AndreaBozzo/ceres-open-data-index huggingface dataset:
Cost of Salinity to Local Infrastructure 1996-97 – Total cost the road component of infrastructure based on the best estimate as described in the project reports. Costs are estimates of the impact of the extent of salinity projected to occur in 2020

    

This dataset contains 14 national surfaces, represented by 1km grids, relating
to the cost of salinity damage to local infrastructrure. The infrastructure
cost impacts are limited to those that occur at the location of salinity
problem, downstream and other offsite impacts are not covered. All dollar
values are given in 1996/97 Australian dollars. Each is described as
follows:1. Total cost ($) to all infrastructure (buildings, road, rail and
bridges) based on the low, abesta and high estimates of the impact of the
current (2000) extent of salinity.2. Total cost ($) to all infrastructure
(buildings, road, rail and bridges) based on the low, abesta and high
estimates of the impact of predicted 2020 extent of salinity3. Total cost ($)
the general infrastructure component (buildings etc., derived from population)
as the abesta estimate of the impact of the current (2000) extent of
salinity.4. Total cost ($) the general infrastructure component (buildings
etc., derived from population) based on the abesta estimate of the impact of
the predicted 2020 extent of salinity5. Total cost ($) the road component of
infrastructure based on the abesta estimate of the impact of the current
(2000) extent of salinity.6. Total cost ($) the road component of
infrastructure based on the abesta estimate of the impact of the predicted
2020 extent of salinity7. Total cost ($) the rail component of infrastructure
based on the abesta estimate of the impact of the current (2000) extent of
salinity.8. Total cost ($) the rail component of infrastructure based on the
abesta estimate of the impact of the predicted 2020 extent of salinity9. Total
cost ($) the bridge component of infrastructure based on the abesta estimate
of the impact of the current (2000) extent of salinity.10. Total cost ($) the
bridge component of infrastructure based on the abesta estimate of the impact
of the predicted 2020 extent of salinity11. Total cost ($) increase to local
infrastructure based on the abesta estimate of the impact of the predicted
2020 extent of salinity

See [further metadata](http://data.daff.gov.au/anrdl/metadata_files/pa_csli_r9cl
__08012a07.xml) for more detail.



Tags: economics, farming, humanenvironment, utilities, waterquality
Organization: Australian Bureau of Agricultural and Resource Economics and Sciences
Springs of the Galilee subregion - Points Geometry

## **Abstract** 

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement.

The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

## **Dataset History** 

A point geometry shapefile was created by extracting from the source file spring locations located within a manually created bounding box including the GAL zone of potential hydrological change.

## **Dataset Citation** 

Bioregional Assessment Programme (2017) Springs of the Galilee subregion - Points Geometry. Bioregional Assessment Derived Dataset. Viewed 12 December 2018, http://data.bioregionalassessments.gov.au/dataset/d0b46bf8-b29f-48e1-a655-8148fd9b02ac.

## **Dataset Ancestors** 

* **Derived From** [Queensland wetland data version 3 - wetland areas.](https://data.gov.au/data/dataset/2a187a00-b01e-4097-9ca4-c9683e7f4786)

* **Derived From** [Geofabric Surface Cartography - V2.1](https://data.gov.au/data/dataset/5342c4ba-f094-4ac5-a65d-071ff5c642bc)

* **Derived From** [Landscape classification of the Galilee preliminary assessment extent](https://data.gov.au/data/dataset/53c534ba-bf4a-4d2a-a220-e74d72e27969)

* **Derived From** [Geofabric Surface Cartography - V2.1.1](https://data.gov.au/data/dataset/ce5b77bf-5a02-4cf8-9cf2-be4a2cee2677)

* **Derived From** [QLD Springs Dataset 2016](https://data.gov.au/data/dataset/26030523-4eb6-4abb-8932-bee72f954303)

* **Derived From** [QLD Springs Dataset 2016 v02](https://data.gov.au/data/dataset/ef1a2e22-4a81-43c7-b5c2-2fd18e4d0ef5)

* **Derived From** [GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)](https://data.gov.au/data/dataset/96ebf889-f726-4967-9964-714fb57d679b)

* **Derived From** [Queensland groundwater dependent ecosystems](https://data.gov.au/data/dataset/10940dfa-d7ef-44fb-8ac2-15d75068fff8)

* **Derived From** [GEODATA TOPO 250K Series 3](https://data.gov.au/data/dataset/a0650f18-518a-4b99-a553-44f82f28bb5f)

* **Derived From** [Multi-resolution Valley Bottom  Flatness MrVBF at three second resolution CSIRO 20000211](https://data.gov.au/data/dataset/7dfc93bb-62f3-40a1-8d39-0c0f27a83cb3)

* **Derived From** [Landscape classification of the Galilee preliminary assessment extent](https://data.gov.au/data/dataset/80e7b80a-23e4-4aa1-a56c-27febe34d7db)

* **Derived From** [Biodiversity status of pre-clearing and remnant regional ecosystems - South East Qld](https://data.gov.au/data/dataset/9b7bcebf-8b7f-4fb4-bc91-d39f1bd960cb)



Tags: Galilee subregion, geoscientificInformation
Organization: Bioregional Assessment Program
Cooper GBA region LiDAR


## **Abstract** 
LiDAR (Light Detection and Ranging) data was collected for the Geological and Bioregional Assessment Program by Fugro Australia Land Pty Ltd over two mobilisations. The data was acquired at an average density of 1 point per square metre, processed and compiled as LiDAR Classified Data in LAS 1 km tiles and 1 m grid DEM in ESRI ascii 1 km tiles. The total area of survey is 31,780 km². The data was used to develop a Digital Elevation Model and to determine bathymetry for a two-dimensional hydrodynamic flood inundation model of the Cooper Creek floodplain.


## **Attribution** 
Geological and Bioregional Assessment Program


## **History** 
LiDAR data was acquired by Fugro Australia Land Pty Ltd over two mobilisations. The first mobilisation was flown from 20 March - 4 April 2019 with an aircraft equipped with a Riegl LMS Q780 LiDAR system. The second mobilisation was flown from 6 - 17 October 2019 with an aircraft equipped with a Riegl LMS Q1560 LiDAR system. Nominal flying height was 2800 mAGL with a swath width of 3200 m.
Processing steps:
• Project Planning
• Aircrew briefing
• Acquisition as per requirements of dry Season
• Field data QA for integrity and completeness
• Downloading raw data
• QA Raw data
• GNSS-IMU Coupled Solution
• Riprocess processing
• Geodetic Validation Flight Line matching
• Ground Filter
• LiDAR data Classification
• Product Generation LiDAR Derivates
• QA of data
• Delivery of Data and reports

Tags: Digital Elevation Model, REMOTE SENSING Lidar, WATER Bathymetry
Organization: Bioregional Assessment Program
Current meter data obtained from a mooring off Point Perpendicular, Jervis Bay: 05/04/89 - 28/03/90

A current meter mooring was installed at the entrance of Jervis Bay, off Point Perpendicular. This mooring housed 2 current meters, at 12m and 34m. Over a period of approx. 1yr the mooring was deployed 5 times in nominally the same location (as illustrated). Deployment 1,3, 4 & 5 - 35.1 S, 150.797 E. Deployment 2 - 35.0983 S, 150.793 E. Datasets presented here correspond to data retrieved from the two current meters over the year. 

The hourly datasets provide data accumulated from all 5 deployments, and provide details of the eastern & northern tidal components, cross & long-shore velocity components, temperature, salinity and sigma-T.

The subsets to these larger datasets, present individual data points collected at sample intervals of 10 mins (deployment 1) or 15 mins (deployments 2, 3, 4, 5). Compared to the hourly averaged datasets, these allow water movements to be studied over a shorter time scale. The parameters measured include the eastern and northern tidal components, water speed and direction, temperature, salinity and sigma-T.

Approx deployment dates - see individual records for exact date and time of collection: 1)  5/4/89 - 4/6/89... 2) 23/6/89 - 28/8/89... 3) 30/8/89 - 13/11/89... 4) 14/11/89 - 29/1/90... 5) 31/1/90 - 28/3/90

This is one of four child records that relate to the parent, 5f4333e0-2ae5-11dd-a735-00188b4c0af8. A pdf outlining the structure and hierarchy of all metadata records relating to this project is available to download through this record. Also available is a pdf of a published working paper documenting this experiment and the results.

Tags: Ocean Circulation, Ocean Currents, Ocean Temperature, Oceans, Salinity, Tidal Components, Tidal Currents, Tides, Water Temperature
Organization: Australian Defence Force Academy (ADFA)
Surface water entitlements for Cooper and Isa basins


## **Abstract** 
The dataset was compiled by the Geological and Bioregional Assessment Program from data  sourced from the Queensland Department of Natural Resources, Mines and Energy. The processes undertaken to compile this dataset are described in the History field in this metadata statement.


## **Attribution** 
Geological and Bioregional Assessment Program


## **History** 
The Lineage field lists the parents of this dataset. Work Location points were exported to an ArcGIS 10.6 File Geodatabase for each polygon area supplied by the Geological and Bioregional Assessment project teams for each area. Corresponding work locations found with each polygon were exported from the licensing system.

Tags: energy water and waste systems, environmental resources
Organization: Bioregional Assessment Program
Water balance of Cullyamurra and Nappamerrie waterholes in the Cooper GBA region


## **Abstract** 
The dataset was compiled by the Geological and Bioregional Assessment Program from multiple sources referenced within the dataset and/or metadata. The processes undertaken to compile this dataset are described in the History field in this metadata statement. This dataset contains a water balance after cease to flow on an event basis for the Cullyamurra and Nappamerrie waterholes. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.


## **Attribution** 
Geological and Bioregional Assessment Program


## **History** 
This dataset contains a water balance after cease to flow on an event basis for the Cullyamurra and Nappamerrie waterholes. Each of these waterholes has a gauging station established by the respective state governments that is measuring stage height, this is converted into a change in storage on a daily basis. The SILO climate data is used to provide the rainfall as input and Morton's Lake evaporation as an output. The difference between the change in storage plus rainfall minus evaporation is the interactions with groundwater and the error term.

Tags: Inland water features
Organization: Bioregional Assessment Program
GBA assessment regions extent


## **Abstract** 
This dataset is a compilation of the three Geological and Bioregional Assessment Program assessment region boundaries. It can be used for cartographic applications to provide overview maps of the assessments, as well as for clipping national scale datasets to the three assessment boundaries.


## **Attribution** 
Geological and Bioregional Assessment Program


## **History** 
This dataset contains the boundary extent of the Cooper, Beetaloo and Isa GBA regions. Shapefiles have been compiled from the source datasets outlined in the lineage and are unprojected (Geographical; GDA94) and projected (Australian Albers; GDA94).

Tags: BOUNDARIES Mapping
Organization: Bioregional Assessment Program
Daily colour changes associated with the fiddler crab, Uca capricornis

The purpose of this experiment was to examine the daily colour changes in relation to the tidal cycle in the fiddler crab, Uca capricornis. Experiments were conducted in the East Point Reserve, Darwin from Nov - Jan (04/05 & 05/06). 

Twenty-seven crabs (13 males, 14 females) were observed on the day after spring tide over several semilunar cycles. Digital photos of the crabs were taken before, during and after low tide. These photographs were examined for any changes in colour or pattern. 

Uca capricornis do not regularly change their colouration over the course of the day. Of the 27 individuals observed, 24 did not noticeably change their colour, and none altered their pattern.

Tags: 28 960036, Behavioural Ecology, Biosphere, Colour Pattern, Crustaceans, Daily Changes, Fiddler Crab, Ocypodidae, Uca capricornis, Zoology
Organization: Australian National University
Daily Net Foreign Exchange Transactions

    

The historical data in this table are sourced from Becker C and M Sinclair
(2004), :Profitability of Reserve Bank Foreign Exchange Operations:
Twenty Years After the Float-C/, RB Research Discussion Paper No
2004-06. Updates to the data are published annually with a one-year lag.

It is not appropriate to use the :Market-C/ series as a proxy for
foreign exchange market intervention. The RB engages in spot or forward
transactions with dealers in the market virtually every day. Most of these
transactions are not intended to influence the exchange rate. Rather, they
occur to cover orders for foreign exchange from clients such as the Australian
Government. When the RB sells foreign exchange to a client, it has the choice
of meeting this out of its holdings of foreign exchange or buying the
equivalent amount of foreign exchange in the market. Most of the time it does
the latter, though even then the timing of the sale and purchase may not
coincide precisely. The RB can also engage in foreign exchange transactions
with counterparties other than dealers as a means of covering client orders.

Daily net foreign exchange transactions, net sales (-) and purchases (+), are
reported according to the date on which the trade took place. This is in
contrast to the monthly transactions data in Table A.4, which are reported
according to the day on which settlement took place. Another difference to
Table A.4 is that interest received on holdings of foreign assets is not
included.

aMarketa transactions are foreign exchange transactions against the Australian
dollar (excluding foreign exchange swaps) undertaken by the RB with
authorised foreign exchange dealers in Australia or banks overseas.

aGovernment and other counterpartiesa transactions include the RBAas foreign
exchange transactions with the Australian Government, outright transactions
with other central banks and international financial institutions that are not
intended to affect the exchange rate, and transactions with clients other than
the Australian Government.



Tags: finance, foreignexchange, rba, statistics
Organization: Reserve Bank of Australia
Daintree Automatic Weather Station (North Queensland)

This dataset contains historical meteorological data from the weather station, which was located north of the Daintree River in North Queensland, between 12 February 1997 and 31 May 1998.

Data recorded: Barometric Pressure, Air Temperature, Solar Radiation (PAR), Wind Direction True (vector averaged), Wind Speed True (30 min average), Humidity, Rainfall.

Tags: Atmospheric Sciences, EARTH SCIENCES, Meteorology
Organization: Australian Institute of Marine Science
Data from the OAIC Public Sector Information Survey 2012

    

The OAIC commissioned ORIMA Research to conduct a dual survey - the PSI
survey, together with a survey of Australian Government agencies on compliance
with their obligations under the Information Publication Scheme. The PSI
survey was structured around the eight [Principles on open public sector infor
mation](http://www.oaic.gov.au/publications/agency_resources/principles_on_psi
_short.html) (Open PSI principles) that were published by the OAIC in 2011.

The IPS/PSI survey was carried out by ORIMA Research in April and May 2012. It
was completed by 191 agencies (78%) of the 245 that were approached. The OAIC
complemented the PSI survey by conducting focus group discussions with a
variety of Australian Government agencies.

The data has been compiled by ORIMA Research from their Data Pack Report for
the PSI Survey.

Please refer to the [PSI survey (PDF, 1.09MB)](http://www.oaic.gov.au/images/documents/information-policy/information-policy-resources/information-policy-reports/IPS_PSI_questionnaire.pdf) on the OAIC
website.

Please refer to the [Data Pack Report for the PSI survey (PDF, 1.72MB)](http://www.oaic.gov.au/images/documents/information-policy/information-policy-resources/information-policy-reports/ORIMA_data_pack_report_PSI_survey.pdf) on the OAIC website.

The OAIC has released two reports examining the issues encountered by agencies
in implementing the Open PSI principles, drawn from the survey results and
focus group discussions.

The interim report of the PSI survey and focus group discussions, [Open
public sector information: government in transition](http://www.oaic.gov.au/information-policy/information-policy-resources/information-policy-reports/open-public-sector-information-government-in-transition), is available on
the OAIC website.

The full report of the PSI survey and focus group discussions, [Open Public
Sector Information: from principles to practice](http://www.oaic.gov.au/public
ations/reports/open_psi_principle_to_practice_february2013.html), is
available on the OAIC website.



Tags: informationmanagement, opendata, opengovernment, openpsi, psi, psisurvey, publicsectorinformation
Organization: Office of the Australian Information Commissioner
Cost of Salinity to Local Infrastructure 1996-97 – Total cost of all infrastructure (buildings, road, rail and bridges) based on the low estimate as described in the project reports. Costs are estimates of the impact of the current (2000) extent of salinity

    

This dataset contains 14 national surfaces, represented by 1km grids, relating
to the cost of salinity damage to local infrastructrure. The infrastructure
cost impacts are limited to those that occur at the location of salinity
problem, downstream and other offsite impacts are not covered. All dollar
values are given in 1996/97 Australian dollars. Each is described as
follows:1. Total cost ($) to all infrastructure (buildings, road, rail and
bridges) based on the low, abesta and high estimates of the impact of the
current (2000) extent of salinity.2. Total cost ($) to all infrastructure
(buildings, road, rail and bridges) based on the low, abesta and high
estimates of the impact of predicted 2020 extent of salinity3. Total cost ($)
the general infrastructure component (buildings etc., derived from population)
as the abesta estimate of the impact of the current (2000) extent of
salinity.4. Total cost ($) the general infrastructure component (buildings
etc., derived from population) based on the abesta estimate of the impact of
the predicted 2020 extent of salinity5. Total cost ($) the road component of
infrastructure based on the abesta estimate of the impact of the current
(2000) extent of salinity.6. Total cost ($) the road component of
infrastructure based on the abesta estimate of the impact of the predicted
2020 extent of salinity7. Total cost ($) the rail component of infrastructure
based on the abesta estimate of the impact of the current (2000) extent of
salinity.8. Total cost ($) the rail component of infrastructure based on the
abesta estimate of the impact of the predicted 2020 extent of salinity9. Total
cost ($) the bridge component of infrastructure based on the abesta estimate
of the impact of the current (2000) extent of salinity.10. Total cost ($) the
bridge component of infrastructure based on the abesta estimate of the impact
of the predicted 2020 extent of salinity11. Total cost ($) increase to local
infrastructure based on the abesta estimate of the impact of the predicted
2020 extent of salinity

See [further metadata](http://data.daff.gov.au/anrdl/metadata_files/pa_csli_r9cl
__08012a12.xml) for more detail.



Tags: economics, farming, humanenvironment, utilities, waterquality
Organization: Australian Bureau of Agricultural and Resource Economics and Sciences
Data of Oceanographic and Marine Meteorological Observation: Japan Meteorological Agency

The Japan Meteorological Agency (JMA) carries out oceanographic and marine meteorological observations through research vessels and ocean data buoys in the western North Pacific and the seas adjacent to Japan.

Oceanographic and marine meteorological observations are conducted in the western North Pacific and in the seas adjacent to Japan by five JMA research vessels named the Ryofu Maru, the Keifu Maru, the Kofu Maru, the Chofu Maru and the Seifu Maru. Background marine pollution and greenhouse gases are also observed.

JMA operates drifting ocean data buoys. The buoys are equipped with sensors near the sea surface level to measure positioning, air pressure, sea surface temperature and wave height/period.

Tags: Air Temperature, Atmosphere, Atmospheric Chemistry, Atmospheric Temperature, Carbon Dioxide, Hydrocarbons, Inorganic Carbon, Methane, NW, Nutrients, Ocean Chemistry, Ocean Temperature, Ocean Waves, Ocean Winds, Oceans, Oxygen, PACIFIC OCEAN, Phosphate, Salinity, Sea Surface Temperature, Water Temperature, Wave Height, Wave Period, Wind Shear, carbon dioxide, hydrocarbon, oxygen, phosphate, pollutants, salinity, temperature, wind direction, wind speed
Organization: Japan Meteorological Agency (JMA)
Data source for polygonal data used by the ASRIS project in generation of modelled surfaces

    

Data provided are the scale of polygonal datasources used to generate the
polygon derived surfaces for the intensive agricultural areas of Australia.
Data modelled from area based observations made by State soil agencies.The
final ASRIS polygon attributed surfaces are a mosaic of all of the data
obtained from various state and federal agencies. The surfaces have been
constructed with the best available soil survey information available at the
time. The surfaces also rely on a number of assumptions. One being that an
area weighted mean is a good estimate of the soil attributes for that polygon
or mapunit. Another assumption made is that the lookup tables provided by
McKenzie et al. (2000), state and territories accurately depict the soil
attribute values for each soil type.The accuracy of the maps is most dependent
on the scale of the original polygon data sets and the level of soil survey
that has taken place in each state. The scale of the various soil maps used in
deriving this map is available by accessing darasource grid, the scale is used
as an assessment of the likely accuracy of the modelling.The Atlas of
Australian Soils is considered to be the least accurate dataset and has
therefore only been used where there is no state based data.Of the state
datasets Western Australian sub-systems, South Australian land systems and NSW
soil landscapes and reconnaissance mapping would be the most reliable based on
scale. NSW soil landscapes and reconnaissance mapping however, may be less
accurate than South Australia and Western Australia as only one dominant soil
type per polygon was used in the estimation of attributes, compared to several
soil types per polygon or mapunit in South Australia and Western Australia.
NSW soil landscapes and reconnaissance mapping as the name suggests is
reconnaissance level only with no laboratory data. The digital map data is
provided in geographical coordinates based on the World Geodetic System 1984
(WGS84) datum.

See [further metadat](http://data.daff.gov.au/anrdl/metadata_files/pa_dams_r9cl_
_04011a00.xml) for more detail.



Tags: agriculture, geoscientificinformation, models, soil
Organization: Commonwealth Scientific and Industrial Research Organisation (CSIRO)