I've been doing a good bit of research lately on a topic that I admit I didn't know nearly as much about as I should have. But thankfully I'm a fast learner so I've been able to pick up on it quickly and probably catch up with the majority of you. I was struck by a couple of thoughts though as I learned things and want to share them with you. First though I'd like to premise this by stating again, for the record, I don't have all the answers. What follows are my opinions. Have a different opinion? I'd love to hear it.

Re-Discovering a Technology

The latest topic of study for me has been surrounding the technology and terminology associated with RDF. If you're reading this and know what RDF is already I want you to pat yourself on the back, you're smarter than I was. If you're more like I was then you might appreciate the following brief definition.

RDF, or Resource Description Framework, is a standard model for data interchange on the Web. RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed.
- https://www.w3.org/RDF

This is a W3 standards definition. And though it sounds complicated at first, don't panic. It's not really. Here's the shortest of possible summaries of what it means. Hang on we're going to introduce a few new terms. This is a way to identify data with unique identifiers to be used on the web. This means the data can be read, understood, and interpreted by machine and human and to know specifically the context. Those unique identifiers are ways across the internet for data to be consistently shared.

But that's not necessarily the topic for this post. Rather, as I was understanding this subject I learned many more keywords, terminologies, and technologies. Here are a few of the topics I've covered.

Owl, or Web Ontology Language, is a Semantic Web Language designed to represent rich and complex knowledge about things, groups of things, and relations between things. OWL documents are known as ontologies.
- https://www.w3.org/OWL
RDFS this is the schema for RDF, or in other words, the language by which simple RDF vocabularies are represented on the web. Other examples include OWL, mentioned above, are built on RDFS and provide language for defined structures.
- https://www.w3.org/2001/sw/wiki/RDFS
SPARQL is the query language for RDF. It has a second usage as a protocol, however for most intents and purposes it is considered a query language primarily.
- https://en.wikipedia.org/wiki/SPARQL

The truth I saw as I studied these various standards is that these topics don't end with this list. There are many more acronyms, protocols, definitions, standards, and use cases which can be studied and learned about. While I admit I was aware of most of these topics (though never used deeply) I can also admit I don't know many who discuss them outside academia and institutional use cases. And now we get to the true topic of this post and the subtle yet growing realization I had as I dug deeper and deeper into this rich set of possibilities.

The technology adoption problem

The question I asked at the beginning of this post, was why do some technologies fail? What causes them to not be adopted and to grow even though the possibilities for the future are massive? As I said in the beginning, I don't claim to have all the answers, but here's what I believe we can see in this instance and in others where good technology seemingly fails.

Side note: I should request absolution here, I'm not suggesting RDF, OWL, SPARQL and the rest have failed. Rather, they were not recognized for their true value when they were released.

Why technology "fails"

The answer comes through two separate yet related aspects. The first of these comes from the nature of certain technology. The concepts while not foreign are certainly challenging. As the technical skills and prowess required to master a particular topic grows so does the level of difficulty in adoption. The time required to understand and learn the skills necessary to use the technology is a self-limiting factor for growth and expansion. This is the first challenge technology must overcome in order to find a foothold for growth and adoption.

The second is similar, as I suggested, and related because without good documentation and sample use cases the learning curve identified previously is not made any easier. The documentation and subsequent examples (examples really do make the world go round) mitigate some of the friction associated with new technology use. People like to have a very deep and easy to understand method for learning new things. This goes much deeper than I can get into in this particular post because there are many different ways in which a new technology can be learned (Snapchat famously created the quintessential example for shareable design).

Lessons to be learned

And so, coming back to the topic at hand. These incredible technologies may not have "failed" fully. There is still hope to see this incredible technology take off and take over the world. Perhaps in the case of RDF (and the rest) the problem can still be solved, and perhaps now is the optimal time for such a technical topic to again be explored, expanded upon and implemented. Perhaps all which is needed is a couple answers as described above. And perhaps you should consider following my Tech Tuesday posts!