Crack Schemaplic V 30
pdf metadata .pdf -- original: xxx.xxx.xxx.xxx:8088 -- Schemaplic: schemaplic:8088:220.127.116.11.124.91 -- Version: schemaplic:18.104.22.168:22.214.171.124.124.91 -- This article discusses database schemas and their relation to Semantic Web data models, and in particular to Linked Data and RDF Schemas. We are living in a world of high velocity innovation. There is no longer a time for innovation to happen slowly. At a conference on Linked Data in Geneva last year, I heard a number of people state the same sentiment: “We are in a race”. The same pace that is required for the current business model of running, maintaining and deploying applications will not be enough in the future. This need is due to the increasing complexity of the data and data models available today. As Thomas Friedman states in his new book, “The World is Flat”, it is no longer sufficient to have a financial service application with a few data sources and few users. The world is flat because this is the only way to run the business model that is required to keep a profitable company. For a start-up, the flatness of the world is a great opportunity but also a great challenge. If there is no data at all, then how do you know what data you need? The Semantic Web Platform as a Service (PaaS) is one approach to making the world flat. PaaS abstracts away the complexity of data by providing a consistent interface to data and providing tools to collect and publish it. PaaS allows for an easy “plug-and-play” approach to data. However, the advantage of this kind of architecture is that the application developer can use PaaS as a Web service and treat it as a black box. This may be ok for some application, but what happens when we need an RDF Web service that can perform a particular action, like “getting an RDF triple for a particular URI”? This means that the application developer needs to know exactly what data they want and in what format. This has the effect of increasing the complexity of the application. The developer needs to know all the details of the schemas, so they can adapt it to each new data source they want to consume.