Craig Walker_TERN Eco-informatics: Managing and delivering ecological research data now and into the future
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The document discusses the goals and activities of TERN Eco-informatics, which aims to bring together ecological data from across Australia for reuse through the Australian Ecological Knowledge and Observation System (ÆKOS). Key goals include negotiating access to national ecological databases, consolidating datasets, developing data standards, and building a portal for ecological data. ÆKOS ingests data, makes it accessible, and provides benefits like increased research and reduced data collection costs. Future potential includes expanding datasets, improving tools, and supporting capacity building.
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Craig Walker_TERN Eco-informatics: Managing and delivering ecological research data now and into the future
- 1. TERN Eco-informatics – Managing and delivering ecological research data now and into the future Craig Walker Eco-informatics Facility Director
- 2. Eco-informatics Goals Bringing ecological data together for informed re-use Priorities for NCRIS: Negotiate sharing and access for key national ecological databases (States and Commonwealth) Consolidate ecological datasets from across Australia Develop a national framework for describing and publishing ecological information (“standards”) Encourage researcher uploading of data (SHaRED) Build a “One-Stop-Shop” portal for ecological data These Goals are being addressed through the Australian Ecological Knowledge and Observation System – ÆKOS
- 3. Eco-informatics Goals cont. Supplementary funding for projects: Fully ingest, integrate and deliver TERN Ausplots data (EIF) Support mobile field capture platforms and data (EIF) Support the TERN Data Discovery Portal (EIF) Incorporate MSPN datasets in ÆKOS (EIF) Build SHaRED tool for Researcher Data Submission (NeCTAR) Build Soils-to-Satellites web application (ANDS)
- 4. Environmental Information Landscape for Australia
- 6. What is ecological “plot” data?
- 7. The ÆKOS Information Landscape Supporting Knowledge © eResearchSA © eResearchSA Models Context Data Plants Birds Bats
- 8. The ÆKOS system Soils-to-Satellites ALA Web Services Data Portal Access Control Information Framework RIF-CS ANDS, TDDP ÆKOS Data Repository Facilitated End-user Community SHaRED Tool Ingest Researcher Submitted Data Licensing Framework TERN MSPN Data Agency Datasets Fauna Flora Govt Ecological Surveys
- 9. ÆKOS Operational Model Common Information Model (Ontology) Data Custodian Subject Expertise ETL Script Engine Data Data Ingestion ÆKOS Source Portal Data Portal Contextual ÆKOS DSL Description ÆKOS Repository
- 10. Key benefits Access to research data increases the return from public investment (OECD Report 2007) Open Access promotes new areas of research and enables exploration of topics not envisaged by the initial researcher Demonstrates delivery in 2013 of a “discipline-oriented and purpose-specific research supporting infrastructure” under NCRIS
- 11. Key benefits for researchers ... ... as data publishers: • Increased visibility • Attribution, citation and acknowledgement • Minimises data misuse • Minimise loss of data memory • Potential for increased collaboration
- 12. Key benefits for researchers... ... as data users: • Single point of access nationally • Enables assessment of ‘fitness for purpose’ of data for re-use • Reduces data preparation (integrate once, use many times) • Minimises cost of recollecting data • Integration and federation of datasets for local-to-national scale studies 1750 2010 http://www.ehow.com
- 13. Current “Beta 1.2” portal © State of South Australia (Dept of Environment, Water & Natural Resources)
- 14. The Future Potential Extension of thematic coverage to include vertebrate and invertebrate fauna, fire monitoring, aquatic ecosystems More data ingested to strengthen the focal point of the portal, given that ÆKOS is generic and supports all ecological data Improvements to visualisation and analysis based on feedback from the ecological community ÆKOS is a suitable repository for the vast volumes of hardcopy material including an effective means of dealing with “filing cabinet leftovers” from existing databases National method catalogue for ecological data collection Strong partnerships developed with custodians can be extended to support capacity building within Agencies, and can optimise legacy and future investments
- 15. Thank you Eco-informatics Facility Contact Details Eco-informatics Director - Craig Walker craig.walker@adelaide.edu.au Data and Partnerships Facilitator -Dr Anita Smyth anita.smyth@adelaide.edu.au Ecological Data Manager - Dr David Turner d.turner@adelaide.edu.au ICT Project Manager – Martin Pullan martin.pullan@adelaide.edu.au Website www.aekos.org.au
Editor's Notes
- This is AEKOS’s niche within the broader framework for the environmental information landscape for Australia. ÆKOS is filling a gap for complex ecological data at the plot level.3 broad categories on the left.BOM is dominating the climate and water space6 initiative serve physical environmental data , 4 are TERN facilities3 initiative house biotic data.
- WhileEco-informatics is concerned with rich ecological data it does not generate data itself. This means that strong collaborations and partnerships are a necessary part of business.
- What type of data is housed in AEKOS?Quantitative data is systematically collected by plot-based sampling units for plants and animals. The key point to note is that this data is quite complex with potentially many thousands of observations and a range of differing methods of collection over many visits at the one sampling location.
- When we talk about ecological data, we need to recognise that it’s not just the data that is important. We need to recognise the context-dependency of the data – i.e. that there is significant additional detail required in order to correctly interpret it and draw valid rather than invalid conclusions. One of the key differences in ÆKOS over other data publication platforms is the attempt to put the data in context and ensure that the related information to help appropriate interpretation is supplied to data users. As well supporting knowledge around the paradigm that was used to collect the data is included so that better understanding of the data can be made.
- Key points to note here are that data is sourced from State and Federal Government large ecological databases, after a suitable open access licence is negotiated. These data are then mapped to a common model “ingested” and stored in the Repository. Other generally smaller datasets are entered through the SHaREd tool. The Data Portal is the public facing means of accessing the data, and this is generally by data records rather than by datasets (although both methods are available). Services are also being made available to deliver data to the ALA, and RIF-CS format metadata is made available to ANDS and the TERN Data Discovery Portal.
- The AEKOS operational model is unusual as it doesn’t rely upon a fixed database schema. This is because the ecological domain in constantly evolving, ecologists use so many different approaches to data collection, and existing repositories across Australia are all different. This approach will be discussed in detail by David Turner tomorrow, however the key component is the DSL in the centre as this maps source data with enrichment across to a common model in the data store, and builds a search index to support the portal functions.Data Enrichment - Transfer source database, enrich the context by utilising the strong relationship between Agency and Eco-informatics, to add knowledge from the custodial expert to the dataData Integration – map data into a common structure that reflects to reality of data using an ontological model rather than a system-specific approachSemantics – all fields and all vocabulary concepts have definitions for clarity. Can search across data which is different in the source but similar in ÆKOSThe ÆKOS DSL is the centrepiece of the system. This defines the NoSQL model, identifies inconsistences resulting from information model changes and re-aligns data to extended or revised model. This approach supports a constantly changing or evolving model – the domain is not static so no schema – there is continuous change. DSL also provides the framework for the portal products as it pre-populates the search index, graph visualisation and description. This means that the portal products are defined on the fly rather than be hard coded.
- (money, time, lost opportunity)