Tag Archives: API

GSTAR web services; now with added GeoJSON

Archaeogeomancy: Digital Heritage Specialists – archaeological geomatics – the majick of spatial data in archaeology – archaeological information systems for the digital age:

"A boundary is an array of an array of an array of arrays" by Paul Downey

“A boundary is an array of an array of an array of arrays” by Paul Downey

Following on from the last update concerning the GSTAR web services, the final pieces of infrastructure for the case studies and demonstrator are nearly complete. Building on the API, a GeoJSON output format has been added so that results from GeoSPARQL queries can a) be accessed via a simple URL as with all other outputs and b) visualised using a web map or indeed any platform which can consume GeoJSON. 

I had assumed this last element would be straightforward, after all, plotting results on a map is just one of those things one would expect from some geospatial resource. But a couple of hurdles presented themselves.

1. Well Known Text

Geospatial data modelled using the GeoSPARQL ontology and stored in a triple store such as Parliament typically makes use of either Well Known Text (WKT) or Geographic Markup Language (GML) to store geometries. Importantly, as per the GeoSPARQL standard there is the ability to include a URI for a Coordinate Reference System (CRS) within a geo:wktLiteral node:

Req 10: All RDFS Literals of type geo:wktLiteral shall consist of an optional URI identifying the coordinate reference system followed by Simple Features Well Known Text (WKT) describing a geometric value. Valid geo:wktLiterals are formed by concatenating a valid, absolute URI as defined in [RFC 2396], one or more spaces (Unicode U+0020 character) as a separator, and a WKT string as defined in Simple
Features [ISO 19125-1].

If using any of the standard outputs from Parliament via Jena using a SPARQL endpoint, the output includes the data as stored and (as was politely pointed out to me by a couple of eminent GeoJSON folks) embedding WKT within JSON structures is not really the done thing:

Consider me slapped. But the triple store is doing exactly as asked, outputting a JSON version of the query results, whatever form they may be in. So I needed an extra step to produce a proper GeoJSON output in which geometries are represented as JSON arrays rather than WKT.

This inclusion of a CRS URI element in a geo:wktLiteral node is problematic for systems expecting a plain old WKT string in which the first element is the geometry type. The overall node structure of a feature geometry when represented in RDF is as follows, comprising the three elements: CRS, WKT + Datatype.

"<http://www.opengis.net/def/crs/EPSG/0/4326> Point(33.95 -83.38)"^^<http://www.opengis.net/ont/geosparql#wktLiteral>

The final element here is the datatype, recorded using the standard ^^<datatype> notation, as generally used for typed literals; this is handled easily and becomes a datatype node in XML and JSON output formats. As such, this element is not a problem when appended to a WKT string.

{ "datatype": "http://www.opengis.net/ont/geosparql#wktLiteral" , "type": "typed-literal", "value" : "<http://www.opengis.net/def/crs/EPSG/0/4326> Point(33.95 -83.38)"}

More generally speaking, it has been noted by the research community (for example by a number of contributors to the Linked Geosptial Data event I attended) that this compound approach is unhelpful and somewhat at odds with the usual approach to semantic structures in which each assertion is represented as a discrete triple. But currently, this is what we have, so that’s that.

Anyway, the solution was actually rather low tech. One of the only Triple Stores to natively support GeoJSON output is Strabon, but the Triple Store selected for use in the GSTAR project is Parliament. So it was necessary to investigate suitable approaches using the platforms in use. A quick look at the Strabon source code (available online under the Mozilla Public License v2.0) revealed an elegantly simple solution. Taking the same example used above, it is clear that there is a pattern to the structure which, with some judicious use of basic Java string functions, can be used to clean up the string and extract the individual components.

Firstly, the EPSG code for the CRS can be extracted by first checking to see if the string begins with a < character, indicating there is a URI present. If so, the EPSG code will be the last element of the URI, appended to the base URI for the namespace. Secondly, the WKT serialisation itself will follow the closing > for the CRS URI tag. These marker elements used to get indices used for substrings are shown in green, the EPSG code shown in blue and the WKT geometry shown in red.

<http://www.opengis.net/def/crs/EPSG/0/4326> Point(33.95 -83.38)

So this gives a nice plain WKT string (the red bit) which can be processed using GeoTools with the added benefit of a Proj4 Coordinate Reference System (derived from the blue bit) which can be used to control any transformations. If there is no CRS element, the input string can be safely returned as is.

2. Generating GeoJSON output

Having resolved the WKT issue, the only remaining hurdle was to take the processed WKT geometries and output JSON coordinate arrays within a GeoJSON structure, as per the GeoJSON standard. This was accomplished using Jackson to manipulate the JSON data combined with geojson-jackson to fuse the JSON and GeoJSON elements. This made it relatively easy to take the Query Results Json Format data and transform it into GeoJSON.

This extra output format has now been added to the Sparqlr API so GeoJSON can be returned for the results of any query containing spatial data.

Results

A final check was to ensure the GeoJSON data is well formed using a suitable viewer, in this case QGIS which has good support for a wide range of OGC standard formats including GeoJSON.

GeoJSON output from Parliament via the Sparqlr API, viewed in QGIS

GeoJSON output from Parliament via the Sparqlr API, viewed in QGIS

Next steps

The final pieces of the puzzle are the demonstrator interface and case study queries showing the capabilities of such resources. The former comprises a web based interface including some Seneschal widgets (for selecting controlled vocabulary items to be used in queries) combined with a web map for visualising results and making spatial selections. The latter comprises some interesting prebuilt GeoSPARQL queries based on real world archaeological research questions, visualised using the same web based UI.

Then just need to finish off that thesis…

The post GSTAR web services; now with added GeoJSON appeared first on Archaeogeomancy: Digital Heritage Specialists.

GSTAR Web Services

Archaeogeomancy: Digital Heritage Specialists – archaeological geomatics – the majick of spatial data in archaeology – archaeological information systems for the digital age:

Web by David Reid

Web by David Reid

With all the source data prepped and ready to go, the next step is to build some demonstrators to show how such geosemantic resources can be used in practice. Whilst very powerful, a Sparql endpoint is not the most friendly way of interacting with data resources, especially from within a web based application where options for programming are a bit limited. There is still quite some debate on this topic which will be covered in more detail in the thesis (watch this space; still on track for submission 1st/2nd quarter 2016!) but the approach I have opted for is an API using web services to provide a range of outputs via a combination of URLs and parameters.

API vs Endpoint

The API is currently being finalised but the initial tests are working well, happily providing a range of outputs from the triple store. This approach allows the web service backend to draw on all the resources needed to handle geosemantic and respond to a range of requests in a form readily digestable by an xHTML+Javascript web application, including mapping. From a geospatial perspective, it means geospatial data can be requested from the webservice in a form ready to be mapped (eg JSON) or used in map popups (eg HTML) rather than having to process large piles of RDF within the browser. It also takes advantage of browser cacheing for the URL based resources, dramatically improving performance by reducing the need for trips to the server to get data.

SPARQLr – the GSTAR web service

Sparklers by Derek Key

Sparklers by Derek Key

The Sparqlr web service which implements the API is a RESTful service and is being built using Jersey which is a great platform for such tasks. This talks to the Parliament triple store via Jena with some Geotools components added to handle spatial data. As the service runs as a Java application on a GlassFish web server, it is possible to make use of the full range of Java tools out there without being limited to what can be achieved within a web browser. And thankfully, much of the code produced previously for the GSTAR Pilot is being recycled! As usual, all development is being undertaken using Eclipse+Maven.

Various queries can be performed in this way, some using basic URL syntax eg http://gstar:8080/sparqlr/api/features to return records about excavated features from archaeological archives as an RDF graph (default) or http://gstar:8080/sparqlr/api/artefacts/ntriple to return records about archaeological objects from museum collections as N-Triples. Parameters are also implemented which can be used to return particular records (eg http://gstar:8080/sparqlr/api/sites?MonUID=MWI11909 to return records about some pits near Stonehenge).

On the geosemantic front, parameters are also being used to pass in geometries as UTF-8 encoded WKT strings to facilitate spatial searches with the incoming WKT geometries used within the web service to add Geosparql filters to Sparql queries (eg http://gstar:8080/sparqlr/api/sites/within?polygon=POLYGON+%28%28569186.11565982+169502.18457639%2C+569186.02731245+169502.23116132%2C+569185.82348375+169502.25234642%2C+569185.70491406+169502.19113299%2C+569185.57672168+169502.04343594%2C+569185.54491719+169501.88381892%2C+569185.64107717+169501.66842781%2C+569185.82308162+169501.55315212%2C+569186.01894577+169501.56512577%2C+569186.19385893+169501.68723228%2C+569186.29291775+169501.91384472%2C+569186.25804717+169502.07848985%2C+569186.11565982+169502.18457639%29%29 to return all sites/monuments within a specified region such as a user generated polygon drawn on a web map).

The bulk of this is now up and running with the next step being to build the web application. This will involve the construction of a web map using OpenLayers to present results and facilitate user input (eg to capture polygonal search areas or points with buffer distances; the kind of spatial searches typically used within web based GIS).

The post GSTAR Web Services appeared first on Archaeogeomancy: Digital Heritage Specialists.

Geosemantics; the story so far

Archaeogeomancy: Digital Heritage Specialists – archaeological geomatics – the majick of spatial data in archaeology – archaeological information systems for the digital age:

Semantic Web Rubik's Cube by dullhunk

Semantic Web Rubik’s Cube by dullhunk

Into the second month of the PhD now and things are starting to coalesce and take shape. A framework for development, testing and deployment of proposed demonstrators is emerging and I’m making good headway demystifying the world of geosemantics (at least, it’s becoming clearer in my head!).

So, as well as continuing with the literature review, I’m knitting together a whole bunch of tools:

  • Java Development Kit (JDK) – the programming language at the heart of it all
  • Maven – a project management and comprehension tool
  • Eclipse – open development platform
  • Jena – a Java framework for building Semantic Web applications
  • Oracle 11g – relational Database Management System (RDBMS) with Spatial and Semantic components
  • D2RQ – a system for accessing relational databases as virtual, read-only RDF graphs.
  • AllegroGraph – a graph database
  • Prolog – logic programming
  • Protégé – ontology editor and knowledge-base framework
  • GeoSPARQL – query language for geospatial data stored as RDF
  • ArcGIS – Geographic Information System for data preparation, processing, etc
  • GeoServer – open source GIS server written in Java that allows users to share and edit geospatial data.

I’ll be posting more along the journey. Next steps will be to complete the literature review, submit stage reports and use some real archaeological data. Exciting stuff!

The post Geosemantics; the story so far appeared first on Archaeogeomancy: Digital Heritage Specialists.