No abstract

Several modern development environments allow executable components, such as hydrologic models, to carry Metadata describing the properties and capabilities of the components. These metadata may be restricted to the names of properties, and their respective data types, or may extend to other information, such as classification of properties (eg. input or output), numeric constraints on parameters (eg. between 0 and 1, or greater than 0) or aliases (eg. rainfall, also known as precipitation). Introspection in these environments allows tool developers to write programs and other components that make use of these metadata to provide generic model processing tools, while allowing model developers to take advantage of these tools without additional development effort. Typical model processing tools include model integration systems, parameter optimisers, automatic user interface generation and automated IO. One approach to implementing model introspection and metadata, used by the Interactive Component Modelling System (ICMS), is to extract information from a model when compiling a custom modelling language. An alternate approach, being evaluated in a new framework, relies on the language independent introspection provided by the .NET environment. These uses of introspection streamline model development within modelling frameworks, reducing the effort required to take advantage of other framework capabilities, such as dynamic visualisation.

The environmental sciences are witnessing a data revolution as large amounts of data are being made available at an increasing rate. Many datasets are being published through operational monitoring programs, research activities and global earth observation virtual laboratories. An important aspect is the ability to query relevant metadata which can potentially provide useful information to discover, access and interpret environmental datasets, information about the data providers themselves, data services, data encodings, observation and measurement properties and data service endpoints. However, support for producing and accessing metadata descriptions in a flexible, extensible, easily integrated and easily discovered manner is lacking as current methods require interpreting multiple standards and formalisms. In this paper, we propose components to streamline discovery and access of hydrological and environmental data: a Data Provider Node ontology (DPN-O) which allows precise descriptions to be captured about datasets, data services and their interfaces; and a Data Brokering Layer which provides an Application Programming Interface (API) for registering metadata for discovery and query of registered DPN datasets. We discuss this work in the context of the eReefs project which is developing an integrated information platform for discovery and visualization of observational and modelled data of the Great Barrier Reef.

Global climate change and local development make water supply one of the most vulnerable sectors in Australia. The Australian government has therefore commissioned a series of projects to evaluate water availability and the sustainable use of water resources in Australia. This paper discusses a river system modelling platform that has been used in some of these nationally significant projects. The platform consists of three components: provenance, modelling engine and reporting database. The core component is the modelling engine, an agent-based hydrological simulation system called the Integrated River System Modelling Framework (IRSMF). All configuration information and inputs to IRSMF are recorded in the provenance component so that modelling processes can be reproduced and results audited. The reporting database is used to store key statistics and raw output time series data for selected key parameters. This river system modelling platform has for the first time modelled a river system at the basin level in Australia. It provides practitioners with a unique understanding of the characteristics and emergent behaviours of river systems at the basin level. Although the platform is purpose-built for the Murray-Darling Basin, it would be easy to apply it to other basins by using different river models to model agent behaviours.

Recent advances in environmental sensing, high-resolution satellite technology, advanced environmental modelling, information platforms, and virtual laboratories present significant opportunities for providing scientific communities and the general public with the ability to discover and gain insights into our ever-changing environment. However, barriers to realising the value of available environmental datasets exist, specifically, in the (lack of) streamlined access to datasets, and tooling to flexibly support the mash-up creation of various visualisations. In previous work, a Data Brokering Layer has been developed to support the streamlining of potentially heterogeneous access mechanisms and data formats. The Data Brokering Layer provides functionality to handle data queries and access to registered datasets and data services, where in the past, visualisation portals would have required ad-hoc code to handle access to each dataset individually, thus limiting the extensibility of such data portals further. Thus, the Data Brokering Layer provides a basis on which a library of visualisation and data discovery modules can be developed. Such visualisation and data discovery modules provide flexible, reusable and mashable components for exploring datasets multiple contexts across multiple domains. Examples of visualisation modules include data portals, embedded visualisation panels, and real-time reports. In this paper, we focus on the visualisation and data discovery capabilities developed in the context of the eReefs project which aim to provide an integrated information platform for discovery and visualisation of observational and modelled data of the Great Barrier Reef.