Hi Arnold and everyone, creator of m-ld here. Thanks for the shout.
I’m coming at this topic from the point of view of a couple of decades in scientific data management – where sophisticated knowledge management, of the kind that may be possible with Linked Data, could provide a huge boost to scientific productivity. We developed a data-linking approach in parallel (ish) with the early days of RDF, which gave us an edge in the market when it came to search, workflows, and reporting. In the end we never transitioned to RDF (though our system was within a hairs-breadth of a 1:1 conceptual mapping), despite many years of championing on my part.
Why?
To cut a long story short, it’s because we didn’t realise we needed it until we had already entrenched our own approach.
I submit to the panel that this is a common problem. I want to build a (social) app to meet a pressing customer need. I take a platform off the shelf and hack together a prototype. I probably have JSON as both a serialisation between distributed components and a readable way to communicate between humans. My prototype is well-received and I get a hundred stories to take me to MVP. Along the way, some suspiciously tricky requirements arise: like internal and external cross-links, a faceted search UI, custom fields. Each of these is addressed with increasingly complex (and, I will stress, fun to invent) solutions involving metadata and query APIs. At no point in this path (or indeed, in the decades to follow) is there any breathing room to take a hatchet to all these custom solutions.
Today I find myself building a software library that will help developers to solve another, parallel, hard problem, which is sharing of live state information allowing multiple concurrent editors. RDF data structures are not easy to make live-sharable (article), but I’ve based m-ld on RDF for the natural extensibility (link to paper). I also know that when m-ld is used in real apps, linked data principles are going to be needed, and they’ll give m-ld an edge in an increasingly competitive space.
PS
That’s the plan . I’m not actually trying to be a lite version of LD. I use LD as my base data representation.
The main place where I may appear to be inventing standard 15 is with json-rql, which is conceptually a mid-point between GraphQL and SPARQL. However in reality it’s just a serialisation for SPARQL, with a lower barrier to entry. Happy to talk more about that, of course.