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DFDF - A Descriptive Approach to Data Standardization Data standardization is fundamentally prescriptive; no information system can solve the data integration problem without enforcing certain rules. But the challenge remains at where the rules should be prescribed. Most existing data standards prescribe the rules over the data itself. Excessive use of such an approach, however, leads to inefficient data representation. The alternative approach is to enforce the conforming rules over the description of the data so that data itself can be encoded in any manner. By developing ontologies for describing the data format and software libraries that can understand the ontology, this descriptive approach to data standardization will provide maximal flexibility in data representation while still ensuring the data interoperability.

The mission of the RDF Working Group, part of the Semantic Web Activity, is to update the 2004 version of the Resource Description Framework (RDF) Recommendation. The scope of work is to extend RDF to include some of the features that the community has identified as both desirable and important for interoperability based on experience with the 2004 ...

SADI is a framework for discovery of, and interoperability between, distributed data and analytical resources. It combines simple, stateless, GET/POST-based Web Services with standards from the W3C Semantic Web initiative. The objective of SADI is to make it easy for data and analytical tool providers to quickly make their resources available on the Semantic Web with minimal disruption to their usual practices. SADI is quite a distinct "technology" in that there's nothing to it… literally! SADI avoids creating new technologies or non-standard Web "infrastructure" (e.g., message formats).

"SWAG is creating a strong infrastructure for the Semantic Web, whilst working with various members of the Web community to ensure data interoperability. The SWAG Dictionary, a database of terms for the Semantic Web, is our first important project to that end. Our work should always be available at our PURL (persistent URL) as described in our URI Persistence Policy."

"Cognonto exploits large-scale knowledge bases and semantic technologies for effective machine learning and data interoperability. The Cognonto Platform powers knowledge management-oriented Web services and APIs. Try it for yourself:"

"KBpedia is a comprehensive knowledge structure for promoting data interoperability and knowledge-based artificial intelligence, or KBAI. The KBpedia knowledge structure combines six (6) public knowledge bases - Wikipedia, Wikidata, OpenCyc, GeoNames, DBpedia and UMBEL - into an integrated whole. KBpedia's upper structure, or knowle"

"Cognonto is an IT consulting boutique specializing in semantic technologies, knowledge graphs, and knowledge-based artificial intelligence. We are the developers of, and have unique expertise in, the knowledge structure KBpedia and its use in machine learning and data interoperability. Cognonto principals are scientists and acknowledged experts in knowledge representation, natural language understanding, and distributed knowledge sharing."

"KBpedia exploits large-scale knowledge bases and semantic technologies for effective machine learning and data interoperability. Here are some example ways that KBpedia may power knowledge management-oriented Web services or APIs. Try it for yourself:"

SPITFIRE: Semantic-Service Provisioning for the Internet of Things using Future Internet Research by Experimentation