data. This article is an updated version of a similar lecture given at reasoning web summer school 2011

Using Maps for Interlinking Geospatial Linked Data

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Knowledge graphs

18siIn this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We conclude with high-level future research directions for knowledge graphs.nonenoneHogan A.; Blomqvist E.; Cochez M.; D'Amato C.; Melo G.D.; Gutierrez C.; Kirrane S.; Gayo J.E.L.; Navigli R.; Neumaier S.; Ngomo A.-C.N.; Polleres A.; Rashid S.M.; Rula A.; Schmelzeisen L.; Sequeda J.; Staab S.; Zimmermann A.Hogan, A.; Blomqvist, E.; Cochez, M.; D'Amato, C.; Melo, G. D.; Gutierrez, C.; Kirrane, S.; Gayo, J. E. L.; Navigli, R.; Neumaier, S.; Ngomo, A. -C. N.; Polleres, A.; Rashid, S. M.; Rula, A.; Schmelzeisen, L.; Sequeda, J.; Staab, S.; Zimmermann, A