I help my clients to enjoy the full benefits of the underlying graph that links the objects described in their data. This graph may link documents to their authors, events to places, products to their documentation, despite of these objects being stored in distinct databases.
Graphs vs. tables vs. trees
The traditional data storage technologies that use tables (relational databases, SQL) or trees (NoSQL, JSON, XML), force the data modellers to make compromises with the original mental data model. Today, standard technologies enable the storage of native graphs, so that you don’t need to make any compromise with your data model.
100% standard technologies (W3C, IETF)
To publish this data, internally or externally, I exclusively use standard and documented Web technologies:
- HTTP for data transport (Wikipedia)
- URIs (Universal Resource Identifiers, Wikipedia), for instance http://colin.maudry.com/id/me or http://www.data.maudry.com/organizations/premier-ministre
- HTML and CSS for human consumption and user interfaces
- JSON, XML, Turtle and CSV for machine consumption
- RDF for structuring and adding semantics to the data
This set of standards and methods to publish data is called Linked Data, because it establishes explicit links between objects (documents, people, places, etc.) This consequently is a solution to data silos (thanks to the native links) and closed platforms (thanks to standards).
If you would like to assess how Linked Data could benefit to your organization, contact me! I’m especially interested in Open data projects.
Reading list
Here is a reading list for those who are curious about Linked Data and the Semantic Web (sorted by increasing complexity and depth):
- Linked Data on Wikipedia
- What is Linked Data? by Manu Sporny
If you don’t feel like reading, this video explains what Linked Data is from scratch - The Semantic Web on Wikipedia
Linked Data is one application of the Semantic Web - DBpedia on Wikipedia
Dbpedia is a good example of how the Web of documents can be extended towards the Web of data, and how they complete each other - RDF 101 by Campbridge Semantics
RDF for the beginner - RDF vs. XML by Campbridge Semantics
Despite what the title implies, this article explains that RDF and XML are not opposed and simply serve different purposes - Semantic Web for the Working Ontologist, Second Edition: Effective Modeling in RDFS and OWL (paperback/Kindle) by Dean Allemang and James Hendler
Excellent book for those who want to learn how to create ontologies and data modelling in the Semantic Web. You just need to have read the first 3 items of my list to be at ease reading this book. - The Linked Data book (HTML version), by Christian Bizer and Tom Heath
Scroll up to see the table of contents; the bible of Linked Data, focus on the sections that catch you attention - Linked data patterns (HTML), par Leigh Dodds
The book of the Linked Data practitioner. It covers dozens of typical use cases.