As well as providing data through existing online portals (e.g. the LRIS Portal, Manaaki Whenua’s national land information portal, and OurEnvironment, Manaaki Whenua’s online land atlas of New Zealand), data were made accessible via open standards-based web data services (APIs) including experimental services that used emerging standards, e.g. the OGC WFS 3.0.
The programme also looked at novel ways to visualise data to communicate about state and trend, uncertainty, and data provenance using infographics, interactive visualisation tools, and ‘story' maps.
Land Use
Within the IDA programme, a set of infographics and geovisualisation tools has been created that help users better understand land resource data and explore spatio-temporal changes for land resource data at a variety of scales and soil data uncertainty. These visualisation products are viewable online at http://vizdemo.landcareresearch.co.nz/.
Two interactive visualization tools were designed and implemented to help visualise data provenance data created by pyluc and LUMASS. ‘Provis’, a web-based tool utilising the ‘D3’ JavaScript library, is capable of visualising very data large provenance files in a way that makes them easier for modellers and researchers to understand.
Soil Quality
Using a number of extant data sources, IDA created a well-documented, nationally meaningful soil quality dataset of clear provenance. We undertook a major data validation exercise manually checking each data entry, cross-checking with lab sheet information, and dealing with legacy data collection and management issues such as inconsistent coding of properties across records. These data were added to Manaaki Whenua's National Soil Data Repository (NSDR). However, because of data privacy and ownership issues we are unable to make most of these data publicly available.
IDA staff led an Open Geospatial Consortium (OGC) interoperabilty experiment, the Soil Data Interoperability Experiment (SoilIE) researching the development and testing of a global Soil Markup Language by which data can be shared between soil information systems. This was achieved by harmonizing and advancing existing standards initiatives such as ISO28258 SoilML, the EU-INSPIRE soil data specification, eSoterML, ANZSoilML, and others. The SoilIE set the stage for an OGC candidate soil data model and encoding standard. A soil-encoding standard is required for the exchange of soil feature data, including data about soil bodies, profiles, horizons, and related entities. A standard is also required as a reference for soil observations, as these features typically host the properties that are observed. This work impacted on the work of Pillar 4 (Global Soil Information System) and Pillar 5 (Harmonization) of the FAO Global Soil Partnership.
Demonstration of provision of soil sensor data as TimeSeriesML - from OGC SoilIE
Biodiversity
IDA designed and implemented an R-Shiny app that draws on integrated species-occurrence biodata developed in our data federation work. The app allows the exploration of variability in selected species distributions according to spatial granularity size (10, 25, 50, and 100 km grids), time-slices of primary occurrence data, and taxonomic resolution.
As an example application, we developed an R-Shiny web application prototype to interactively visualise indigenous myrtaceae species occurrence in response to the sudden incursion of myrtle rust in May 2017.
New Zealand species occurrence data are now available for download, with visualisation and modelling through several GBIF and Australian Living Atlas websites.
Observation counts of myrtle trees in New Zealand
Access to these demo apps is password protected due to data licence restrictions. Please contact the IDA Programme leader to determine if you can gain access to the tools.