A number of accessible RDF stores are populating the linked open data world. The navigation on data reticular relationships is becoming every day more relevant. Several knowledge base repositories present relevant links to common vocabularies while many others are going to be discovered increasing the reasoning capabilities of our knowledge base applications. Linked Open Graph, LOG, is a web tool for collaborative browsing and navigation on multiple SPARQL entry points, RDF stores and LD in integrated manner. The LOG.disit.org tool is shortening the gap from the users to understand the Linked Data and provides an easy and accessible set of samples to navigate in multiple RDF stores with LD/LOD: providing features and advantages using dbPedia, Getty, Europeana, Geonames, etc. The LOG tool is free to be used, and to be embedded in third party pages. It has been adopted, developed and/or improved in multiple projects: such as ECLAP for social media cultural heritage, Sii-Mobility for smart city, and ICARO for cloud ontology analysis, OSIM for competence / knowledge mining and analysis.
The LOG.DISIT.ORG is covering multiple domains: cultural heritage, library, smart city, smart cloud, e-govern, etc. It allows discovering links, saving and sharing the graphs among a community.
K12-exam-app: detailed digital (RDF) curriculum in NL to connect information domains
Cable-stayed bridge is a subtype of Bridge. The semantic definition formulates the discriminating property by which it is distinguished from its parent.
It also gives the supertypes in the taxonomy, from which it inherits all given discriminating properties.
The CB-NL is an initiative of the BIR (Dutch Building Information Council),
Exchange and bringing together overlapping or complementing information from various sources, applications, and perspectives has been a major issue in both commercial and scientific domains. Several aspects can be identified that complicate the realization of a solution to the problem one of the largest being the way in which information is offered. Differences in formats or structures of information as well as differences in vocabulary provide hurdles for the interoperability and integration of information.
In the past 5-10 years, Semmtech has been working on a so called SEMMweb Data Cloud-solution, making full use of Semantic Web-technology in an advanced and innovative manner. A Data Cloud is a coherent set of information that can be used by different software from different suppliers unbound by the location where the information is stored. A Data Cloud can be a single autonomous set of information or a collection of different sets which link information into a coherent whole. A Data Cloud can describe any business domain, like for instance civil engineering products, throughout its life-cycle, while different parts (subsets) of the data are managed by different parties in the supply chain, with different software from different vendors. Information in a Data Cloud is retrievable via the Internet and can be (re)used by different parties to add data about any object, contributing to one big ’cloud’ of data that covers parts of or even the whole range of references and attributes related to an object.
An interesting case that combines some of the most relevant components of the Data Cloud-solution in a working prototype is the V-con project. The prime focus of this prototype is to tackle a set of interoperability challenges as set by two National Road Authorities (i.e. Rijkswaterstaat and Trafikverket) in a European project by the name of Virtual Construction for Roads (V-Con). Specifically in this project, Semmtech is partnering with the global engineering firm Arcadis.
The SemaGrow project develops a Linked Data infrastructure that allows transparent access to distributed heterogeneous and constantly updated large datasets. The developed innovations are delivered as the SemaGrow Stack, an open source software package. Through the SemaGrow Stack applications can access heterogenous, distributed triple stores using a single SPARQL endpoint, without having knowledge of the underlying schemas of the individual sources. To prove its practical value, the SemaGrow Stack is tested in data and knowledge intensive use cases from the agro-environmental domain.