Your SlideShare is downloading. ×
Ecosystem data and TERN: Genes to geosciences workshop 19 May 2014
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Ecosystem data and TERN: Genes to geosciences workshop 19 May 2014

338
views

Published on

Powerpoint presentation used to support the 'Ecosystem data and TERN' workshop on 19 May 2014, held at Macquarie University in Sydney as part of the Genes to Geosciences seminar series.

Powerpoint presentation used to support the 'Ecosystem data and TERN' workshop on 19 May 2014, held at Macquarie University in Sydney as part of the Genes to Geosciences seminar series.

Published in: Science, Technology, Education

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
338
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
12
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Ecosystem Data and Australia’s TERN: Making the most of TERN to benefit your research and data management! A workshop for the “Genes to Geosciences” Series Macquarie University, May 19, 2014: 1000 – 1500 hrs
  • 2. Contents 1. Welcome and Introductions 2. TERN and the Research Cycle and Data Cycle 3. Australian Ecosystem Data • what’s available • data discovery • evaluation of data – is it suitable for my needs? • download and appropriate re-use 4. eMAST Example - New possibilities with ecosystem data 5. Data Management and Publishing • why does it matter and how can it help you • data management plans • data publishing – what are your options and why does it matter • data publishers – a continuum of approaches • data publishing options with TERN 6. Wrap-up and Exit Survey
  • 3. Who are we? To understand your current practices and topics of interest we did a survey beforehand. Have you previously searched for and accessed data from a public repository? Yes: 7 No: 5 Do you have a data management plan? Yes: 4 No: 8 Have you published data? Yes: 6 No: 6 Survey – your prior knowledge, experience, and requests for today
  • 4. • To explain and demonstrate options available to the ecosystem science research community to use online resources for searching, evaluating, downloading, publishing and managing ecosystem data sets. • Focus on activity and learning-by-doing, rather than too much talking • To recognise different needs of researchers in different position and stages in research careers. 1. Aims and outcomes
  • 5. • What will you walk away with? - Better understanding of the national research infrastructure available to you – TERN - Sense of the kinds of ecosystem data that is available, and how you can get it - Experience searching, assessing and downloading data for your research - Understanding the principles of good data management and the benefits for you - Appreciation of the options for data management - Introduction to tools for managing your data, including TERN infrastructure 1. Aims and outcomes
  • 6. 2. What is TERN? • Infrastructure and networks to support coordinated, collaborative ecosystem science community • Enabling sustained, long-term collection, storage, synthesis and sharing of ecosystem data • Connecting science with policy and management
  • 7. • TERN’s infrastructure for ecosystem science
  • 8. Instruments + Sensors Policy + Management Analysis + Synthesis Modelling Data Searching Data Sharing Data Curation + Publishing Data Storage Processing + Analysis Collection Methods
  • 9. Storage, preservation and discoverability of data Data analysis, integration and synthesis r Ecosystem Science Data + meta-data, licensing Research output: new data and publications Enables large scale and coordinated data collection, sharing and multiple re-uses Enhanced ability to revise, question and expand knowledge Knowledge gap: research questions Proposal and planning Data collection, verification, quality assurance and control Research lifecycle
  • 10. Storage, preservation and discoverability of data Data analysis, integration and synthesis r Ecosystem Science Data + meta-data, licensing Research output: new data and publications Enables large scale and coordinated data collection, sharing and multiple re-uses Enhanced ability to revise, question and expand knowledge Knowledge gap: research questions Proposal and planning Data collection, verification, quality assurance and control This morning
  • 11. 3. Australian Ecosystem Data • Learning Objectives: To identify the following resources for Australian ecosystem science applications: - ecosystem data stores - meta-data portals - data publishers • Sections: • 1030 - 1040 Data discovery • 1040 -1055 Data discovery - exercise • 1055 -1125 Evaluation of data – is it suitable for my needs? • 1125 – 1145 Download and appropriate re-use • 1145 – 1215 eMAST Possibilities
  • 12. Data Discovery Learning objectives: To understand how to approach data discovery through systematic use of ecosystem data stores, portals and data journals.
  • 13. • National infrastructure for Australian ecosystem data
  • 14. • National infrastructure for Australian ecosystem data
  • 15. TERN’s data portals and meta-data structure: Auscover Ozflux Ausplots, and Transects Coasts Soils Supersites Network and LTERN eMAST AeKOS EcoinformaticsTERN Data Discovery Portal
  • 16. TERN Data: TERN facility Kind of data available Where can I access [+ submit] data ? AusCover Remote sensing data and derived products covering: land cover; ecosystem variables; fire; surface radiation, meteorology; base satellite data and inputs to satellite processing; site-based datasets. Via TDDP or AusCover portal: www.auscover.org.au/data/product-list [Submit - matt.paget@csiro.au] AusPlots Vegetation and soil surveys and samples; photopoints. Over 330 sites sampled so far. As at March 2014: data from ~130 rangelands sites available, with more coming soon. Via AEKOS data portal www.aekos.org.au or Soils to Satellites soils2sat.ala.org.au/ (In future will also be searchable from TDDP) Specimens (vegetation voucher samples and soils) ian@ausplots.org.au Photopoints: Contact ben@ausplots.org.au ACEAS (Australian Centre for Ecological Analysis and Synthesis) Synthesised data products from ACEAS working groups. Via TDDP or ACEAS portal: aceas-data.science.uq.edu.au/portal/ [Submit – s.guru@uq.edu.au]
  • 17. TERN Data: TERN facility Kind of data available Where can I access [+ submit] data ? ACEF Australian Coastal Ecosystems Facility Key datasets include coastal bathymetry, coastal habitats, water quality, beach morphology, turtle distribution and habitat Via TDDP or ACEF portal: acef.tern.org.au/portal/ [Submit – jonathan.hodge@csiro.au] Australian SuperSite Network (ASN) Vegetation composition, structure and cover; fauna surveys; soil properties; gas and energy flux (see OzFlux below); meteorology; surface, ground and soil water Via TDDP or ASN portal: www.tern-supersites.net.au/knb/ [Submit – shiela.lloyd@jcu.edu.au] Australian Transect Network (ATN) Vegetation and soil surveys, including specimens. Via AEKOS data portal www.aekos.org.au or Soils to Satellites soils2sat.ala.org.au/ (In future will also be searchable from TDDP) Specimens (vegetation voucher samples and soils) stefan.caddy-retalic@adelaide.edu.au Eco- Informatics Ecological data from individual sites, and from broadscale surveys. Data from AusPlots and the Australian Transect Network, alongside key data from State and Federal partners. See AEKOS data publication schedule for more detail. www.aekos.org.au (In progress of submitting metadata to TDDP) [submit - www.aekos.org.au/access_shared]
  • 18. TERN Data: TERN facility Kind of data available Where can I access [+ submit] data ? eMAST Ecosystem Modelling and Scaling Infrastructure Modelled climate and land surface data derived from surface observations. Partially available via eMAST: www.tern.org.au/e-MAST-Data-Products- pg26355.html (In progress of submitting metadata to TDDP) [Submit - bradley.evans@mq.edu.au] LTERN Long-Term Ecological Research Network Vegetation composition, structure and cover; fauna surveys; surface, ground and soil water Via TDDP or LTERN portal: www.ltern.org.au/knb/ [Contact emma.burns@anu.edu.au ] OzFlux CO2 and other gas concentration and fluxes; evapotranspiration; surface energy balance; carbon and water cycles Via TDDP or OzFlux portal: ozflux.its.monash.edu.au/ecosystem/home [Submit -pisaac.ozflux@gmail.com ] Soil and Landscape Grid of Australia Functional soil attributes and key landscape features. Under development. Best available data products via TDDP: http://portal.tern.org.au/search#!/q=soils/p= 1/tab=collection/group=Soils/num=10 [Submit - mike.grundy@csiro.au]
  • 19. • Other data stores and sources?
  • 20. • Other data stores and sources?
  • 21. • Other data stores and sources?
  • 22. • Other data stores and sources?
  • 23. Data Discovery - Exercise Exercise: • Using the TERN Data Discovery Portal: http://portal.tern.org.au
  • 24. Data Download and Evaluation Learning objective To understand how to effectively search, download and critically assess ecosystem data sets for use in your own work from: ecosystem data stores, portals and data journals.
  • 25. Evaluation of data – is it suitable for my needs? Exercise Exercise: • Evaluating your chosen dataset: • What is the metadata? • What do different parts of the metadata mean? • Is this going to be useful for you? • Criteria to use for evaluation?  Data format (s)  Data currency  Data collection methods  Data QA/QC  Data licence
  • 26. Download and Appropriate Re-use of Data Learning Objective: To understand what data “licensing” is from the research producer, user and owner’s points of view. What do licences mean? If you download data with a licence, what are your obligations for re-use?
  • 27. TERN’s Data Licences http://ww.tern.org.au/datalicence
  • 28. Licencing for Australian Data - www.ausgoal.gov.au
  • 29. ecosystem Modelling And Scaling infrasTructure (eMAST) Integrating multiple data sets Presentation by Brad Evans based on contributions by Colin Prentice, Michael Hutchinson, Gab Abramowitz, Ben Evans, Rhys Whitley, Julie Pauwels
  • 30. Land surface 101: Energy balance Source: IPCC
  • 31. Land surface 101: Carbon cycle Source: NASA eMAST Domain
  • 32. Research domain: Impacts of rising CO2 Thus the ecosystem modeller seeks to: 1. Understand the effects of CO2 increases on ecosystems 2. Quantify negative feedbacks – the impact of rising CO2, land surface warming and extreme events on ecosystems 6CO2 + 6H20 C6H12O6 + 6O2 light energy chlorophyll + nutrients
  • 33. IPCC Consensus: CO2 Fertilization WUE NPP WUE = GPP ET NPP = GPP - R N & P Land Surface Models -> Coupled to Climate Models Other approaches
  • 34. Observations , models and policy (1) MORE Observations (2) BETTER models are developed (3) Models evaluated against observations (4) EVEN BETTER Models (5) BETTER Policy A viscous cycle
  • 35. Unifying principles for ecosystem modellers # 1: Observations, Models and Understanding: Integration of empirical science and modelling betters scientific understanding. # 2: Transparency, Evaluation, Confidence : Reproducible models, evaluated with observations, enhance model efficacy. # 3: Innovation, Standards, Simplicity: Continuous innovation, use standards, mitigate unnecessary complexity.
  • 36. eMAST Observations and Models Models OzFlux CO2 and water fluxes Plot Networks Vegetation Observations via AeKos and Others AusCover Remote Sensing – Satellite, in-situ & Obs. Bureau of Meteorology and Geoscience Australia Land Surface Models Soils Properties of soil dap.nci.org.au geonetwork TERN TDDP tern.org.au RDSI VM’s raijin@nci INTERSECT NeCTAR PALS EVALUATION NeCTAR Virtual Labs
  • 37. eMAST Delivers in 2014-2015 : 1 of 3 Simple land surface process models • eMAST R-Package: MQ & ANU Bioclimate indices and surface processes • eMAST Earth System Model Connex (C++ & FORTRAN): MQ & ANU Bioclimate indices and surface processes coupled to ACCESS and other Earth System Models • ePiSaT R-Package: Continental Gross Primary Production (data model fusion) • Community R-Packages: Hutchinson Drought & BoM Heatwave – in kind from Ivan Hanigan (ANU) • pyeMAST: Python version of eMAST tools including big data services (connectivity with SPEDDEXES). Statistical land surface models • Data Assimilation: Ensemble Kalman Filter coupled to process based land surface model (Renzullo, CSIRO) • Fubaar: Machine learning land surface model (in-kind MQ – Keenan) Open Source ! Tools
  • 38. eMAST Delivers in 2014-2015 : 2 of 3 Observation assimilation into Models • eMAST Ecosystem Model Parameters Database (EMP DB). • NCAR’s Data Assimilation Research Testbed (DART) • DART-CESM : In collaboration with NEON, Inc. (USA) • DART-CABLE : In collaboration with the NCI, NCAR and CSIRO • Assimilation of : fluxes, leaf properties, plot network observations Modelled Data discovery and ACCESS Tools • SPEDDEXES: A community based solution to (a) publishing big data (b) sharing big data (c ) discovering big data and (d) programmatic access to big data on Australia’s eResearch infrastructure. • SPEDDEXES@NeCTAR-VL’s: Collaborative extension of the SPEDDEXES tools to the NeCTAR Virtual Laboratories – embedding in the Climate and Weather Laboratory Benchmarking and Evaluation • eMAST@PALS : Development of the PALS system for eMAST and TERN data streams • eMAST BENCH : International collaboration on benchmarking Tools
  • 39. eMAST Delivers in 2014-2015: 3 of 3 NEXT Generation of Ecosystem Models • ARC DP on Australian Tropical Savanna’s : Past Present and Future: Enhancing ecosystem models for Tropical Savanna’s • ARC DP on the Next Generation of Ecosystem Models: Using plant trait observations to inform a new approach to ecosystem modelling. • GePiSaT: Global version of the ePiSaT model (eMAST and Imperial College of London) • CAMELS: Coupling ACCESS with Models of Ecosystems and the Land Surface: Next generation approach to ecosystem and land surface modelling Datasets from eMAST • ANUClimate: A extension of past methods for gridding Climate and Weather for the Australian continent . • eMAST Bioclimate • eMAST Land Surface Modelling Tools & Data
  • 40. Climate and Bioclimate data Res. 0.01 degrees (nominally 1km) T, P, R + and 50 + indices
  • 41. : New approach for Big Data It is no longer practical, let alone affordable, to continue to do data-intensive ecosystem science in the copy-and-work paradigm, a new approach to working with Big Data is required. Think about network data access, not file downloads … Cross-disciplinary use of file formats and services … Open-source server technology and file formats … Work with big data in a high performance facility
  • 42. Big Data : eMAST’s collections 10 100 1000 10000 5419 1928 326 176 140 DataVolumes(TB) Scientific Data for Research (NCI RDSI node) by 2015
  • 43. Three eMAST projects 1. Observations: The Ecosystem Model Parameters Database 2. Models: Ecosystem Production in Space and Time 3. Observations in Models: CABLE-DART Data assimilation on the NCI
  • 44. Observations The Ecosystem Model Parameters Database • Originally setup to generate continental scale surfaces of leaf properties (nitrogen, phosphorus etc) using ANN’s • Adapted in April 2014 for use with Data assimilation • Focal point for ecosystem scientists and plot networks to contribute observations for use in models EMP DB Example One
  • 45. eMAST : Data assimilation Example Two
  • 46. eMAST : Data assimilation Collaborative ‘Community’ approach: Work with international experts (Fox – NEON and Hoar – NCAR) and local champions Renzullo (CSIRO) and Evans. Open to community participation (Wang, Haverd and Trudinger CSIRO)
  • 47. Data assimilation: NEON Leaf Carbon Fox et al. 2012
  • 48. Data assimilation: NEON Leaf Carbon Fox et al. 2012
  • 49. Ecosystem Production in Space and Time Example Three ePiSaT Data filtering: Removal of outliers etc.. Gap filling of PAR (PPFD) for GPP 1 3 1R = Assimilation Amax = - 2 Efficiency Φ = 2 2 3 Amax * FC = Rectangular Hyperbole 3 parameter 1 2 3 Respiration Quantum R - Φ I Amax +Φ I
  • 50. How does gross primary productivity (GPP) vary in space and time across Australia? How can we ‘simply’ estimate GPP across Australia? What data does TERN provide that might be useful for addressing this research question? Ecosystem Production in Space and Time ePiSaT
  • 51. Choose the ePiSaT model from emast.org.au TDDP or SPEDDEXES Obtain OzFlux data via the TERN/ OzFlux portals Run the ePiSaT model – generate estimates of ecosystem parameters, evaluate them Obtain climate (eMAST) and satellite data (AusCover) to scale the ePiSaT parameters Produce continental scale estimates of GPP and evaluate them Ecosystem Production in Space and Time ePiSaT
  • 52. This project is supported by the Australian National Data Service (ANDS). ANDS is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program and the Education Investment Fund (EIF) Super Science Initiative. For more information visit the ANDS website ands.org.au and Research Data Australia services.ands.org.au.
  • 53. Closing thoughts on data sharing…
  • 54. Lunch 
  • 55. Storage, preservation and discoverability of data Data analysis, integration and synthesis r Ecosystem Science Data + meta-data, licensing Research output: new data and publications Enables large scale and coordinated data collection, sharing and multiple re-uses Enhanced ability to revise, question and expand knowledge Knowledge gap: research questions Proposal and planning Data collection, verification, quality assurance and control This afternoon
  • 56. 5. Data Management & Publishing • Learning Objectives: To understand recognised best practice in “data management” for ecosystem, science data sets. To understand what is required for “data publishing” in appropriate storage sites, portals and journals for specific research purposes – and to understand the diversity of options. • Sections: • 1305-1315 Why does data management + publishing matter and how can it help you? • 1315-1330 Data management plans - exercise • 1330-1340 Data publishing – your options and why does it matter • 1340-1350 Data publishers – a continuum of approaches • 1350-1430 Data publishing options with TERN
  • 57. Data Management Learning Objectives: To understand recognised best practice in “data management” for ecosystem, science data sets. - Why good data management is beneficial? - What is good data management?
  • 58. Poor Data Management Unusable Lost Re-collected www.shutterstock.com . 54240301 http://360digest.com/2006/02/25/messy-office-contest/ TERNAusPlots
  • 59. Personal Drivers Increase efficiency of research Guarantee the quality and authenticity of data Enable exposure of research outcomes via collaborations and dissemination (40%) Provide reproducibility of experimental and computational outcomes Facilitate the validation and verification of results Source: UQL-050112 – Research Data Management Fact Sheet 2
  • 60. Survey on research data management 2012: • 63% aware of Australian Code of Conduct • 70% understand their data management responsibilities • 70% don’t do data management plans • 70% don’t keep a registry of research data collections From Miller, C (2012). “Responses to interviews: University of Adelaide research data repository and metadata store” • 82% agree data should be available to other researchers • 81% would re-use another’s data • 29% supported public access to their data
  • 61. Data Management Plans - Exercise Exercise: Design of a “data management plan” to meet Australian Research Council requirements. ARC Proposal Guidelines – Under “Project Description” “MANAGEMENT OF DATA Outline plans for the management of data produced as a result of the proposed research, including but not limited to storage, access and re-use arrangements.”
  • 62. Data Publishing Learning Objectives: To understand what is required for “data publishing” in appropriate storage sites, portals and journals for specific research purposes – and to understand the diversity of options available. To understand the different levels of publishing possible under the “data publishing continuum.”
  • 63. Why should I publish data? • replication and verification of work; • formal and measureable recognition of data as a research output; • a reduction in the duplication of data collection; • re-use of data in multi- and interdisciplinary research; • greater transparency in the research process.
  • 64. High quality, well-described ecological data for 1000s species occurring at 25,000 sites and another 67,000 coming soon Successful data publishers get noticed Correlation between archived or open access data to copies of published articles and citation impact (Sharing detailed research data is associated with increased citation rate: Piowar, et al (2007)
  • 65. Adopting good science practice • Data are well-described and reproducible • ApplyNHMRC and ARC research ethics • NHMRC Open Access policy came into effect from 1 July 2012 http://www.nhmrc.gov.au/grants/policy/dissemination-research-findings • ARC Open Access policy came into effect from 1 January 2013. http://www.arc.gov.au/applicants/open_access.htm  “A11.5.2. Researchers and institutions have an obligation to care for and maintain research data in accordance with the Australian Code for the Responsible Conduct of Research (2007). The ARC considers data management planning an important part of the responsible conduct of research and strongly encourages the depositing of data arising from a Project in an appropriate publically accessible subject and/or institutional repository. “
  • 66. When not to publish data or place restrictions • Patent application • Confidential human/individual details • Confidential data due to commercial sponsorship arrangements • Sensitive species declared by governments • Sensitive location declared by governments
  • 67. http://www.tern.org.au/Data-publishing-pg26249.html Data Publishers – A Continuum
  • 68. Data Publishing - Exercise Exercise Identification and review of potential data publishers. We will divide you into small groups to assess the approach to data publishing of a given data publisher in terms of: - submission and review process; - attributes required for re-use; - capacity for re-use - costs; and - ability to measure output and re-use.
  • 69. Data Publishing with TERN Learning Objectives: Identification of current and planned data publishing options in TERN. To understand how you can publish your data with TERN
  • 70. TERN’s data portals and meta-data structure: Auscover Ozflux Ausplots, and Transects Coasts Soils Supersites Network and LTERN eMAST AeKOS EcoinformaticsTERN Data Discovery Portal
  • 71. Data Publication in TERN - SHaRED
  • 72. - Metadata complying with ISO 19115 and 19139 international standards; specifically the ANZLIC Profile of those standard - Easy to use - Base template which can accommodate in depth details if needed - *.xml format Tool developed by ANZLIC - the Spatial Information Council (ANZLIC) Data Publication in TERN - ACEF using ANZMet Lite http://spatial.gov.au/sites/default/files/legacy/osdm.gov.au/Metadata/ANZLIC%2Bmetadata%2Bresources/default.html
  • 73. Data Publication in TERN - ACEF using ANZMet Lite
  • 74. Data Publication in TERN - Morpho https://knb.ecoinformatics.org/#tools
  • 75. Questions?
  • 76. 6. Wrap up Outcomes? - Better understanding of the national research infrastructure available to you – including TERN - Knowledge of the kinds of ecosystem data that is available, and how you can get it - Experience searching, assessing and downloading data for your research - Understanding the principles of good data management and the benefits for you - Appreciation of the options for data management - Introduction to tools for managing your data, including TERN infrastructure
  • 77. 6. Wrap up • Email exit survey tomorrow • Presentations and materials online and links sent to you • Please contact us with any questions or follow up items
  • 78. International Partners TERN is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative
  • 79. More Questions? Prof Stuart Phinn s.phinn@uq.edu.au Dr Bek Christensen r.christensen@uq.edu.au www.tern.org.au

×