Andrew Phelps reports, “Data nerds from government and academia gathered Friday at Northeastern University to show off the latest version of Weave, an open-source, web-based platform designed to visualize ‘any available data by anyone for any purpose.’ The software has a lot of potential for journalists. Weave is supported by the Open Indicators Consortium, an unusual partnership of planning agencies and universities who wanted better tools to inform public policy and community decision-making. The groups organized and agreed to share data and code in 2008, well before Gov 2.0 was hot.” Read more

SemTechBiz is Less Than 2 Weeks Away

The Semantic Tech & Business Conference (SemTechBiz) is coming to San Francisco on June 3-7! Join us for case studies, innovative panels, tutorials, and keynotes that will provide you with practical advice, hands-on guidance, and breakthrough approaches to solving business problems with semantic technology. Passes go up $200 at the door. Sign up now and save !

With the Web 2.0, ontologies are being used to improve search capabilities and make inferences for improved human or computer reasoning. By relating terms in an ontology, the user doesn’t need to know the exact term actually stored in the document. Data Rationalization is a Managed Meta Data Environment (MME) enabled application which creates/extends an ontology for a domain into the structured data world, based on model objects stored in various models (of varying levels of detail, across model files and modeling tools) and other meta data. Ontology is “the study of the categories of things that exist or may exist in some domain”1. An ontology is comprised of “a collection of taxonomies and thesauri”2 about a domain. Data Models, often unknowingly, express many aspects of ontology, even though they are not stored in OWL or RDF.

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Master Data Management is now mainstream and those of us who have practiced it for a few years are battered, bruised and wearily displaying our scars. Typically defined as the people, processes and systems that govern the core data (e.g. products, customers, suppliers) needed to run a business, Master Data Management (or MDM) requires painstaking work in three broad areas: data standardization, architecture, and governance:

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I cam across this in the Ontolog-Forum, and got permission from Mike Bennett, the author to quote it.  Some great pragmatism here, on the one hand we need to apply semantics and ontology building to systems development and integration, but at the same time, let’s not get too carried away trying to "model reality." 

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I came across this in the Ontolog-Forum, and got permission from Mike Bennett, the author, to quote it.  Some great pragmatism here: on the one hand, we need to apply semantics and ontology building to systems development and integration, but at the same time, let’s not get too carried away trying to "model reality." 

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XML Keyword Search is still a popular academic subject. It has not reached or been recognized by XML and Internet commercial products yet. The concepts involved are also very important to the semantic web. The semantics industry today with its work on higher level semantics like ontologies and taxonomies has overlooked the importance of utilizing the semantics of hierarchical structured data like XML. When working with hierarchically structured data, the first level of handling semantic understanding must be recognizing the hierarchical structure and its (lower level) hierarchical semantics. This is then used to eliminate false keyword search results that can show up as matches in hierarchical structures; otherwise they will go undetected to the higher level semantic processing which will also not detect them since they are not concerned with the structure of the data. This will cause unmeaningful results to be returned. 

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Executive Summary

Today the data structure transformation terminology of Restructuring and Reshaping are used interchangeably for XML structure transformation processes. There are two basic types of XML hierarchical data structure transformations that need to be distinguished because they are different in meaning, results, and use. These are restructuring controlled by existing relationships in the data, and reshaping controlled by the semantics of the current data structure. Restructuring is performed by using new and unused relationships to restructure the data. On the other hand, reshaping uses the semantics of the current structure to mold the structure into any other shape without requiring or relying on any data relationships in the data. The processing follows correct hierarchical semantics principles to derive correct hierarchical results.

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Executive Summary

SeMuSe is an open and collaborative community based project to work on a Semantic Museum vision, and provides a forum for discussion of the future of applied cultural and natural heritage data management. Members of SeMuSe can greatly benefit from advancements made in the Semantic Technology community. The goal of SeMuSe is to help organizations and practitioners to introduce Semantic Technologies and concepts to cultural and natural heritage data management efforts and to capitalize on the results of more than a decade of Semantic Technology research. Emerging technology standards like RDF, RDFS and OWL and domain specific vocabularies such as museumdat and the CIDOC CRM ontology specification are a marriage made in Semantic Technology heaven, allowing to lead semantic cultural and natural heritage data management to its full potential – SeMuSe.

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