- From: Hans-Jürgen Rennau <hjrennau@gmail.com>
- Date: Wed, 23 Feb 2022 08:10:26 +0100
- To: semantic-web@w3.org
- Message-ID: <CA+H2zTA+8d4sA0mxO-8bGugUQPg-PGmkH1aVeo7vPbz8DuLf=A@mail.gmail.com>
Hello, I am interested in the transformation of non-RDF data into RDF data and I am puzzled, nay, haunted by a simple analogy. We have stylesheets for defining visual representation of data in a convenient, standardized way. Could we not have "semsheets" for defining semantic representation of data in a convenient, standardized way? I admit the oversimplification: CSS stylesheets are designed to work with HTML, a scope sufficient for practical purposes. Whereas "non-RDF data" is by definition a broad spectrum of media types, so the uniformity of a single "semsheet language" may not be attainable. But how about approaching the goal, based on an appropriate partitioning of data sources? For example: (1) Relational data (2) Tree-structured data (3) Other Tree-structured data comprises most structured data except for graph data - JSON, XML, HTML, CSV, .... And concerning "other", what comes to my mind is (i) unstructured text and (ii) non-RDF graph data. So keeping this partitioning in mind, how about standards, frameworks, tools enabling customized mapping of data to RDF? What I am aware of is very little: (1) relational data: R2RML [1], ? (2) tree-structured data: RML [2], ? (3) other: ? Note that I did not mention RDFa, as it is about embedding, rather than writing mapping documents, nor GRDDL, as it is about finding a mapping document, not its content. I am convinced that there are quite a few other standards, frameworks and tools which should be listed above, replacing the "?". Can you help me to find them? Any links, thoughts, comments highly appreciated. (And should you think the partitioning is faulty, please share your criticism. The same applies to the very quest for common, standardized mapping languages.) Thank you! With kind regards, Hans-Jürgen Rennau [1] https://www.w3.org/TR/r2rml/ [2] https://rml.io/specs/rml/
Received on Wednesday, 23 February 2022 10:12:15 UTC