Nicholas J. Car

Towards Linked Data Conventions for Delivery of Environmental Data Using netCDF

netCDF is a well-known and widely used format to exchange array-oriented scientific data such as grids and time-series. We describe a new convention for encoding netCDF based on Linked Data principles called netCDF-LD. netCDF-LD allows metadata elements, given as string values in current netCDF files, to be given as Linked Data objects. netCDF-LD allows precise semantics to be used for elements and expands the type options beyond lists of controlled terms. Using Uniform Resource Identifiers (URIs) for elements allows them to refer to other Linked Data resources for their type and descriptions. This enables improved data discovery through a generic mechanism for element type identification and adds element type expandability to new Linked Data resources as they become available. By following patterns already established for extending existing formats, netCDF-LD applications can take advantage of existing software for processing Linked Data and supporting more effective data discovery and integration across systems.

A Best of Both Worlds Approach to Complex, Efficient, Time Series Data Delivery

Point time series are a key data-type for the description of real or modelled environmental phenomena. Delivering this data in useful ways can be challenging when the data volume is large, when computational work (such as aggregation, subsetting, or re-sampling) needs to be performed, or when complex metadata is needed to place data in context for understanding. Some aspects of these problems are especially relevant to the environmental domain: large sensor networks measuring continuous environmental phenomena sampling frequently over long periods of time generate very large datasets, and rich metadata is often required to understand the context of observations. Nevertheless, timeseries data, and most of these challenges, are prevalent beyond the environmental domain, for example in financial and industrial domains.

Implementing a Glossary and Vocabulary Service in an Interdisciplinary Environmental Assessment for Decision Makers

When delivering scientific information for decision makers, it is important to define and use appropriate terminology to ensure scientific credibility and good communication. A glossary with terms from authoritative sources for specific domains can increase the usefulness and reusability of information for decision makers as the information can be more easily used without adaptation or translation. Linked Data principles and semantic web-based vocabulary tools provide mechanisms for delivering formalised glossaries via vocabulary services for use in integrated products, both documents and information platforms.

A Cotton Irrigator’s Decision Support System and Benchmarking Tool Using National, Regional and Local Data

We are developing a smart phone application that provides irrigation water management advice using satellite imagery, weather stations and field-scale farmer provided data.

Joining the Dots: Using Linked Data to Navigate between Features and Observational Data

Information about localized phenomena may be represented in multiple ways. GIS systems may be used to record the spatial extent of the phenomena. Observations about the state of one or more properties of the phenomena are available from real-time sensors, models, or from archives. The relationships between these data sources, or specific features in different data products, cannot easily be specified. Additionally, features change over time, their representations use different spatial scales and different aspects of them are of concern to different stakeholders. This greatly increases the number of potential relationships between features. Thus, for a given feature we can expect that heterogeneous information systems will exist, holding different types of data related to that feature. We propose the use of Linked Data to describe the relationships between them. We demonstrate this in practice using the Australian Hydrologic Geospatial Fabric (Geofabric) feature dataset and observational data of varying forms, including time-series and discrete measurements. We describe how different resources, and different aspects and versions of them, can be discovered and accessed. A web client is described that can navigate between related resources, including using the Geofabric’s feature relationships, to navigate from one observational dataset to another related by hydrological connectivity.

USING decision models to enable better irrigation Decision Support Systems

Abstract Many attempts have been made to enhance irrigation decisions using Decision Support Systems (DSS). These have met with limited success for many reasons, one of which is well known: that DSS encode decision rules (waterbalances, financial models) narrower in scope than the criteria farmers really use to make decisions, thus their advice is of limited value or perhaps entirely irrelevant. To assist irrigation DSS designers build more flexible systems, we suggest they heed decision theory and decision modelling, separately from domain-specific DSS tasks. They may then find better ways of modelling real-world decisions which might allow for wider ranging sets of decision rules than previously. To facilitate this, we review three different decision modelling systems and with each model the seemingly straightforward irrigation decision “How much should I water today?”. In doing this we show how they can assist with wide-ranging rule integration. The systems we chose are: Decision Modelling Notation (DMN) from the business analysis community; the Decision Ontology (DO), a Semantic Web modelling system; and Decision Modelling Ontology (DMO) a formal ontology from Information Systems Engineering. We have determined that each of these modelling systems have useful aspects for irrigation DSS designers, which we list, but that they are not equally useful. Also, none of the systems provide designers with both the best modelling system and best technology & tools. We complete our work with a list of requirements for a future decision modelling system based on the intersection of the strengths of the systems investigated and our perceptions of irrigation DSS need. We believe a future system is possible to make and could serve irrigation DSS designers better than any current system. In future work, we indicate what steps might be taken with existing systems to evolve them in line with our future system requirements. Finally, we conclude with a summary of our findings.

netCDF-LD SKOS: Demonstrating Linked Data Vocabulary Use Within netCDF-Compliant Files

netCDF, the widely-used array-oriented data container file format, has previously been extended in an initiative called netCDF-LD, to include Linked Data metadata elements. In this paper, we build on that initiative with demonstrations of a Simple Knowledge Organization System (SKOS)-aware file format and associated tooling. First, we discuss a very simple way to reference SKOS vocabulary data stored online in netCDF files via Linked Data. Second, we describe our prototype ncskos tools, including ‘ncskosdump’, which wraps the well-known ‘ncdump’ tool used to print out netCDF headers and data. Our tools utilize some of the features of Linked Data and SKOS vocabularies to enhance the metadata of netCDF files by allowing: multilingual metadata label retrieval; alternate term name retrieval; and hierarchical vocabulary relationship navigation. In doing this, ncskosdump preserves the ncdump practice of writing output in standard CDL (network Common Data Language). For the demonstration of theses formats and tools, we relate how we have included URI links in netCDF files to SKOS concepts within a demonstration vocabulary and how the ncskos tools can be used to manage these files in ways that are not possible using only regular netCDF metadata. We also discuss problems we perceived in scaling Linked Data functionality when applying it to large numbers of netCDF files or in multiple file management sessions, and how we have catered for these. Finally, we indicate some future work in the area of more comprehensive Linked Data representation in netCDF files.

Mobile Field Data Collection for Post Bushfire Analysis and African Farmers

In recent years CSIRO has been trialling field data collection using mobile devices such as phones and tablets. Two recent tools that have been developed by CSIRO are the CSIRO Surveyor (Post Bushfire House Surveyor) and DroidFarmer. Challenges tackled include mapping field documents to mobile data through QR (Quick Response) codes, rapid input of survey data, accurate capture of GPS locations and offline operation. Throughout this paper we detail the design choices made for these systems. We give details of how well field data collection was performed and discuss our planned future developments in this space.