![]() ![]() Most of them had, at best, mixed success, and several have been abject failures that have since been superseded by other technologies. Use Case Failures. I've been involved in a number of semantics projects over the years. Since there are a great number of operations where sequencing is in fact very important, this limitation is a significant one, and in a world where object databases (which support arrays or sequences) are increasingly the norm, there are many analytics-related activities that simply cannot be done on the current crop of knowledge bases. It is possible to create extrinsic ordering by creating a linked list, but because path traversal order is not in fact uniformly respected, retaining this via SPARQL is not guaranteed. Lack of Intrinsic Sequencing. RDF works upon the (admittedly valid) assumption that in a graph there is no intrinsic ordering. Without that use case, though, many of the benefits of RDF fall by the wayside. Moreover, with SPARQL, the need for intrinsic inferencing dropped fairly dramatically. However, in practice, many complex models have foundered because inheritance was made too complicated or the models failed to take into account temporal complexities. Inferencing, which involves the ability to use aspects of the model itself to surface new information, can make for some very potent applications, but only if the model itself is navigable in the same way as other information, and only if the model is designed to make such inferences easily. Inference an Edge Case. One of the most powerful aspects of RDF, at least as far as proponents of the technology would have it, is its ability to be used for logical inferencing. Add into that configuring triple store graphs can be a logistical nightmare and the likelihood that most programmers - let alone data analysts - would have encountered RDF drops dramatically. in computational linguistics, RDF is not hard to understand, but if you have a two-year certificate in programming JavaScript or Python, chances are pretty good that RDF's graph model is incomprehensible. Too Complex. It took me a few years to really grok how RDF worked, in part because it assumed that people would be able to understand the graph paradigm and logical inferencing models. The Semantic Web Is In Troubleīefore getting a lot of brickbats from colleagues in the community about this particular assertion, I want to lay out some of my own observations about where and why I believe the Semantic Web is currently in trouble: Instead, as the headline suggests, I think that the king of the hill will likely end up being GraphQL. I'm not talking about Neo4J's Cypher (which in its open incarnation is intriguing), or GQL, TigerGraph's SQL-like language intended to bring SQL syntax to graph querying. I like SPARQL, but increasingly I have to admit a hard reality: there's a new kid on the block that I think may very well dethrone the language, and perhaps even RDF. ![]() ![]() I remember working through the complexities of RDFS and OWL, spending a long afternoon with one of the editors of the SPARQL specification in 2007, promoting SPARQL 1.1 and SHACL in the mid-2010s, and watching as the technology went from being an outlier to having its moment in the sun just before COVID-19 hit. I'm relatively old school, semantically speaking: my first encounters with RDF was in the early 2000s, not long after Tim Berners-Lee's now-famous article in Scientific American introducing the Semantic Web to the world. ![]()
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