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For some time now, Structured Dynamics (SD) has been touting the unique advantages of ODapps, or ontology-driven applications [1]. ODapps are modular, generic software applications designed to operate in accordance with the specifications contained in one or more ontologies. The relationships and structure of the information driving these applications are based on the standard functions and roles of ontologies (namely as domain ontologies), as supplemented by UI and instruction sets and validations and rules. When these supplements are added to standard ontology functions, we collectively term them adaptive ontologies [2].

"Virtually everywhere one looks we are in the midst of a transition for how we organize and manage information, indeed even relationships. Social networks and online communities are changing how we live and interact. NoSQL and graph databases - married to their near cousin Big Data - are changing how we organize and store information and data. Semantic technologies, backed by their ontologies and RDF data model, are showing the way for how we can connect and interoperate disparate information in ways only dreamed about a decade ago. And all of this, of course, is being built upon the infrastructure of the Internet and the Web, a global, distributed network of devices and information that is undoubtedly one of the most important technological developments in human history. There is a shared structure across all of these developments - the graph. Graphs are proving to be the new universal paradigm for how we organize and manage information. Graphs have an inherently expandable nature, and one which can also capture any existing structure. So, as we see all of the networks, connections, relationships and links - both physical and informational - grow around us, it is useful to step back a bit and contemplate the universal graph structure at the core of these developments. Understanding that we now live in the Age of the Graph means we can begin studying and using the concept of the graph itself to better analyze and manage our interconnected world. Whether we are trying to understand the physical networks of supply chains and infrastructure or the information relationships within ontologies or knowledge graphs, the various concepts underlying graphs and graph theory, themselves expressed through a rich vocabulary of terms, provide the keys for unlocking still further treasures hidden in the structure of graphs."

Ontologies are to the Open Semantic Framework what humans were to the Mechanical Turk. The hidden human in the Mechanical Turk was orchestrating all and every chess move. However, to the observers, the automated chess machine was looking just like it: a new kind of intelligent machine. We were in 1770.

According to the W3C, "The Media Annotations Working Group invites implementation of the Candidate Recommendation Ontology for Media Resources 1.0.

Developers can find excellent resources at productontology.org, home of The Product Types Ontology: High-precision identifiers for product types based on Wikipedia.

Some of the key findings from the 2011 State of Tooling for Semantic Technologies are: As of the date of this article, there are 1010 tools in the Sweet Tools listing, the first it has passed 1000 total tools A total of 158 new tools have been added to the listing in the last six months, an increase of 17% 75 tools have been abandoned or retired, the most removed at any period over the past five years A further 6%, or 55 tools, have been updated since the last listing Though open source has always been an important component of the listing, it now constitutes more than 80% of all listings; with dual licenses, open source availability is about 83%. Online systems contribute another 9% Key application areas for growth have been in SPARQL, ontology-related areas and linked data Java continues to dominate as the most important language.

 Tim Berners Lee recognized the problematics of the messy web early on and proposed the Semantic Web to overcome messiness and apply a semantic structure to bring order (read: computer logic) in the chaos (read: human expression). Pierre Levy, French philosopher and leading expert on collective intelligence, is on a similar mission. While driven by, arguably, a similar set of goals, his approach takes a step further. The problem with Berners Lee semantic structure is that implies a universal ontology, which might prove out to be the Achilles heel of the protocol. Levy's approach overcomes these problems. Levy is currently working on a research program, called IEML (Information Economy Meta Language). IEML is a metalanguage and proposes itself as the language of collective intelligence. 

Semantics can enhance a broad variety of information processing - search, integration, analysis, pattern extraction and mining, discovery, situational awareness, and question-answering. Consider search: a search system that could distinguish between "Merry Christmas" as a greeting and one of the 60 or so songs named "Merry Christmas" as cataloged in MusicBrainz (a community-created music encyclopedia; http://musicbrainz.org) would have a powerful semantic search capability.