Re: grlc turns your Linked Data queries into Linked Data APIs

On 1/30/17 4:37 PM, Andreas Harth wrote:
> Hi Pieter,
>
> interesting ideas!
>
> I just wanted to add Linked Data-Fu to the list, which allows to
> specify link traversals in a Notation3 syntax in combination with
> a SPARQL query processor.
>
> We'll run a tutorial about the system and related ideas at ESWC [2].
>
> Cheers,
> Andreas.
>
> [1] https://linked-data-fu.github.io/
> [2] http://harth.org/andreas/2016/eswc-tut/
>

Hi Andreas,

Do you not have a live demo anywhere?


Kingsley
> On 01/26/17 16:13, Pieter Colpaert wrote:
>> Hi Albert,
>>
>> Nice work! With The DataTank [1] we also released a similar feature back
>> in 2012 that takes SPARQL templates at its input, and describes its
>> output using DCAT-AP, the right HTTP headers for e.g., caching, and
>> supports content negotiation. Next to also BASIL, also LimeDS [2]
>> provides similar functionality, as a data adapter connecting various
>> interfaces using a visual interface.
>>
>> I like these kinds of frameworks as they bridge the gap between
>> publishing data as interoperable as possible – for maximum reuse – and
>> front-end developers that want an app on top of a number of triples.
>> They form an abstraction layer which can be used by front-end developers
>> to quickly create a UI on top of data without having the take into
>> account an open world assumption. Such frameworks are great tools for
>> digital signage providers [3] and similar type of reuse that needs
>> simple views, to take away some of the processing from a low-end device.
>>
>> To that extent, I would find it interesting if in the same way we could
>> create an abstraction framework for more complex user agents. E.g., user
>> agents that combine different data sources by crawling Linked Data using
>> LDQL [4], the Linked Data Fragments client [5] or for the Linked
>> Connections client for public transit route planning[6]. While when the
>> caches of these type of user agents are cold, an end-user might have to
>> wait some time for an answer, when the caches are hot – not unthinkable
>> when all your end-users are asking very similar questions – results are
>> probably going to be very fast.
>>
>> Kind regards,
>>
>> Pieter
>>
>> [1] https://github.com/tdt/core
>>
>> [2] http://limeds.be/
>>
>> [3] Back in 2012, I introduced The DataTank at this company and it did
>> this trick well: https://flatturtle.com
>>
>> [4] http://olafhartig.de/files/HartigPerezLDQL_JWSPreprint.pdf
>>
>> [5] http://client.linkeddatafragments.org/
>>
>> [6] http://linkedconnections.org
>>
>> On 26-01-17 13:58, Albert Meroño Peñuela wrote:
>>> Hi all,
>>>
>>> Just letting you know that there is a public instance of grlc
>>> available at [1]. No more hard-coded queries in your Linked Data
>>> consuming applications!
>>>
>>> grlc [5], inspired by tools like BASIL [4], is a small server that
>>> converts your SPARQL queries into Linked Data APIs, automatically and
>>> on the fly. To do this, it assumes that your SPARQL queries are
>>> publicly available in a GitHub (or similar) repository. For example,
>>> queries stored in https://github.com/CLARIAH/wp4-queries have their
>>> equivalent API at http://grlc.io/api/CLARIAH/wp4-queries/api-docs
>>> (notice the user and repository names in the URIs). You can call API
>>> endpoints by e.g. http://grlc.io/api/CLARIAH/wp4-queries/datasets
>>>
>>> Full details are described in this paper [2].
>>>
>>> The latest additions include a docker-based deployment, parameter
>>> enumerations, result pagination, and compatibility with #LD servers,
>>> RDF dumps, and HTML+RDFa pages (besides SPARQL endpoints).
>>>
>>> We would be pleased to hear from your experiences on using grlc: bugs,
>>> performance, use cases, feature requests, etc. grlc's issue tracker
>>> can be found at [3].
>>>
>>> Thanks,
>>> Albert
>>>
>>> [1] http://grlc.io
>>> [2]
>>> https://www.albertmeronyo.org/wp-content/uploads/2016/04/SALAD2016_paper_4.pdf
>>>
>>>
>>> [3] https://github.com/CLARIAH/grlc/issues
>>> [4] http://basil.kmi.open.ac.uk/app/#/collection
>>> [5] https://github.com/CLARIAH/grlc
>>
>
>
>


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