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Data is generally saved in many different databases. Data analysis is more valuable if applied to all data, not just data from a single source. In addition, data analysis can generate more interesting results if it takes into account logical links existing between data from various sources. For example, data from a petroleum deposit stored in database A can be linked to predictions saved in database B and linked to real-time measurements of oil extraction saved in database C.

An analysis taking into account all data and all logical links between data is ideal. This is only possible by using standards for:

• Identifying data at a global level
• Making data accessible
• Describing data and links between data from various sources

At Koneksys, we believe that adoption of the following 3 Web standards supports these goals and helps link data better:

• URL for identifying data at a global level (as for web pages in HTML)
• REST API (HTTP) compliant with a Hypermedia standard (e.g OSLC or smartAPI) for making data accessible (improved version of the REST APIs that are currently commonly used)
• RDF for describing data and links between data of various origins (the equivalent of HTML but for data)

URL, HTTP, and RDF are Web standards defined by the W3C organization. Basically, we apply the architecture of the Web, as it currently exists to connect web pages, to connect data on a private enterprise Web (beware, this is not about a public web, although of course it can be applied there as well). We call this approach the “Data Web”. This approach provides a global view of data and its links which may easily be updated anytime and in turn provide updated analysis results.

Traditional data management applications are restricted to using data from a specific source. In contrast, Web search engines, such as Google’s search service, consider the Web as its source of documents instead of a specific database. The Web can therefore be viewed as a source for documents and data. We believe that future data management applications, such as for data analysis and visualization, will use data on the private enterprise Web as a source, in other words the Data Web as a “new global database”.

Koneksys offers solutions to integrate data according to the Data Web. We have developed all components of the Data Web architecture:

• Servers exposing data according to standardized REST APIs
• Clients using these REST APIs
• Data management solutions taking as input data from the private enterprise Web instead of a specific database, to further process it for example with specific solutions such as Spark or Elasticsearch

More details can be found at the slide deck, ‘Data Integration Solutions Created By Koneksys’.

We believe that the Data Web will revolutionize the architecture of data management solutions.