Technologies

Visualisation

Geo TaggingWe specialise in creating graphical representations of complex scientific data. Our work ranges from custom scientific visualisations to the production of charts and cartographic products for a general audience. Although we continue to produce high-quality print maps, increasingly we are focused on developing interactive visualisations delivered over the Internet. We try to present complex environmental data in an accessible graphical format to help people understand abstract concepts, reveal patterns and highlight outliers.

Oblique View

Grid and high performance computing

Landcare Research is a member of the BeSTGRID community, which provides High Performance Computing (HPC) resources to the BeSTGRID’s member institutes via the REANZ network. To provide uniform access across all BeSTGRID HPC resources, the Landcare Research Informatics team employs the BeSTGRID tools to give our staff access to SCENZ-Cluster.

The Informatics team manages SCENZ-Cluster as a resource for the SCENZ-Grid project on behalf of Landcare Research. Our cluster consists of 13 SGI Altix XE servers, and has in total 104 CPUs, 384 GB of RAM, and 3.5 TB of local storage, which gives an estimated maximum computational power of 1.15 TFLOPS (1.15 trillion Floating Point Operations Per Second). It runs the Rocks Cluster Linux distribution and works with most open-source applications that work from the Linux command line. We’ve had excellent progress with using R, JAGS, mrBayes, and a few other applications.

Remote sensing

We extract spatial environmental information from digital airborne and satellite data. Remote sensing uses sensors that either detect electromagnetic radiation reflected or emitted from ground targets or that detect reflected responses from objects that are irradiated from artificially-generated energy sources, such as radar and lidar.

The data gathered is then processed, using computer algorithms to convert the digital data to imagery and thence to information. Common image processing routines include feature extraction, pattern recognition, classification, projection, and signal analysis.

Our image information feeds , for example, into new soil mapping, into models run to better understand hydrological and nutrient cycling processes, into better ways to measure agricultural productivity, and into the LUCAS system – New Zealand’s land use and carbon reporting obligations under the Kyoto protocols.

Web Services

Scientists, policy makers, business and the public can reap huge benefits from being able to find, access and reuse biodiversity and land based environmental science data.

Finding data can be achieved through searching the web, specialist web sites e.g. www.data.govt.nz, or domain specific data catalogues, e.g. the LRIS portal or NZFUNGI – New Zealand Fungi. Getting access to the data is more complicated however. A user might need to contact the data holder directly or at the very least download the data from a web site.  Doing this requires the user to then manage the data and in some cases it may not be in a form they can directly use.  In such situations access to the data directly over the web may be a better option.  Using what are known as web services, a user could link to the data from their desktop software and incorporate it into their local applications and databases. Web services also allows software developers to develop new web-based applications that offer users novel extensions to the base data, e.g. to view the data as a map or as a summary of consistent data following some data merging operation.  The outputs from these web services can also be plugged together to build larger, more comprehensive services and applications thus allowing otherwise separate services to interoperate and data to be integrated.  Such services don’t have to be just about providing data or information, they can also be used to process or analyse data provided by other web services.

The W3C defines a “web service” as “a software system designed to support interoperable machine-to-machine interaction over a network”. Web services share business logic, data and processes through a programmatic interface across a network. Critically, applications using web services and web services working together require standardized ways of doing things, frequently using standards such as XML, SOAP, REST, and WSDL over an Internet protocol.  Web services normally have a standard way of communicating with other web services, including a named set of operations that characterise the behaviour of a web service, and how data should be structured. Web services reflect a new service-oriented architectural approach to building computer software, based on the notion of building applications by discovering and organising smaller more focused network-available web services into larger more powerful systems.

The Informatics team is a great believer in the value of web services for constructing service based systems to support science and business and the team is employing this service-oriented approach on a number of fronts.  For example, we are using Open Geospatial Consortium (OGC) Web Services Specifications to build a standards-based interoperable framework for web-based discovery, access, integration, analysis, exploitation and visualization of online geospatial data sources, sensor-derived information and geoprocessing capabilities.  By creating scientific workflows using OGC web services and other types of web services we can deploy analysis and modelling capabilities within scientific environments for use by Landcare scientists and others.

We are also using web services to deliver authoritative lists of Scientific Names for our Nationally Significant biological databases, e.g. NZFlora and NZFungi, and for harvesting biological data associated with individual specimens from biological collections around New Zealand.  In the near future these biological services will expand to encompass a consensus list of all organism names important to New Zealand and services to integrate data from throughout the country documenting the presence of invasive species that may threaten our national biodiversity and economy.

Other technologies we work with

  • Databases
  • Geospatial modelling
  • Semantics
  • Social media and social software

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