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Relational Database

06.18.10
Relational Database and the Semantic Web

In order for the Semantic Web to become a reality and success, there needs to be data on the web published as Linked Data. However, data on the web is not a new thing. People have been publishing raw data for a long time as XML, CSV or even spreadsheets. Data can also be accessed through APIs.  But where does most of the data on the web come from? Relational Databases!

05.04.10
The Pfizer IDEA project: An Interview with Franz’ Jans Aasman and IO Informatics’ Robert Stanley

11.09.09
Creating Dynamic Business Applications using Semantic Web Technology – Part II

This is the second of a two-part series discussing how Semantic Web Technology can enable Dynamic Business Applications in the enterprise. Read Part 1 of the article here.

Empowering New Roles and the Future Role of IT

09.17.09
New W3C Group to Standardize Relational Database to RDF Mapping

W3C announces the new RDB2RDF Working Group, whose mission is to standardize a language for mapping relational data and relational database schemas into RDF and OWL, tentatively called the RDB2RDF Mapping Language, R2RML. From the beginning of the deployment of the Semantic Web there has been increasing interest in mapping relational data to the Semantic Web.

06.19.09
Thoughts on the Semantic Technology 2009 Conference – and the Semantic Web – Kurt Cagle

There comes a point in most programmers careers where they make a startling realization. Computer programming has nothing to do with mathematics, and everything to do, ultimately, with language. It’s a sobering thought. The art of computer programming largely involves the creation of and manipulation of text at the level of the individual character, at the level of the word, the line, the paragraph – and from there to the next level of abstraction:

06.17.09
OpenStructs Announced

 

CORALVILLE, IA, June 16, 2009 — As part of a broader set of product announcements, Structured Dynamics today unveiled openstructs.org, an education and distribution site dedicated to open source software for converting, managing, viewing and manipulating structured data. Structured data can represent any existing data struct from the simplest attribute-value pair formats to fully specified relational database schema. 

06.09.09
Cambridge Semantics to Showcase Practical Solutions for Mainstream Markets at Semtech 2009

Cambridge, MA, June 9, 2009 (Booth #114) – Cambridge Semantics, the leading provider of practical semantic solutions, announced today that its products and company leaders will be featured extensively at the 2009 Semantic Technology Conference (SemTech). With a focus on bringing scalable semantic technology solutions to the mainstream market, Cambridge Semantics will announce at the show the availability of its Anzo(TM) suite of fully packaged semantic applications designed to support practical, enterprise-wide solutions for a wide range of industries.

06.03.09
The Power of Semantic Technology – an Introduction for Enterprise IT Managers

We have witnessed over the years the progression from basic machine languages, to higher-level procedural languages, and then to object-oriented languages. Each advance introduced dramatic improvements in software capabilities that resulted in major leaps forward in fulfilling information technology requirements. We are again on the verge of another major advance in the evolution of software technology that may bring great value to organizations and other information technology beneficiaries.

06.01.09
The Next Big Thing for the Data Management Community – David Wood

The next big thing for the data management community is to give up central control and planning in order to gain scalability and robustness.

06.01.09
Semantic Technology and Master Data Management

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: