Back in my college days, I worked on (or near) the Haystack project — an attempt to build a UI for the semantic web. It was built on top of the Eclipse IDE, and focused on personal information management and bioinformatics as its two domains. Each semantic data type (think IRI) was mapped to a program written in a custom language called Adenine, that rendered a UI specific to that type. Adenine’s syntax was itself a subset of RDF, so you could write it in N3. It was a cool vision, but never came to fruition.
Ever since then, semantic web (or SemWeb) is something I've thought about a lot. This is very relevant to my role as CTO at TetraScience because our platform is dedicated to collecting, centralizing, harmonizing, and preparing R&D lab data for exploration and analysis with techniques like machine learning and data science. Ontologies, metadata, and formatting are all critical to making data accessible and actionable (aka useful). While we each have our own individual opinions about the future and practicality of the semantic web, our goal as a company, and my responsibility as the CTO, is to ensure we achieve the end goal of accessible/actionable data, using the best means possible.
Here is a collection of thought leadership articles about semantic web that I'm tracking. This is a question we are asked often, so I thought I'd share.