The Experiment – What are we trying to prove?

What am I trying to learn here? I don’t want this to be a fishing expedition with no results or just another blog of data tourism. We know that in order to learn any practical skill we must start as we mean to continue, or at least just start.

I’ve done some thinking about what is the goal I’m trying to achieve. What will I have when I’m finished? How will I know if I’ve succeeded or failed? I want to state a direction but I also want to be flexible enough to shift if I find that an assumption I’ve made at the beginning is wrong or not where I want to go. I want to keep track of all the things I had to do and learn to go from what I am now (i.e. a data architect who knows how to design data structures – glossaries, protocols, data models, databases, ETL functions) to someone who knows how to ‘codify’ data┬áin the semantic web (i.e. how data is an object that is a thing in its own right instead of things that are held by other things).

If I restate that thinking as the question, then:

How can a person who’s learned traditional data architecture (defined as third normal form models, interface file formats, relational database tables, ETL, mapping, etc) achieve expertise in new semantic web technologies including ontologies, inference and data codification? What does that person need to learn, what are the steps, what are the languages and tools?

I know I could take a data science course or a programming course but I think it’s more than that. There’s a psychological shift that I need to make from thinking about data being decanted into containers to data being a thing or an object on its own. I’d like to see how inference works in a practical sense, do it for myself and understand the practical way to get it going. The end result might be more of a continuum of skills rather than a thing that I’ve built, but I suspect I’ll have to build something to get skilled in the technologies that I want to investigate.

The audience for my experiment would be people who have an interest in data and the future of data but don’t know where to start or what to do next (in a sense, the audience is me).

I welcome comments and suggestions. Starting off might be slow as I work out what I need to look at and then try to catch up to all the people who’ve been working on this for years before me. I want to make this a practical how-to so I’ll have to hit all the basics before I get fancy. Time to get started!