Re: semsheets

Hi,

Under the W3C Community Group on Knowledge Graph Construction (https://w3id.org/kg-construct <https://w3id.org/kg-construct>), we are making the effort to collect all these tools/languages specifications/resources for performing these kinds of tasks (currently, it is mainly based on R2RML and its extensions but of course, it's open to any other tool). 

You should visit https://github.com/kg-construct/awesome-kgc-tools <https://github.com/kg-construct/awesome-kgc-tools> to have an overview of all of them, and we are open to receive updates/PR from anyone! Additionally, for more detailed information on each resource, you may also take a look at https://github.com/kg-construct/resources <https://github.com/kg-construct/resources> 

Best regards,
David

 <https://www.upm.es/>
David Chaves-Fraga
Postdoctoral Researcher
Escuela Técnica Superior de Ingenieros Informáticos
Ontology Engineering Group
Calle de Los Ciruelos S/N.
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✉ david.chaves@upm.es <mailto:david.chaves@upm.es>
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Aviso / Disclaimer <https://www.upm.es/disclaimer> 🌳 🌳 Piensa antes de imprimir.

> On 23 Feb 2022, at 12:27, Martynas Jusevičius <martynas@atomgraph.com> wrote:
> 
> Hi,
> 
> For CSV, in addition to TARQL there's also CSV2RDF which uses a
> slightly different processing model and query forms:
> https://github.com/AtomGraph/CSV2RDF
> 
> For XML, definitely XSLT, version 3.0 if it's available to you. With
> it you can even do streaming transformations, which is pretty much
> impossible otherwise.
> 
> Martynas
> atomgraph.com
> 
> On Wed, Feb 23, 2022 at 12:22 PM Christian Chiarcos
> <christian.chiarcos@web.de> wrote:
>> 
>> Hi,
>> 
>> as far as CSV data is concerned, TARQL (https://tarql.github.io/) is a great tool as it allows you to do transformations with SPARQL, and whatever relational data you have, it can be trivially exported to CSV. In that case, no specific standard (other than SPARQL) needed.
>> 
>> For tree/XML, I guess most people just resort to XSL. It is possible, of course, to use a generic XSL template to just encode the XML data model in RDF and then run SPARQL updates over that. But this isn't ideal because the raw RDF dump is too raw, so I guess we won't have a fully generic alternative to resource-specific XSL scripts any time soon.
>> 
>> For tree/JSON, JSON-LD contexts are more or less what you're asking for. Wrt. XML conversion, you can also convert XML to JSON and then provide the contexts.
>> 
>> For plain text, there are some extractor frameworks, but an easy stylesheet isn't feasible, as you need to configure language-specific processing modules.
>> 
>> NB: We are currently in the process of bundling a number of converter frameworks and subsequent SPARQL transformations into compact workflows, see https://github.com/Pret-a-LLOD/Fintan (still in progress, final release by end of June this year). Our specific goal is to apply this to data in NLP, but general-purpose converters are included as well, so you can at least run the XSL+SPARQL and TARQL/CSV+SPARQL transformations.
>> 
>> Best,
>> Christian
>> 
>> Am Mi., 23. Feb. 2022 um 08:10 Uhr schrieb Hans-Jürgen Rennau <hjrennau@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/
>