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Use of www to achieve environmental data

Use of www to achieve environmental data. Benjamin Pfeil Bjerknes Centre for Climate Research / University of Bergen. Ways how to get data. ...but also. Often data shows a snapshot of the environment at that time/space

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Use of www to achieve environmental data

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  1. Use of www to achieve environmental data Benjamin Pfeil Bjerknes Centre for Climate Research / University of Bergen

  2. Ways how to get data...

  3. ...but also

  4. Often data shows a snapshot of the environment at that time/space • Sampling can be very expensive (average of over 900.000 NOK for one data set for bio-, geoscience - including costs for expeditions, laboratories, etc) • Therefore is data very valueable for future scientific work and has to be archived and made available

  5. Why do we need data? • Verification of research results • Comparison of results • Indication of trends • Model input • Remote sensing • Etc.

  6. Some facts about data in the scientific community • Scientific instruments and computer simulations create large amount of data • Due to new measurement (and better precision) are the data volumes doubling each year • Scientific data has to be archived according to ”Good scientific practise in research and scholarship” (European Science Foundation 2000)

  7. Global increase in publications in empirical sciences ?

  8. Good scientific practice in research and scholarship European Science Foundation (ESF), 2000 Data accumulation, handling, and storage 36. Data are produced at all stages in experimental research and in scholarship. Data sets are an important resource, which enable later verification of scientific interpretations and conclusions. They may also be the starting point for further studies. It is vital, therefore, that all primary and secondary data are stored in a secure and accessible form. 37. Institutions may pay particular attention to documenting and archiving original research and scholarship data. Several codes of good practice recommend a minimum period of 10 years, longer in the case of especially significant or sensitive data. National or regional discipline-based archives should be considered where there are practical or other problems in storing data at the institution where the research was conducted.

  9. Principles for dissemination of scientific data (International Council for Science/CODATA) 4. Scientific advances rely on full and open access to data. Both science and the public are well served by a system of scholarly research and communication with minimal constraints on the availability of data for further analysis. The tradition of full and open access to data has led to breakthroughs in scientific understanding, as well as to later economic and public policy benefits. The idea that an individual or organization can control access to or claim ownership of the facts of nature is foreign to science. 5. The interests of database owners must be balanced with society’s need for open exchange of ideas. Given the substantial investment in data collection and its importance to society, it is equally important that data are used to the maximum extent possible. Data that were collected for a variety of purposes may be useful to science. Legal foundations and societal attitudes should foster a balance between individual rights to data and the public good of shared data.

  10. International Council for Science (ICSU) • Founded in 1931 to promote international scientific activity in the different branches of science and its application for the benefit of humanity • One of the oldest non-governmental organizations • More than 135 nations adhere to it • ISCU established the World Data Center system in the 1950s Source: www.iscu.org

  11. World Data Center system Mission Statement of the World Data Center System • Data constitute the raw material of scientific understanding. The World Data Center system works to guarantee access to solar, geophysical and related environmental data. It serves the whole scientific community by assembling, scrutinizing, organizing and disseminating data and information

  12. Airglow • Mitaka,Japan • Rockets and Satellites • Obninsk, Russia • Astronomy • Beijing, China • Rotation of the Earth • Obninsk, Russia • Washington DC, USA • Atmospheric Trace Gases • Oak Ridge TN, USA • Satellite Information • Greenbelt MD, USA • Aurora • Tokyo, Japan • Seismology • Denver CO, USA • Beijing, China • Cosmic Rays • Toyokawa, Japan • Soils • Wageningen, The Netherlands • Earth Tides • Brussels, Belgium • Solar Activity • Meudon, France • Geology • Beijing, China • Solar Radio Emission • Nagano, Japan • Geomagnetism • Copenhagen, Denmark • Edinburgh, UK • Kyoto, Japan • Colaba, India • Solar Terrestrial Physics • Boulder CO, USA • Didcot Oxon, UK • Moscow, Russia • Haymarket, Australia • Glaciology • Boulder CO, USA • Cambridge, UK • Lanzhou, China • Solid Earth Geophysics • Beijing, China • Boulder CO, USA • Moscow, Russia • Oceaography • Obninsk, Russia • Silver Spring MD, USA • Tianjin, China • Recent Crustal Movements • Ondrejov, Czech Republic • Human Interactions in the Environment • Palisades NY, USA • Space Science • Beijing, China • Sunspot Index • Brussels, Belgium • Remotely Sensed Land Data • Sioux Falls SD, USA • Ionosphere • Tokyo, Japan • Space Science Satellites • Kanagawa, Japan • Marine Environmental Sciences • Bremen, Germany • Paleoclimatology • Boulder CO, USA • Renewable Resources and Environment • Beijing, China Network of ICSU WDCs • Meteorology • Asheville NC, USA • Beijing, China • Obninsk, Russia • Marine Geology and Geophysics • Boulder CO, USA • Moscow, Russia • Nuclear Radiation • Tokyo, Japan WDC Co-ordination Offices Washington DC, USA Beijing, China

  13. Where and how do you get data? • Ok, now you have been (hopefully) listening for some time, but how can you have access to environmental data? • You have 15-20 minutes in order to find environmental data using the internet Good luck 

  14. What are scientific data and how can they be structured?

  15. What are data ? DataSet title: VogelsangE et al 2001/Age control of sediment core V23-81 Reference: Broecker, WS et al (1988): Preliminary estimates for the radiocarbon age of deepwater … Bond, GC et al (1993): Correlations between climate records …, Nature, 365: 143-147 Sarnthein, M; Winn, K; Jung, S J A; Duplessy, J C; Labeyrie, L D … (1994): Changes in east… Project: Glacial Atlantic Mapping and Prediction (GLAMAP2000) Event: V23-81 * LATITUDE: 54.2500 * LONGITUDE: -16.8300 * ELEVATION: -2393.0 * DATETIME: 18 Oct 1966 00:00:00 * GEAR: Piston corer, unspec. * CAMPAIGN: V23 Parameter: Age, dated - Age, dated [kyr] * … METHOD: AMS 14C dating. Broecker et al. 1988. … Dated material - Age, dated material * PI: Sarnthein Sed rate - Sedimentation rate [cm/kyrs] * PI: Sarnthein * METHOD: calculated PI: Sarnthein, Michael, e-mail: ms@gpi.uni-kiel.de Data details: http://www.pangaea.de/Cores/Age/V23-81.pdf Source: PANGAEA - DataSet ID: 59872 Depth [m] Age, dated [kyr] Age model [kyr] Dated material Age, error [kyr] Sed rate [cm/kyrs] : 0.015 0.075 0.075 0.620 : 3.310 3.355 : 0.090 0.090 0.100 0.150 : : : : : : : : G. inflata G. bulloides : : : N. pachyderma sin. N. pachyderma sin. : 3.6 1.67 0.05 0.10 0.15 : 21.21 21.70 : 1.32 6.73 : :

  16. Metadata – describing your data who Principal investigator(s) (PI), Project(s) what Title, Identifier (DOI) Data types, Parameter [unit] Quantities how Methods Reference(s) where Spatial coverage -> geographical positions Sampling event, Campaign, Location when Temporal coverage ->

  17. Level of scale Ratio Quantitative, zero included e.g. Kelvin scale { 15.456; -3.2; 760; 0 } Interval Quantitative, no zero, equal intervals (addition, subtraction), but no proportions e.g. Fahrenheit scale Ordinal Semiquantitative, rank-ordered, intervals may not be equal e.g. { first; second; third } { rare; frequent; abundant } Nominal Qualitative, no ordering implied e.g. { male; female } { red; green; blue }

  18. Classification schemes Technical numerical data text data pictures Processing level interpretations, aggregated data (e.g. timeslices) tertiary data SSTformam calculated from raw data (e.g. paleotemperatures) SSTMG/CA secondary data SSTalkenone raw data (e.g. counts, d18O) primary data

  19. What are geocodes? LATITUDE (decimal degrees) LONGITUDE (or degree, minute, second) UTM (Universal Transverse Mercator) DEPTH, sediment [m] DEPTH, ice/snow [m] DEPTH, water [m b.s.l.] ALTITUDE [m a.s.l.] ELEVATION [m a.s.l.] ORDINAL NUMBER eg. Tree ring DISTANCE [cm] DATE/TIME AGE [kyr BP] Spatial Temporal

  20. Geocodes – the third dimension Ice Outcrops (depth, distance, ordinal number) Land Lake Altitude / Elevation Depth in ice Shelf Ocean Depth in water Depth in water Depth in sediment Corals (distance) Warves (ordinal number) Depth in ice Trees (ordinal number) Depth in sediment

  21. Geocodes – temporal DATE/TIME Calendars & timezones GEOLOGIC AGE relative age dating bio- / lithostratigraphy Absolute age dating radiometric time scale chronography Warves Trees Corals nominal ages absolute ages

  22. Ways to archive data

  23. Technical data organisation File systems disadvantage: low consistency of data advantage: fast & cheap archiving procedure (on a short run) Relational databases (RDBs) disadvantage: work intensive archiving procedure, needs high degree of data organization usage for mass data is limited advantage: high consistency of data, low costs for data curation, good retrieval qualities Mixed Relational database -> geocoded data & metadata File system -> mass data (geophysical data, pictures, films)

  24. How to make data available to science?

  25. Possible problems in retrieving data from the net • Version conflicts (data is archived in many data centres – in different stages e.g. raw data, quality controlled, etc.) • Bad documented metadata and data (methods, units, unclear parameter definitions, etc) • Just metadata is available online – data has to be requested • Naming of cruises varies in many countries > hard to identify same cruises • Date formats (mm/dd/yyyy; yy/mm/dd; dd/mm/yyyy etc) • Ways to report the position (Lat/Long, UTM) • Different export formats (plain text, xml, netCDF, etc) • Different entities (one data set = data from one cruise or data from one station or data from one) • Data set is too large to be downloaded (e.g. model data) Result: Can take a lot of time to create large homogenic data collections!

  26. (Some) important WDCs for environmental data • WDC for Atmospheric Trace Gases Carbon Dioxide Information Analysis Center USA • WDC for Climate Model and Data Max-Planck-Institute for Meteorology GERMANY • WDC for Glaciology, Boulder University of Colorado USA • WDC for Marine Environmental Sciences Center for Marine Environmental Sciences (MARUM) GERMANY • WDC for Marine Geology & Geophysics, Boulder USA • WDC for Oceanography, Silver Spring USA

  27. Remember that WDC is a status! There are many national and international data centres as well which are no WDC e.g. ICES – International Council for the Exploration of the Sea, Denmark BODC – British Oceanographic Data Centre, UK BADC – British Atmospheric Data Centre, UK NODC – National Oceanographic Data Center, USA NMD - Norsk marint datasenter, Norway

  28. World Data Center for Marine Environmental Sciences (WDC-MARE) at University of Bremen, Germany • is aimed at collecting, scrutinizing, and disseminating data related to global change in the fields of environmental oceanography, marine geology, paleoceanography, and marine biology. It focuses on georeferenced data using the information system PANGAEA. The WDC stores and handles numeric, string, and image data. Users can retrieve data through the Internet via different gateways. • offers data management services, in particular project data management and data publication. It maintains an inventory of site and sampling locations for all related fields. It provides hosting and mirroring of electronic journals and serves software products for analyzing, visualization, and transformation of data.

  29. How to access dat via WDC-MAREhttp://www.wdc-mare.org/ or http://www.pangaea.de/ • Data is available via www using the search engine PangaVista www.pangaea.de/PangaVista • use it like • E.g. Search by parameter, scientist, region, project, research vessel, institute, etc

  30. You can either view the data online

  31. Or dowload the data

  32. Nice, but what else can I do with the data Since all data at WDC-MARE is archived in a relational database it can be easily converted to other formats like: Ocean Data View ArcGIS PanPlot (Open Source plotting software)

  33. Pan2Application – converter for data from WDC-MARE

  34. Ocean Data Viewhttp://odv.awi-bremerhaven.de/ Ocean Data View (ODV) is a software package for the interactive exploration, analysis and visualization of oceanographic and other geo-referenced profile or sequence data.

  35. PanPlothttp://www.pangaea.de/Software/PanPlot/

  36. Networking between different data holders is essential The user can use one website in order to find metadata and data that is archived in many different data centres

  37. Global Change Master Directory Gives access to metadata, but can be hard to find the data

  38. Gives access to metadata and links directly to the data set

  39. Thanks for listening!Questions?Comments?

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