Ecology is a field of study in ecosystem science (Ecosystem Science Long-term Plan). It is studied from many perspectives (blue area), often in connection with allied fields (green zone), making it a transdisciplinary endeavour.
Ecological science involves integrating, analyzing, visualizing and collecting better information about plants, animals, microbes of different ecosystems, observing how they interact among themselves and the environments where they are co-located in nature. It also involves understanding and forecasting how our harvesting of the Australian environment affects are our social, economic and health well-being.
High value data
Data are the currency of science, policy, management and economic well-being. The numbers of any data analysis affect the quality of results, the reliability of environmental change forecasts and decision making and "garbage in, garbage out" is an apt cautionary adage. Eco-informatics aims to offer high value ecology data for its user base. Features of our data collection are:
|Essential measures: Our ecology data consists of in situ co-located species and environment (ecological attribute) data enable the 'how', 'why' and 'what if I do this' questions about both species-to-species and species-to-environment interactions scientists know are fundamental for understanding, forecasting and managing environmental change. 'Species data' include all land-based biota and 'environment data' are the ecological attributes recorded concurrently with the biota.
|Coverage: Widespread, large volumes of data for species and ecological attributes gathered through surveillance monitoring across Australia improves the accuracy, precision, uncertainty, consistency and appropriateness of analysis.
|Depth: Data supplied from long-term monitoring and detailed, localised experimental programs improve the veracity and validity of the 'what' and 'where' reporting.
|Integrity: Quality assured data curation by collaboration, secure systems operation for preservation, decommissioning arrangements with our hosting university give our data authenticity.|
|Transparency: We strive to achieve scientific quality and transparency in our metadata by doing detailed authoring (in collaboration with the data producers) on a number of threads. The sections are: (1) overview (title, author(s), scope, accessibility, abstract, objectives), (2)scope (temporal, spatial, taxonomic, thematic, collection status, update frequency, last update. curation status, completeness), (3)methods ( plot selection, establishment, layout and description methods, sampling methods for each suite of ecological attributes) and (4) condition of data use (citation, licence, rights, access, collaboration and contact statements) and (5) reference list. aim with our metadata to offer the highest scientific quality are given the highest priority.
|Trusted: We balance the different user needs to make it easy for users to find, understand and access data by having commonly used interfaces and functionality, interoperability of services and dedicated support to help users.