Vocabularies are the building blocks of the Semantic Web providing shared terminological resources for content indexing, information retrieval, data exchange, and content integration. Most semantic web applications in practical use are based on lightweight ontologies and, more recently, on the Simple Knowledge Organization System (SKOS) data model being standardized by W3C. Easy and cost-efficient publication, integration, and utilization methods of vocabulary services are therefore highly important for the proliferation of the Semantic Web. This paper presents the ONKI SKOS Server for these tasks. Using ONKI SKOS, a SKOS vocabulary or a lightweight ontology can be published on the web as ready-to-use services in a matter of minutes. The services include not only a browser for human usage, but also Web Service and AJAX interfaces for concept finding, selecting and transporting resources from the ONKI SKOS Server to connected systems. Code generation services for AJAX and Web Service APIs are provided automatically, too. ONKI SKOS services are also used for semantic query expansion in information retrieval tasks. The idea of publishing ontologies as services is analogous to Google Maps. In our case, however, vocabulary services are provided and mashed-up in applications. ONKI SKOS was published in the beginning of 2008 and is to our knowledge the first generic SKOS server of its kind. The system has been used to publish and utilize some 60 vocabularies and ontologies in the National Finnish Ontology Service ONKI www.yso.fi.
Abstract. CULTURESAMPO is an application demonstration of a national level publication system of cultural heritage contents on the Web, based on ideas and technologies of the Semantic (Web and) Web 2.0. On the semantic side, the system presents new solutions to interoperability problems of dealing with multiple ontologies of different domains, and to problems of integrating multiple metadata schemas and cross-domain content into a homogeneous semantic portal. A novelty of the system is to use semantic models based on events and narrative process descriptions for modeling and visualizing cultural phenomena, and for semantic recommendations. On the Web 2.0 side, CULTURESAMPO proposes and demonstrates a content creation process for collaborative, distributed ontology and content development including different memory organizations and citizens. The system provides the cultural heritage contents to end-users in a new way through multiple (nine) thematic perspectives, based on semantic visualizations. Furthermore, CULTURESAMPO services are available for external web-applications to use through semantic AJAX widgets. A Basis for Cultural Heritage on the Semantic WebIn our view, a cross-domain semantic cultural heritage portal [1] should be built on three pillars: First we need a cross-domain content infrastructure of ontologies, metadata standards, and related services, that is developed and maintained on a global level through collaborative local efforts. Second, the process of producing ontologically harmonized metadata should be organized in a collaborative fashion, where distributed content producers create semantically correct annotations cost-efficiently through centralized services. Third, the contents should be made available to human end-users and machines thought intelligent search, browsing, and visualization techniques. For machines, easy to use mash-up APIs and web services should be available. In this way, the collaboratively aggregated, semantically enriched knowledge base can be exposed and reused easily as services in other portals and applications in the same vein as Google Ads or Maps 1 .1
This paper presents the results of a pilot study on using automatic text categorization techniques in identifying online sexual predators. We report on our SVM and k-NN models. Our distance weighted k-NN classifier reaches an f-measure of 0.943 on test data distinguishing the child and the victim sides of text chats between sexual predators and volunteers posing as underage victims.
Abstract.The number of open datasets available on the web is increasing rapidly with the rise of the Linked Open Data (LOD) cloud and various governmental efforts for releasing public data in different formats, not only in RDF. The aim in releasing open datasets is for developers to use them in innovative applications, but the datasets need to be found first and metadata available is often minimal, heterogeneous, and distributed making the search for the right dataset often problematic. To address the problem, we present DataFinland, a semantic portal featuring a distributed content creation model and tools for annotating and publishing metadata about LOD and non-RDF datasets on the web. The metadata schema for DataFinland is based on a modified version of the voiD vocabulary for describing linked RDF datasets, and annotations are done using an online metadata editor SAHA connected to ONKI ontology services providing a controlled set of annotation concepts. The content is published instantly on an integrated faceted search and browsing engine HAKO for human users, and as a SPARQL endpoint and a source file for machines. As a proof of concept, the system has been applied to LOD and Finnish governmental datasets.
Metadata about documents, artifacts, and other objects is traditionally created by filling in metadata fields (e.g., dc:subject) with values taken from controlled vocabularies, such as keyword thesauri and classifications (e.g., LCSH). When this practice is applied to Linked Data a new problem is encountered: Linked data typically comes from different organizations and domains where mutually incompatible thesauri and classifications are used in annotations. This breaks links between the annotations, which creates data silos in linked data clouds. This paper argues that to solve the problem it is not enough to link data using primarily owl:sameAs mappings, as is customary today in, e.g., the Linked Open Data cloud, but one has to link annotation vocabularies, i.e., ontologies, into a Linked Open Ontology cloud. Since class hierarchies (using, e.g., rdfs:subClassOf) form the backbone of annotation ontologies, a key problem here is how to create and maintain a system of interlinked hierarchical ontologies so that the transitive subclass relations are not broken, when reasoning across ontologies in fundamental tasks such as query expansion and property inheritance. As a solution, we present the steps necessary for transforming thesauri into a cloud of ontologies and maintaining the system when ontologies are updated. Our approach has been used and evaluated in practice in building a cloud called KOKO of sixteen ontologies, with a total of 47,000 concepts, forming a basis for the Finnish national Linked Data architecture. KOKO has been published as an ontology service and is in use in, e.g., collection managing systems for both data indexing and semantic search.
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