Read about how you can create systems capable of discovering relationships and detecting patterns within all kinds of data.
The main function of RDF databases (also known as RDF triplestores or semantic graph databases) is to store and query structured data. But why not take this understanding a little bit further and see these DBMSs as story engines, as containers for knowledge bytes? Or maybe with a less poetic tinge, as useful tools that enhance any writing and research workflow where a fast and accurate discovery of information is mission critical. Not surprisingly, these databases have been widely used to manage unstructured and structured data in Media & Publishing.
A triplestore, with all its complexity under the hood, can be looked at as an extremely useful knowledge container, serving publishing and authoring workflows when crafting content. The spirit of such an approach has been communicated wonderfully in the report The Curious Journalist’s Guide to Data.
If you understand data, you will begin to see stories that others literally cannot imagine.
In an environment of billions of information pieces, very often poorly interconnected and scattered across disparate sources, seeing stories and being able to keep a good narrative flowing is a must for anyone in the business of engaging and nurturing audiences. Such ability starts with the realization that data can be stored and queried in a way that adds depth and breadth to authoring and researching.
Seeing stories in data might sound like a stretch for most of us who prefer the good old way of pulling facts, quotes, video and other related content from around the Web and from internal archives, instead of wrangling data and trying to elicit meaning from a set of databases.
Yet, we could open up to a framing where stories, reports, articles and any other author’s work about a given topic are about piecing together components that interact with each other. Or even about weaving connections that span across diverse resources. Then data and stories will not be so much of a stretch to see as the two sides of one and the same coin.
Isn’t every story built of some facts, entities and relationships? And isn’t it the case that the easier and the faster our access to them, the richer and deeper our understanding and from there authoring?
An RDF database, serving as a smart system, to pull data and weave our stories, allows us to handle millions, or hundreds of millions of resources and connections between them to keep the narrative going. Click To Tweet
With a highly connected database we can easily access all kinds of resources from external, internal data or third-party databases.
Of course, to ground things a bit, we need to mention that not all triplestores are created equal. In our Whitepaper The Truth About Triplestores (quoted in the Infobox above) you will see that depending on your task, some of the graph databases can be more helpful, other – less, as they all allow for different extensions and additional capabilities.
GraphDB, Ontotext’s RDF database, for example, implements W3C standards for describing the data and its semantics such as RDF (for representing graph data), SPARQL (the query language for distributed knowledge bases), SKOS (the knowledge organization system), etc. This allows it to easily grow (with the right extensions and functionalities built on top of it), into a knowledge base, a kind of memory palace, and thus be of immense help to any authoring process.
Some of the workflows GraphDB (coupled with additional semantic technology) has been designed to improve and enhance are the ones related to authoring, editorial, production and delivery. With features powered by semantic metadata, intelligent content discovery and recommendation, contextual semantic search, referencing and semantic annotations are brought seamlessly to the process of writing, researching and publishing (see more at Towards Data Driven Publishing).
Discoverability, content analysis and archives management are at the heart of any well-written, researched and authored piece. With a triplestore humming at the back of authoring and publishing systems, many opportunities for smarter content creation open up, including:
Usually preferred for enterprise data integration, master data and metadata management, and data publishing, RDF/SPARQL-based engines are also worth considering as a way to craft coherently connected and cross-referenced content. Leading examples of this are – BBC, IET and Springer Nature – where RDF databases power content management and creation solutions to make richer, deeper and consistent stories.
Want to tell your stories with an RDF database?
White Paper: The Truth About Triplestores