Protege Wiki Metadata? Thesauri? Taxonomies? Topic Maps! Making sense of it all Abstract To be faced with a document collection and not to be able to find the information you know exists somewhere within it is a problem as old as the existence of document collections. Information architects have so far applied known and well-tried tools from library science to solve this problem, and now topic maps are sailing up as another potential tool for information architects. The paper argues that topic maps go beyond the traditional solutions in the sense that it provides a framework within which they can be represented as they are, but also extended in ways which significantly improve information retrieval. Table of contents 1. The task of an information architect is to create web sites where users can actually find the information they are looking for. Topic maps are a relative newcomer to this area and bring with them the promise of better-organized web sites, compared to what is possible with existing techniques. 2. 2.1. Metadata 2.2. Table 2.1. title
Web Ontology Language Un article de Wikipédia, l'encyclopédie libre. Pour les articles homonymes, voir OWL. Le langage OWL est basé sur les recherches effectuées dans le domaine de la logique de description. Il peut être vu en quelque sorte comme un standard informatique qui met en oeuvre certaines logiques de description, et permet à des outils qui comprennent OWL de travailler avec ces données, de vérifier que les données sont cohérentes, de déduire des connaissances nouvelles ou d'extraires certaines informations de cette base de données. Il permet notamment de décrire des ontologies, c'est-à-dire qu'il permet de définir des terminologies pour décrire des domaines concrets. Une terminologie se constitue de concepts et de propriétés (aussi appelés « rôles » en logiques de description). Une extension de RDF[modifier | modifier le code] RDF permet par exemple de décrire que <Jean> est le père de <Paul>, au travers des individus <Jean>, <Paul>, et de la relation est le père de. .
Semantic Technology’s Role in Big Data Solutions? Forbes has published an article that points out an opportunity for Semantic Technology companies. The article discusses the lack of understanding in companies around big data. Author Gil Press writes, “Listening to Gartner analysts Sheila Childs and Merv Adrian talking yesterday about big data infrastructure challenges, I was reminded of a story Mike Ruettgers, former EMC CEO, liked to tell about similar challenges in the early 1990s. At the time, the reigning buzzword was ‘client/server computing,’ signaling a shift to relatively inexpensive servers based on the UNIX operating system. The early adopters were not the people in the glass houses, the data center managers. He goes on, “Visiting the CIO of John Deere, Ruettgers asked him whether he saw these ‘distributed systems’ coming back to be managed by the IT department. Press notes, “You may find that all of your best DW, BI, MDM practices for SDLC, PMO and Governance aren’t directly applicable to or just don’t work for Big Data.
Ontology creation for the rest of us… COE is a project whose goal is to develop an integrated suite of software tools for constructing, sharing and viewing OWL encoded ontologies based on CmapTools, a concept mapping software used in educational settings, training, and knowledge capturing. Concept maps provide a human-centered interface to display the structure, content, and scope of an ontology. Currently, our work focuses on developing conventions for constructing new Cmap OWL ontologies that will assist and guide users when forming class and property relationships among the concepts in the ontology. In addition, we are working on clustering and searching techniques that support the reuse of existing ontologies. An overview presentation is here. Startup instructions are here. The manual is here. Papers OWL Templates People Adding IHMC Public Ontologies Download Updater for V5.0.3
IsaViz Overview News IsaViz and Java 1.6 (2007-10-21) IsaViz 2.x is not compatible with Java 1.6 or later. IsaViz and GraphViz (2007-05-23) IsaViz 2.x is not compatible with GraphViz 2.10 or later. Several bugs have been fixed in the FSL engines for Jena, Sesame and the visual FSL debugger embedded in IsaViz. Fresnel in IsaViz (2006-05-19) IsaViz 3.0 now supports Fresnel lenses and several elements of the Core Format Vocabulary. FSL for Sesame 2-alpha-3 (2006-04-25) The FSL engine for Sesame 2 now works with version 2alpha3 instead of version 2alpha1. FSL for Sesame 1.2.2 (2005-12-06) In addition to the Sesame 2.0 implementation of FSL, there is now a Sesame 1.2.2 implementation written by Ryan Lee from project Simile. Java FSL Documentation available (2005-11-18) Documentation for the three existing Java FSL engine implementations (for Jena, Sesame and IsaViz) is now available. FSL for Sesame 2.0 (2005-11-15) Fresnel comes with a companion proposal specifying a path language for RDF called FSL. Screenshots
RelFinder - Visual Data Web Are you interested in how things are related with each other? The RelFinder helps to get an overview: It extracts and visualizes relationships between given objects in RDF data and makes these relationships interactively explorable. Highlighting and filtering features support visual analysis both on a global and detailed level. The RelFinder is based on the open source framework Adobe Flex, easy-to-use and works with any RDF dataset that provides standardized SPARQL access. Check out the following links for some examples: The RelFinder can easily be configured to work with different RDF datasets. The RelFinder can also be more deeply integrated with your project: Integrating the RelFinder See the following examples of how the RelFinder is integrated into other projects: Ontotext applies the RelFinder to enable an exploration of relationships in the biomedical domain. All tools on this website are research prototypes that might contain errors.
Pearltrees: mise à jour de l’export RDF Pour rentrer dans le vif du sujet, voici les modifications apportées sur l’export RDF de pearltrees : Fixe des problèmes de casse Remplace owl:sameAs par dc:identifier sur la class pt:Pearl Remplace owl:sameAs par rdfs:seeAlso sur les perles référencant des pt:Tree Remplace le préfix dc: par dcterms: Utilisation de sioc:UserAccount pour lier foaf et pearltrees Description simple du schéma pearltrees sur l’url associé Ajout de pt:inTreeSinceDate sur pt:Pearl Ajout de pt:treeId, pt:assoId et pt:lastUpdate sur pt:Tree Sur l’année passée j’ai reçu avec grand plaisir les retours de nombreuses personnes, je tiens à remercier particulièrement Alexandre , Gautier et Vincent pour leurs feedbacks détaillés. Je vous invite à créer un compte pearltrees , et explorer par vous même votre export. Un petit exemple d’utilisation de l’export et de l’interface javascript de l’embed: En cliquant sur les liens suivants vous pouvez piloter l’embed ci-dessus Mon pearltree Governement Data share Uncategorized
Tracker Tracker is a search engine, search tool and metadata storage system. It allows you to find the proverbial needle in your computer's haystack as well as providing a one stop solution to the organisation, storage and categorisation of your data. User Resources Getting in Touch IRC channel Mailing list File a bug Maintainers: Martyn Russell nickname martyn Jürg Billeter nickname juergbi Carlos Garnacho nickname garnacho Philip Van Hoof nickname pvanhoof Ivan Frade nickname frade Mikael Ottela nickname ottela Aleksander Morgado nickname aleksander Development Resources Semantic desktop In computer science, the Semantic Desktop is a collective term for ideas related to changing a computer's user interface and data handling capabilities so that data is more easily shared between different applications or tasks and so that data that once could not be automatically processed by a computer could be. It also encompasses some ideas about being able to automatically share information between different people. This concept is very much related to the Semantic Web but is distinct insofar as its main concern is the personal use of information. General description[edit] The vision of the semantic desktop can be considered as a response to the perceived problems of existing user interfaces. Secondly there is the problem of relating different files with each other. Related to this a user will often access a lot of data from the Internet which is segregated from the data stored locally on the computer, being accessed through a browser or other programs. Standardization effort[edit]
Generating RDF from data.gov - Data-gov Wiki From Data-gov Wiki Overview Many of the datasets in data.gov are available as tables (spreadsheets). This makes it easy to translate the datasets into RDF by generating a triple for each table cell where the row id is the subject, the column name is the predicate, and the cell content is the object. In the first principle, we minimize our translation by (i) preserving the functional structure of the original tables and (ii) skipping additional understanding of the cell content. In the second principle, we keep the translated RDF friendly to Web users. Our third principle was approached by using a semantic wiki to host user contributed extensions. In our fourth principle we preserve knowledge provenance of the converted RDF documents by embedding metadata about their sources, creators, and creation date time using the well-known Dublin Core and FOAF vocabularies. To find more details, please go to The Problem Here is an example <? <?
Planet RDF Resource Description Framework The Resource Description Framework (RDF) is a family of World Wide Web Consortium (W3C) specifications[1] originally designed as a metadata data model. It has come to be used as a general method for conceptual description or modeling of information that is implemented in web resources, using a variety of syntax notations and data serialization formats. It is also used in knowledge management applications. RDF was adopted as a W3C recommendation in 1999. The RDF 1.0 specification was published in 2004, the RDF 1.1 specification in 2014. Overview[edit] RDF is an abstract model with several serialization formats (i.e. file formats), so the particular encoding for resources or triples varies from format to format. As RDFS and OWL demonstrate, one can build additional ontology languages upon RDF. History[edit] The W3C published a specification of RDF's data model and an XML serialization as a recommendation in February 1999.[9] RDF topics[edit] RDF vocabulary[edit] Classes[edit] rdf[edit] rdfs[edit] <?
Marbles Linked Data Engine