SPARQLKit
An implementation of the SPARQL 1.1 Query and Update language in Objective-C.
This code implements a full SPARQL 1.1 Query and Update engine in Objective-C. The design is based on trait/role-based programming, where possible allowing for natural extensibility and component selection/replacement (e.g. using the Raptor RDF parser and a triple-store backed by the OS X Address Book).
The code depends on the GTWSWBase framework.
Plugins
The system provides an extensible plugin architecture for data sources and RDF parsers.
Plugins are automatically loaded from the Library/Application Support/SPARQLKit/PlugIns directory.
Some example plugins include:
- GTWSPARQLProtocolStore provides triplestore access to remote remote data using the SPARQL Protocol
- GTWRedland provides both a librdf in-memory triplestore and a Raptor RDF parser
- GTWAddressBookTripleStore provides access to a users address book contacts
- GTWApertureTripleStore provides access to photo metadata (including geographic and depiction data) from Aperture libraries
- GTWAOF provides a persistent, append-only quad store
Example
The gtwsparql tool available in this package provides a command line interface to a
full SPARQL 1.1 Query and Update environment.
Loading Data
% gtwsparql
sparql> LOAD <http://dbpedia.org/data/Objective-C.ttl> ;
OK
sparql> SELECT (COUNT(*) AS ?count) WHERE { ?s ?p ?o }
-------------
| # | count |
-------------
| 1 | 372 |
-------------
sparql> LOAD <http://dbpedia.org/data/SPARQL.ttl> INTO GRAPH <http://example.org/SPARQL> ;
OK
sparql> SELECT * WHERE { GRAPH ?g {} }
-----------------------------------
| # | g |
-----------------------------------
| 1 | <http://example.org/SPARQL> |
-----------------------------------
sparql> SELECT DISTINCT ?subject WHERE { GRAPH <http://example.org/SPARQL> { ?subject ?p ?o } } ORDER BY ?subject
-----------------------------------------------------------------------------
| # | subject |
-----------------------------------------------------------------------------
| 1 | <http://dbpedia.org/resource/SPARQL> |
| 2 | <http://fa.dbpedia.org/resource/اسپارکل> |
| 3 | <http://zh.dbpedia.org/resource/SPARQL> |
| 4 | <http://de.dbpedia.org/resource/SPARQL> |
| 5 | <http://dbpedia.org/resource/SPARQL_Protocol_and_RDF_Query_Language> |
| 6 | <http://ar.dbpedia.org/resource/سباركل> |
| 7 | <http://ru.dbpedia.org/resource/SPARQL> |
| 8 | <http://dbpedia.org/resource/Sparq> |
| 9 | <http://lv.dbpedia.org/resource/SPARQL> |
| 10 | <http://vi.dbpedia.org/resource/SPARQL> |
| 11 | <http://nl.dbpedia.org/resource/SPARQL> |
| 12 | <http://uk.dbpedia.org/resource/SPARQL> |
| 13 | <http://ja.dbpedia.org/resource/SPARQL> |
| 14 | <http://dbpedia.org/resource/Sparql> |
| 15 | <http://it.dbpedia.org/resource/SPARQL> |
| 16 | <http://hu.dbpedia.org/resource/Sparql> |
| 17 | <http://wikidata.dbpedia.org/resource/Q54871> |
| 18 | <http://en.wikipedia.org/wiki/SPARQL> |
| 19 | <http://pl.dbpedia.org/resource/SPARQL> |
| 20 | <http://fr.dbpedia.org/resource/SPARQL> |
| 21 | <http://es.dbpedia.org/resource/SPARQL> |
-----------------------------------------------------------------------------
Namespace Completion
The tool can auto-complete prefix declarations (sourced from prefix.cc. By hitting TAB immediately after a prefix name (including colon), the full prefix IRI is added to the query string:
sparql> PREFIX foaf:<TAB>
sparql> PREFIX foaf: <http://xmlns.com/foaf/0.1/>
Configuring the Data Source
The gtwsparql tool can take a string argument to specify the data source configuration.
In its simplest form, this is just the name of a triple- or quad-store plugin.
For example, we can query over Aperture photo metadata loaded into the default graph:
% gtwsparql -s GTWApertureTripleStore
sparql> PREFIX dcterms: <http://purl.org/dc/terms/> PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?place (SAMPLE(?i) AS ?image) WHERE { ?i dcterms:spatial [ foaf:name ?place ] FILTER(REGEX(?place, "Airport")) } GROUP BY ?place ORDER BY ?place
-----------------------------------------------------------------------------------------------------------------------------------------------------
| # | place | image |
-----------------------------------------------------------------------------------------------------------------------------------------------------
| 1 | "Anchorage Airport" | <file:///Users/greg/Pictures/Aperture Library.aplibrary/Masters/2013/03/27/20130327-000128/P1040654.RW2> |
| 2 | "Cape Town Airport" | <file:///Users/greg/Pictures/Aperture Library.aplibrary/Masters/2013/07/04/20130704-222928/IMG_1931.JPG> |
| 3 | "Genoa Cristoforo Colombo Airport" | <file:///Users/greg/Pictures/Aperture Library.aplibrary/Masters/2013/07/04/20130704-222928/IMG_1796.JPG> |
| 4 | "Indira Gandhi Airport" | <file:///Users/greg/Pictures/Aperture Library.aplibrary/Masters/2013/05/22/20130522-235054/IMG_1752.JPG> |
| 5 | "Or Tambo Airport" | <file:///Users/greg/Pictures/Aperture Library.aplibrary/Masters/2013/07/04/20130704-222928/IMG_1924.JPG> |
| 6 | "Vadodara Airport" | <file:///Users/greg/Pictures/Aperture Library.aplibrary/Masters/2013/05/22/20130522-235054/IMG_1762.JPG> |
| 7 | "Wellington Airport" | <file:///Users/greg/Pictures/Aperture Library.aplibrary/Masters/2013/04/10/20130410-213038/P1070371.RW2> |
-----------------------------------------------------------------------------------------------------------------------------------------------------
The SPKTripleModel can be used to construct a dataset with multiple triplestores, each available in a separate graph.
We can query over both Aperture photo metadata and address book contacts:
% gtwsparql -s '{ "storetype": "SPKTripleModel", "graphs": { "tag:addressbook": { "storetype": "GTWAddressBookTripleStore" }, "tag:aperture": { "storetype": "GTWApertureTripleStore" } } }'
sparql> SELECT * WHERE { GRAPH ?g {} }
-------------------------
| # | g |
-------------------------
| 1 | <tag:addressbook> |
| 2 | <tag:aperture> |
-------------------------
This allows us to find the number of photos depicting members of the same family by combining depiction data from Aperture with family name data from the address book (by constructing a query dataset using the FROM keyword):
sparql> PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?family (COUNT(*) AS ?count) FROM <tag:addressbook> FROM <tag:aperture> WHERE { ?image a foaf:Image ; foaf:depicts [ foaf:familyName ?family ] } GROUP BY ?family ORDER BY ?count
----------------------------------
| # | count | family |
----------------------------------
| 1 | 1 | "Kjernsmo" |
| 2 | 6 | "Heath" |
| 3 | 14 | "Brickley" |
| 4 | 25 | "Aastrand Grimnes" |
| 5 | 104 | "Acton" |
| 6 | 116 | "Gillis" |
| 7 | 504 | "Crawford" |
| 8 | 2029 | "Williams" |
----------------------------------
Starting an Endpoint
A SPARQL endpoint can easily be started:
sparql> endpoint 8080
Endpoint started on port 8080
At this point, http://localhost:8080/sparql is a SPARQL Protocol endpoint URL that will respond to queries.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent