VOYAGES OF THE SEMANTIC ENTERPRISE. SPARQL Web Pages. I've written here before about how SPARQL Web Pages (SWP) let you convert your RDF to HTML or XML by embedding SPARQL queries into the appropriate markup. In that very simple example, I showed how to create a web page for an address book entry and then display it both in TopBraid Composer and in a regular web browser.
Today I'm going to show how I did something similar to display a single Person instance from the Kennedys sample data included with TopBraid Composer and then defined a page that showed all the people in that data model. You can download and try the project here. The fun part was displaying it so that it looks like a proper mobile web page on a phone's web browser, as shown here on an Android phone and on an iPhone turned sideways to test the re-orienting capability of the display. Touching someone's name on the phone expands the display to show the remaining property names and values about that person underneath his or her name. The ? This should work with any browser. Running TopBraid Live in the Amazon EC2 Cloud. A recent Dilbert strip inspired me to go through Dave Winer's EC2 for Poets tutorial as a geeky weekend project. It was surprisingly easy and inexpensive to get a computer image running in Amazon's "Elastic Computing Cloud" (EC2) and to then get a copy of TopQuadrant's TopBraid Live running in that image.
These images are cheap to run, as you can see on their price list. Note that the cost per hour of running a default Linux image is not eighty-five cents an hour when using servers in northern Virginia, but eight and a half cents. (It's an additional penny an hour when using their servers in California, Ireland, or Singapore.) If you're willing to spend a dollar or two an hour, you can get full control of some really large-scale computing power without spending much money unless you're planning some long-term use of it, in which case you'll want to compare the options with your requirements more closely than I did. Living in the XML and OWL World - Comprehensive Transformations of XML Schemas and XML data to RDF/OWL. Many enterprise information models are expressed using XML Schemas.
Data between applications is commonly exchanged in XML, compliant with those schemas. Connecting XML data from different systems in a coherent aggregated way is a challenge that confronts many organizations. Capabilities of RDF/OWL to describe semantics of different data models and aggregate disparate data are a natural fit for addressing these challenges. For a number of years now, TopBraid Composer included the ability to convert XSDs and associated XML files to RDF/OWL. However, for some XML Schemas our converter did not work as well as customers needed. For the upcoming TopBraid Composer 3.6.0 release, it was significantly improved to have a more comprehensive coverage of XSD constructs and more meaningful conversion to OWL. An overview of the approach is illustrated in the following figure: Since, the conversion occurs automatically, users do not have to worry about writing any rules for commonly needed mappings.
SPARQL endpoint. SPARQL endpoints are an increasingly popular way to expose linked data. Invoking SPARQL Endpoints from TopBraid Composer's SPARQL view was the subject of a previous TQ blog on SPARQL Endpoints.In this entry we will discuss how TopBraid Live can be used to implement a SPARQL Endpoint using TopBraid Live. SPARQL Endpoints are Web services that conform to the SPARQL protocol. SPARQL queries are passed to a URL where a SPARQL service processes the query and returns results in a defined XML format.
A number of SPARQL Endpoints exist for Web data (see the W3C list of current SPARQL Endpoints) and have become important sources for linked data. A SPARQL Endpoint service implementation is packaged with TopBraid Live and is available out-of-the box for both TopBraid Live Personal Server (TopBraid Composer-ME running on localhost:8083), and TopBraid Live Enterprise Server (for more information, see TBL Home page). Using SPIN functions in SPARQL Endpoints Conclusions. How to convert a spreadsheet to SKOS. In an earlier entry, we learned how SPARQL Rules can increase the quality of taxonomies and other controlled vocabularies stored using the W3C SKOS ontology. (As I wrote there, the Simple Knowledge Organization Systemvocabulary management specification is gaining popularity because, as a standard, it makes it easier to share taxonomies and thesaurii between different systems.
It also guards investments in vocabulary development against the potential problems of dependence on a proprietary vendor format.) TopQuadrant's Enterprise Vocabulary Net (EVN) vocabulary manager uses SKOS as its default format for storing data. Whether you use EVN or not, a first step in systematic management of vocabularies is often the conversion of vocabularies stored in ad hoc spreadsheets—an unfortunately very popular way to store them—to SKOS, so today we'll look at how TopBraid makes this conversion easy. Below is an Excel spreadsheet with some data about a few Caniformia animals. How to use the SPARQLMotion Debugger. Since release 3.3, TopBraid Composer has included an interactive debugger for SPARQLMotion scripts that can make your development go much faster.
TopQuadrant VP of Product Development Holger Knublauch wrote a nice overview of the debugger's features in his blog; below is a short hands-on tutorial in the use of the debugger. We're going to put together a short SPARQLMotion script with a problem that prevents it from running properly. Experienced SPARQLMotion developers may notice the problem when we add it, but leave it in there—we'll see how the SPARQLMotion debugger helps us locate it. Creating our script Our script will prompt the user for a string to search for and then list the first and last names of everyone in the sample kennedy data file included with TopBraid Composer who has that string as part of their first name.
First, create a new SPARQLMotion file and give it a base URI of and a file name of debugdemo. There are two more modules to add. Ontologies and Data Models – are they the same? Yesterday a question about how ontologies may be different from logical data models was asked by a newcomer on TopBraid Users Forum. As to be expected on the TopBraid Forum, by ontologies he meant specifically ontology models expressed in RDFS/OWL. Because we frequently hear this or similar questions in our trainings, workshops and in conversations with customers, I decided to respond in a blog post instead of writing an e-mail. Data modeling was invented more than thirty years ago to help with the design of databases, specifically, relational databases.
As quoted below, ANSI definition from 1975 differentiated between three data models – conceptual, logical and physical. Data modeling quickly became recognized as a tool for analyzing the semantics of an organization with the respect to the structure and flow of the information used in carrying out organization’s activities. Wikipedia offers the following definition of Data Modeling: These statements are called RDF triples.
Converting UML Models to OWL - Part I. Convert UML to OWL - why would you ever want to do this? One reason suffices: many enterprise models, that serve as either standards or enterprise schemas, are specified in UML. Increasingly, there is interest in having content of UML models re-purposed in RDF/OWL and the need for RDF/OWL to interoperate with systems built from UML Models. UML Models are notoriously hard to exchange between UML tools, let alone be transformed into OWL. The exchange format XMI is not only is difficult to understand but also has vendor-specific extensions. The vagaries of MOF, CMOF and EMOF create their own challenges.
Nonetheless we have done transformations of UML to OWL. UML to OWL - Part 1 Contents Part 1 of the series explains the basis of the approach. Note that some diagrams may be too small to be viewed in the body of the document. Goals, Objectives and Requirements The OWL Models must faithfully represent packages and the logical models or class diagrams. Backgrounder on XMI Backgrounder on MOF <? Top. VOYAGES OF THE SEMANTIC ENTERPRISE. S is for Semantics: Stop Press: Microdata in TopBraid. Back during the RSS wars, there was heated disagreement about the format for RSS - among the disagreements was whether RSS should be RDF-based or not. The history is sordid, but from the point of view of someone building a linked data hub like the TopBraid Suite, we could be agnostic about this. Sure, it was great that RSS 1.0 was formatted as good RDF, so that any RDF reader could read it. But the formats aren't that different - at the time, I found a rosetta stone (Yahoo! Was publishing identical feeds in four formats; RSS 0.9x, 1.0, 2.0 and Atom), and gave it to one of my programmers, asking him to create an RSS importer for the TopBraid Suite that would turn all of them into the same triples.
It took him less than a week to turn this out, then a bit longer to test it against lots of feeds. For years now, TopBraid Suite has been able to read feeds in all these formats. He might get around to blogging more details himself as they develop. S is for Semantics. Composing the Semantic Web. Validating schema.org Microdata with SPIN. The new 3.5.1 version of TopBraid Composer introduces some initial features to import, browse, edit and analyze Microdata.
I wrote about this in a previous blog entry - if you want to try those features just download TBC's evaluation version, keeping in mind that Microdata support is still at an early stage and that, for example, the parser isn't fast yet. Today I will focus on a SPARQL-based approach for validating schema.org Microdata using SPIN inside of TopBraid. I have published a library of SPIN constraints at This library currently includes 11 types of integrity constraints covering various aspects on the schema.org ontology, as shown below. The most basic tests are making sure that schema.org properties can only be used at classes with matching domains, and that the values of those properties match their declared ranges. A really powerful demonstration of ontology reuse and linkage is the constraint that validates currency codes.