diff --git a/aodn_cloud_optimised/bin/aggregated_kelp_nonqc.py b/aodn_cloud_optimised/bin/aggregated_kelp_nonqc.py new file mode 120000 index 00000000..579d8acc --- /dev/null +++ b/aodn_cloud_optimised/bin/aggregated_kelp_nonqc.py @@ -0,0 +1 @@ +generic_launcher.py \ No newline at end of file diff --git a/aodn_cloud_optimised/bin/aggregated_seabird_nonqc.py b/aodn_cloud_optimised/bin/aggregated_seabird_nonqc.py new file mode 120000 index 00000000..579d8acc --- /dev/null +++ b/aodn_cloud_optimised/bin/aggregated_seabird_nonqc.py @@ -0,0 +1 @@ +generic_launcher.py \ No newline at end of file diff --git a/aodn_cloud_optimised/bin/aggregated_seagrass_nonqc.py b/aodn_cloud_optimised/bin/aggregated_seagrass_nonqc.py new file mode 120000 index 00000000..579d8acc --- /dev/null +++ b/aodn_cloud_optimised/bin/aggregated_seagrass_nonqc.py @@ -0,0 +1 @@ +generic_launcher.py \ No newline at end of file diff --git a/aodn_cloud_optimised/config/dataset/aggregated_kelp_nonqc.json b/aodn_cloud_optimised/config/dataset/aggregated_kelp_nonqc.json new file mode 100644 index 00000000..2528ab7e --- /dev/null +++ b/aodn_cloud_optimised/config/dataset/aggregated_kelp_nonqc.json @@ -0,0 +1,203 @@ +{ + "dataset_name": "aggregated_kelp_nonqc", + "logger_name": "aggregated_kelp_nonqc", + "cloud_optimised_format": "parquet", + "run_settings": { + "paths": [ + { + "type": "parquet", + "partitioning": null, + "s3_uri": "s3://aodn-processing/stored/datauplift/kelp/kelp.parquet" + } + ], + "cluster": { + "mode": "local", + "restart_every_path": false + }, + "clear_existing_data": true, + "raise_error": false, + "batch_size": 4, + "force_previous_parquet_deletion": false + }, + "metadata_uuid": null, + "schema": { + "occurrenceID": { + "type": "string", + "nullable": "False" + }, + "eventDate": { + "type": "timestamp[ms]", + "nullable": "False" + }, + "decimalLatitude": { + "type": "double", + "nullable": "False" + }, + "decimalLongitude": { + "type": "double", + "nullable": "False" + }, + "label.id": { + "type": "int64", + "nullable": "True" + }, + "verbatimIdentification": { + "type": "string", + "nullable": "False" + }, + "occurrenceStatus": { + "type": "string", + "nullable": "False" + }, + "basisOfRecord": { + "type": "string", + "nullable": "False" + }, + "associatedMedia": { + "type": "string", + "nullable": "False" + }, + "scientificName": { + "type": "string", + "nullable": "False" + }, + "scientificNameID": { + "type": "string", + "nullable": "False" + }, + "taxonRank": { + "type": "string", + "nullable": "False" + }, + "kingdom": { + "type": "string", + "nullable": "False" + }, + "phylum": { + "type": "string", + "nullable": "False" + }, + "class": { + "type": "string", + "nullable": "True" + }, + "order": { + "type": "string", + "nullable": "True" + }, + "family": { + "type": "string", + "nullable": "True" + }, + "genus": { + "type": "string", + "nullable": "True" + }, + "scientificNameAuthorship": { + "type": "string", + "nullable": "False" + } + }, + "aws_opendata_registry": { + "Name": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Description": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Documentation": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Contact": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "ManagedBy": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "UpdateFrequency": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Tags": [ + "FILL UP MANUALLY - CHECK DOCUMENTATION" + ], + "License": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Resources": [ + { + "Description": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "ARN": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Region": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Type": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Explore": [ + "FILL UP MANUALLY - CHECK DOCUMENTATION" + ] + } + ], + "DataAtWork": { + "Tutorials": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Services": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorURL": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ], + "Tools & Applications": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorURL": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ], + "Publications": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ] + } + }, + "schema_transformation": { + "drop_variables": [], + "add_variables": { + "filename": { + "source": "@filename", + "schema": { + "type": "string", + "units": "1", + "long_name": "Filename of the source file" + } + }, + "timestamp": { + "source": "@partitioning:time_extent", + "schema": { + "type": "int64", + "units": "1", + "long_name": "Partition timestamp" + } + }, + "polygon": { + "source": "@partitioning:spatial_extent", + "schema": { + "type": "string", + "units": "1", + "long_name": "Spatial partition polygon" + } + } + }, + "partitioning": [ + { + "source_variable": "timestamp", + "type": "time_extent", + "time_extent": { + "time_varname": "eventDate", + "partition_period": "Y" + } + }, + { + "source_variable": "polygon", + "type": "spatial_extent", + "spatial_extent": { + "lat_varname": "decimalLatitude", + "lon_varname": "decimalLongitude", + "spatial_resolution": 90 + } + } + ], + "global_attributes": { + "set": { + "title": "IMOS - Aggregated Kelp Data Product" + } + } + } +} diff --git a/aodn_cloud_optimised/config/dataset/aggregated_seabird_nonqc.json b/aodn_cloud_optimised/config/dataset/aggregated_seabird_nonqc.json new file mode 100644 index 00000000..322196e4 --- /dev/null +++ b/aodn_cloud_optimised/config/dataset/aggregated_seabird_nonqc.json @@ -0,0 +1,501 @@ +{ + "dataset_name": "aggregated_seabird_nonqc", + "logger_name": "aggregated_seabird_nonqc", + "cloud_optimised_format": "parquet", + "run_settings": { + "paths": [ + { + "type": "parquet", + "partitioning": null, + "s3_uri": "s3://aodn-processing/stored/datauplift/seabird/seabird.parquet" + } + ], + "cluster": { + "mode": "local", + "restart_every_path": false + }, + "clear_existing_data": true, + "raise_error": false, + "batch_size": 4, + "force_previous_parquet_deletion": false + }, + "metadata_uuid": null, + "schema": { + "resource_link": { + "type": "string", + "nullable": "False", + "definition": "The resource link for additional metadata context." + }, + "download_link": { + "type": "string", + "nullable": "False", + "definition": "The Darwin Core download link." + }, + "dataset_version": { + "type": "string", + "nullable": "False", + "definition": "The version of the dataset when it was downloaded to create this aggregated data product." + }, + "id": { + "type": "string", + "nullable": "False", + "definition": "Unique identifier of the row of a given dataset" + }, + "modified": { + "type": "timestamp[ms]", + "nullable": "False", + "long_name": "Date Modified", + "url": "http://purl.org/dc/terms/modified", + "definition": "Date on which the resource was changed." + }, + "bibliographicCitation": { + "type": "string", + "nullable": "True", + "long_name": "Bibliographic Citation", + "url": "http://purl.org/dc/terms/bibliographicCitation", + "definition": "A bibliographic reference for the resource." + }, + "institutionCode": { + "type": "string", + "nullable": "True", + "long_name": "Institution Code", + "url": "http://rs.tdwg.org/dwc/terms/institutionCode", + "definition": "The name (or acronym) in use by the institution having custody of the object(s) or information referred to in the record." + }, + "collectionCode": { + "type": "string", + "nullable": "True", + "long_name": "Collection Code", + "url": "http://rs.tdwg.org/dwc/terms/collectionCode", + "definition": "The name, acronym, coden, or initialism identifying the collection or data set from which the record was derived." + }, + "basisOfRecord": { + "type": "string", + "nullable": "False", + "long_name": "Basis Of Record", + "url": "http://rs.tdwg.org/dwc/terms/basisOfRecord", + "definition": "The specific nature of the data record." + }, + "occurrenceID": { + "type": "string", + "nullable": "False", + "long_name": "Occurrence ID", + "url": "http://rs.tdwg.org/dwc/terms/occurrenceID", + "definition": "An identifier for the dwc:Occurrence (as opposed to a particular digital record of the dwc:Occurrence). In the absence of a persistent global unique identifier, construct one from a combination of identifiers in the record that will most closely make the dwc:occurrenceID globally unique." + }, + "catalogNumber": { + "type": "string", + "nullable": "True", + "long_name": "Catalog Number", + "url": "http://rs.tdwg.org/dwc/terms/catalogNumber", + "definition": "An identifier (preferably unique) for the record within the data set or collection." + }, + "recordedBy": { + "type": "string", + "nullable": "True", + "long_name": "Recorded By", + "url": "http://rs.tdwg.org/dwc/terms/recordedBy", + "definition": "A list (concatenated and separated) of names of people, groups, or organizations responsible for recording the original dwc:Occurrence. The primary collector or observer, especially one who applies a personal identifier (dwc:recordNumber), should be listed first." + }, + "organismQuantity": { + "type": "string", + "nullable": "True", + "long_name": "Organism Quantity", + "url": "http://rs.tdwg.org/dwc/terms/organismQuantity", + "definition": "A number or enumeration value for the quantity of dwc:Organisms." + }, + "organismQuantityType": { + "type": "string", + "nullable": "True", + "long_name": "Organism Quantity Type", + "url": "http://rs.tdwg.org/dwc/terms/organismQuantityType", + "definition": "The type of quantification system used for the quantity of dwc:Organisms." + }, + "sex": { + "type": "string", + "nullable": "True", + "long_name": "Sex", + "url": "http://rs.tdwg.org/dwc/terms/sex", + "definition": "The sex of the biological individual(s) represented in the dwc:Occurrence." + }, + "lifeStage": { + "type": "string", + "nullable": "True", + "long_name": "Life Stage", + "url": "http://rs.tdwg.org/dwc/terms/lifeStage", + "definition": "The age class or life stage of the dwc:Organism(s) at the time the dwc:Occurrence was recorded." + }, + "occurrenceStatus": { + "type": "string", + "nullable": "True", + "long_name": "Occurrence Status", + "url": "http://rs.tdwg.org/dwc/terms/occurrenceStatus", + "definition": "A statement about the presence or absence of a dwc:Taxon at a dcterms:Location." + }, + "occurrenceRemarks": { + "type": "string", + "nullable": "True", + "long_name": "Occurrence Remarks", + "url": "http://rs.tdwg.org/dwc/terms/occurrenceRemarks", + "definition": "Comments or notes about the dwc:Occurrence." + }, + "organismID": { + "type": "string", + "nullable": "True", + "long_name": "Organism ID", + "url": "http://rs.tdwg.org/dwc/terms/organismID", + "definition": "An identifier for the dwc:Organism instance (as opposed to a particular digital record of the dwc:Organism). May be a globally unique identifier or an identifier specific to the data set." + }, + "fieldNumber": { + "type": "string", + "nullable": "True", + "long_name": "Field Number", + "url": "http://rs.tdwg.org/dwc/terms/fieldNumber", + "definition": "An identifier given to the dwc:Event in the field. Often serves as a link between field notes and the dwc:Event." + }, + "eventDate": { + "type": "date32[day]", + "nullable": "False", + "long_name": "Event Date", + "url": "http://rs.tdwg.org/dwc/terms/eventDate", + "definition": "The date-time or interval during which a dwc:Event occurred. For occurrences, this is the date-time when the dwc:Event was recorded. Not suitable for a time in a geological context." + }, + "country": { + "type": "string", + "nullable": "True", + "long_name": "Country", + "url": "http://rs.tdwg.org/dwc/terms/country", + "definition": "The name of the country or major administrative unit in which the dcterms:Location occurs." + }, + "stateProvince": { + "type": "string", + "nullable": "True", + "long_name": "First Order Division", + "url": "http://rs.tdwg.org/dwc/terms/stateProvince", + "definition": "The name of the next smaller administrative region than country (state, province, canton, department, region, etc.) in which the dcterms:Location occurs." + }, + "locality": { + "type": "string", + "nullable": "True", + "long_name": "Locality", + "url": "http://rs.tdwg.org/dwc/terms/locality", + "definition": "The specific description of the place." + }, + "minimumDepthInMeters": { + "type": "int64", + "nullable": "True", + "long_name": "Minimum Depth In Meters", + "url": "http://rs.tdwg.org/dwc/terms/minimumDepthInMeters", + "definition": "The lesser depth of a range of depth below the local surface, in meters." + }, + "maximumDepthInMeters": { + "type": "int64", + "nullable": "True", + "long_name": "Maximum Depth In Meters", + "url": "http://rs.tdwg.org/dwc/terms/maximumDepthInMeters", + "definition": "The greater depth of a range of depth below the local surface, in meters." + }, + "decimalLatitude": { + "type": "double", + "nullable": "False", + "long_name": "Decimal Latitude", + "url": "http://rs.tdwg.org/dwc/terms/decimalLatitude", + "definition": "The geographic latitude (in decimal degrees, using the spatial reference system given in dwc:geodeticDatum) of the geographic center of a dcterms:Location. Positive values are north of the Equator, negative values are south of it. Legal values lie between -90 and 90, inclusive." + }, + "decimalLongitude": { + "type": "double", + "nullable": "False", + "long_name": "Decimal Longitude", + "url": "http://rs.tdwg.org/dwc/terms/decimalLongitude", + "definition": "The geographic longitude (in decimal degrees, using the spatial reference system given in dwc:geodeticDatum) of the geographic center of a dcterms:Location. Positive values are east of the Greenwich Meridian, negative values are west of it. Legal values lie between -180 and 180, inclusive." + }, + "coordinateUncertaintyInMeters": { + "type": "int64", + "nullable": "True", + "long_name": "Coordinate Uncertainty In Meters", + "url": "http://rs.tdwg.org/dwc/terms/coordinateUncertaintyInMeters", + "definition": "The horizontal distance (in meters) from the given dwc:decimalLatitude and dwc:decimalLongitude describing the smallest circle containing the whole of the dcterms:Location. Leave the value empty if the uncertainty is unknown, cannot be estimated, or is not applicable (because there are no coordinates). Zero is not a valid value for this term." + }, + "footprintWKT": { + "type": "string", + "nullable": "True", + "long_name": "Footprint WKT", + "url": "http://rs.tdwg.org/dwc/terms/footprintWKT", + "definition": "A Well-Known Text (WKT) representation of the shape (footprint, geometry) that defines the dcterms:Location. A dcterms:Location may have both a point-radius representation (see dwc:decimalLatitude) and a footprint representation, and they may differ from each other." + }, + "identifiedBy": { + "type": "string", + "nullable": "True", + "long_name": "Identified By", + "url": "http://rs.tdwg.org/dwc/terms/identifiedBy", + "definition": "A list (concatenated and separated) of names of people, groups, or organizations who assigned the dwc:Taxon to the subject." + }, + "scientificNameID": { + "type": "string", + "nullable": "False", + "long_name": "Scientific Name ID", + "url": "http://rs.tdwg.org/dwc/terms/scientificNameID", + "definition": "An identifier for the nomenclatural (not taxonomic) details of a scientific name." + }, + "scientificName": { + "type": "string", + "nullable": "False", + "long_name": "Scientific Name", + "url": "http://rs.tdwg.org/dwc/terms/scientificName", + "definition": "The full scientific name, with authorship and date information if known. When forming part of a dwc:Identification, this should be the name in lowest level taxonomic rank that can be determined. This term should not contain identification qualifications, which should instead be supplied in the dwc:identificationQualifier term." + }, + "valid_authority": { + "type": "string", + "nullable": "True" + }, + "kingdom": { + "type": "string", + "nullable": "True", + "long_name": "Kingdom", + "url": "http://rs.tdwg.org/dwc/terms/kingdom", + "definition": "The full scientific name of the kingdom in which the dwc:Taxon is classified." + }, + "phylum": { + "type": "string", + "nullable": "True", + "long_name": "Phylum", + "url": "http://rs.tdwg.org/dwc/terms/phylum", + "definition": "The full scientific name of the phylum or division in which the dwc:Taxon is classified." + }, + "class": { + "type": "string", + "nullable": "True", + "long_name": "Class", + "url": "http://rs.tdwg.org/dwc/terms/class", + "definition": "The full scientific name of the class in which the dwc:Taxon is classified." + }, + "order": { + "type": "string", + "nullable": "True", + "long_name": "Order", + "url": "http://rs.tdwg.org/dwc/terms/order", + "definition": "The full scientific name of the order in which the dwc:Taxon is classified." + }, + "family": { + "type": "string", + "nullable": "True", + "long_name": "Family", + "url": "http://rs.tdwg.org/dwc/terms/family", + "definition": "The full scientific name of the family in which the dwc:Taxon is classified." + }, + "genus": { + "type": "string", + "nullable": "True", + "long_name": "Genus", + "url": "http://rs.tdwg.org/dwc/terms/genus", + "definition": "The full scientific name of the genus in which the dwc:Taxon is classified." + }, + "specificEpithet": { + "type": "string", + "nullable": "True", + "long_name": "Specific Epithet", + "url": "http://rs.tdwg.org/dwc/terms/specificEpithet", + "definition": "The name of the first or species epithet of the dwc:scientificName." + }, + "taxonRank": { + "type": "string", + "nullable": "True", + "long_name": "Taxon Rank", + "url": "http://rs.tdwg.org/dwc/terms/taxonRank", + "definition": "The taxonomic rank of the most specific name in the dwc:scientificName." + }, + "scientificNameAuthorship": { + "type": "string", + "nullable": "True", + "long_name": "Scientific Name Authorship", + "url": "http://rs.tdwg.org/dwc/terms/scientificNameAuthorship", + "definition": "The authorship information for the dwc:scientificName formatted according to the conventions of the applicable dwc:nomenclaturalCode." + }, + "vernacularName": { + "type": "string", + "nullable": "True", + "long_name": "Vernacular Name", + "url": "http://rs.tdwg.org/dwc/terms/vernacularName", + "definition": "A common or vernacular name." + }, + "survey_type": { + "type": "string", + "nullable": "False", + "long_name": "Survey Type", + "definition": "The type of survey, one of `Tracking` or `At-sea observations`" + }, + "Wind Direction": { + "type": "double", + "nullable": "True", + "long_name": "Wind from direction in the atmosphere", + "url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-discovery-parameter-vocabulary/version-1-7/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP01%2Fcurrent%2FEWDAZZ01", + "units": "deg", + "units_long_name": "Degrees", + "units_url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-units-of-measure-vocabulary/version-1-1/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP06%2Fcurrent%2FUAAA" + }, + "Air Temperature": { + "type": "double", + "nullable": "True", + "long_name": "Temperature of the atmosphere", + "url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-discovery-parameter-vocabulary/version-1-7/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP01%2Fcurrent%2FCTMPZZ01", + "units": "degC", + "units_long_name": "Degrees Celsius", + "units_url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-units-of-measure-vocabulary/version-1-1/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP06%2Fcurrent%2FUPAA" + }, + "Wind Speed": { + "type": "double", + "nullable": "True", + "long_name": "Wind speed in the atmosphere", + "url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-discovery-parameter-vocabulary/version-1-7/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP01%2Fcurrent%2FESSAZZ01", + "units": "Knots", + "units_long_name": "Knots (nautical miles per hour)", + "units_url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-units-of-measure-vocabulary/version-1-1/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP06%2Fcurrent%2FUKNT" + }, + "Depth": { + "type": "double", + "nullable": "True", + "long_name": "Sea-floor depth below surface of the water body", + "url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-discovery-parameter-vocabulary/version-1-7/resource?uri=http%3A%2F%2Fvocab.aodn.org.au%2Fdef%2Fdiscovery_parameter%2Fentity%2F574", + "units": "m", + "units_long_name": "Metres", + "units_url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-units-of-measure-vocabulary/version-1-1/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP06%2Fcurrent%2FULAA" + }, + "Air Pressure": { + "type": "double", + "nullable": "True", + "long_name": "Pressure (measured variable) exerted by the atmosphere", + "url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-discovery-parameter-vocabulary/version-1-7/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP01%2Fcurrent%2FCAPHZZ01", + "definition": "Measurement as a phenomenon (as opposed to a co-ordinate) of the force per unit area exerted by the atmosphere determined in-situ at a known altitude.", + "units": "hPa", + "units_long_name": "Hectopascals", + "units_url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-units-of-measure-vocabulary/version-1-1/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP06%2Fcurrent%2FHPAX" + }, + "Sea State": { + "type": "string", + "nullable": "True", + "long_name": "Average height of waves on the water body", + "url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-discovery-parameter-vocabulary/version-1-7/resource?uri=http%3A%2F%2Fvocab.aodn.org.au%2Fdef%2Fdiscovery_parameter%2Fentity%2F412", + "units": "m", + "units_long_name": "Metres", + "units_url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-units-of-measure-vocabulary/version-1-1/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP06%2Fcurrent%2FULAA" + }, + "Salinity": { + "type": "double", + "nullable": "True", + "long_name": "Practical salinity of the water body", + "url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-discovery-parameter-vocabulary/version-1-7/resource?uri=http%3A%2F%2Fvocab.nerc.ac.uk%2Fcollection%2FP01%2Fcurrent%2FPSLTZZ01", + "units": "PSU", + "units_long_name": "Practical Salinity Unit", + "units_url": "https://vocabs.ardc.edu.au/repository/api/lda/aodn/aodn-units-of-measure-vocabulary/version-1-1/resource?uri=http%3A%2F%2Fvocab.aodn.org.au%2Fdef%2Funitsofmeasure%2Fentity%2F481" + }, + "Cloud Cover": { + "type": "string", + "nullable": "True", + "long_name": "Cloud Cover Observation Measurements", + "url": "https://vocabs.ardc.edu.au/repository/api/lda/neii/cloud-cover-observation-measurements/version-2-0-agldwg-pid/resource?uri=https%3A%2F%2Flinked.data.gov.au%2Fdef%2Fcloud-cover-observation-measurements", + "definition": "Cloud cover observations are measured in oktas (eighths). The sky is visually inspected to produce an estimate of the number of eighths of the dome of the sky covered by cloud. The presence of any trace of cloud in an otherwise blue sky is recorded as 1 okta, and similarly any trace of blue on an otherwise cloudy sky is recorded as 7." + } + }, + "aws_opendata_registry": { + "Name": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Description": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Documentation": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Contact": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "ManagedBy": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "UpdateFrequency": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Tags": [ + "FILL UP MANUALLY - CHECK DOCUMENTATION" + ], + "License": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Resources": [ + { + "Description": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "ARN": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Region": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Type": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Explore": [ + "FILL UP MANUALLY - CHECK DOCUMENTATION" + ] + } + ], + "DataAtWork": { + "Tutorials": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Services": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorURL": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ], + "Tools & Applications": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorURL": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ], + "Publications": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ] + } + }, + "schema_transformation": { + "drop_variables": [], + "add_variables": { + "filename": { + "source": "@filename", + "schema": { + "type": "string", + "units": "1", + "long_name": "Filename of the source file" + } + }, + "timestamp": { + "source": "@partitioning:time_extent", + "schema": { + "type": "int64", + "units": "1", + "long_name": "Partition timestamp" + } + }, + "polygon": { + "source": "@partitioning:spatial_extent", + "schema": { + "type": "string", + "units": "1", + "long_name": "Spatial partition polygon" + } + } + }, + "partitioning": [ + { + "source_variable": "timestamp", + "type": "time_extent", + "time_extent": { + "time_varname": "eventDate", + "partition_period": "Y" + } + }, + { + "source_variable": "polygon", + "type": "spatial_extent", + "spatial_extent": { + "lat_varname": "decimalLatitude", + "lon_varname": "decimalLongitude", + "spatial_resolution": 90 + } + } + ], + "global_attributes": { + "set": { + "title": "IMOS - Aggregated Seabird Data Product" + } + } + } +} diff --git a/aodn_cloud_optimised/config/dataset/aggregated_seagrass_nonqc.json b/aodn_cloud_optimised/config/dataset/aggregated_seagrass_nonqc.json new file mode 100644 index 00000000..6f110c1e --- /dev/null +++ b/aodn_cloud_optimised/config/dataset/aggregated_seagrass_nonqc.json @@ -0,0 +1,236 @@ +{ + "dataset_name": "aggregated_seagrass_nonqc", + "logger_name": "aggregated_seagrass_nonqc", + "cloud_optimised_format": "parquet", + "run_settings": { + "paths": [ + { + "type": "parquet", + "partitioning": null, + "s3_uri": "s3://aodn-processing/stored/datauplift/seagrass/seagrass.parquet" + } + ], + "cluster": { + "mode": "local", + "restart_every_path": false + }, + "clear_existing_data": true, + "raise_error": false, + "batch_size": 4, + "force_previous_parquet_deletion": false + }, + "metadata_uuid": null, + "schema": { + "source": { + "type": "string", + "nullable": "False", + "description": "The source dataset name" + }, + "source_id": { + "type": "string", + "nullable": "False", + "description": "The source dataset row id" + }, + "metadata_link": { + "type": "string", + "nullable": "False", + "description": "The source dataset metadata link" + }, + "start_year": { + "type": "int16", + "nullable": "False", + "description": "The start year of the measurement" + }, + "start_month": { + "type": "int8", + "nullable": "True", + "description": "The start month of the measurement" + }, + "start_day": { + "type": "int8", + "nullable": "True", + "description": "The start day of the measurement" + }, + "end_year": { + "type": "int16", + "nullable": "True", + "description": "The end year of the measurement (if applicable)" + }, + "end_month": { + "type": "int8", + "nullable": "True", + "description": "The end month of the measurement (if applicable)" + }, + "end_day": { + "type": "int8", + "nullable": "True", + "description": "The end day of the measurement (if applicable)" + }, + "geometry": { + "type": "string", + "nullable": "False", + "description": "The WKT encoded geometry of the measurement" + }, + "lat": { + "type": "float", + "nullable": "False", + "description": "The latitude of the measurement, taken from the centroid of the geometry" + }, + "lon": { + "type": "float", + "nullable": "False", + "description": "The longitude of the measurement, taken from the centroid of the geometry" + }, + "h3_cell_15": { + "type": "string", + "nullable": "False", + "description": "The h3 cell corresponding to the measurement" + }, + "australian_marine_regions_tags": { + "type": "string", + "nullable": "True", + "description": "The australian marine regions tags found applicable to the measurement" + }, + "present": { + "type": "bool", + "nullable": "False", + "description": "The presence of the species of the measurement" + }, + "biomass": { + "type": "float", + "nullable": "True", + "description": "The biomass of the species of the measurement (if applicable, most studies only measure presence)", + "unit": "gdw/m^2" + }, + "scientific_name": { + "type": "string", + "nullable": "False", + "description": "The scientific name of the measurement, as per WoRMS catalogue" + }, + "aphia_id": { + "type": "int64", + "nullable": "False", + "description": "The scientific name aphia id of the measurement, as per WoRMS catalogue" + }, + "rank": { + "type": "string", + "nullable": "False", + "description": "The taxon rank of the measurement, as per WoRMS catalogue" + }, + "status": { + "type": "string", + "nullable": "False", + "description": "The taxon acceptance of the measurement, as per WoRMS catalogue" + } + }, + "aws_opendata_registry": { + "Name": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Description": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Documentation": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Contact": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "ManagedBy": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "UpdateFrequency": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Tags": [ + "FILL UP MANUALLY - CHECK DOCUMENTATION" + ], + "License": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Resources": [ + { + "Description": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "ARN": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Region": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Type": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Explore": [ + "FILL UP MANUALLY - CHECK DOCUMENTATION" + ] + } + ], + "DataAtWork": { + "Tutorials": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "Services": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorURL": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ], + "Tools & Applications": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorURL": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ], + "Publications": [ + { + "Title": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "URL": "FILL UP MANUALLY - CHECK DOCUMENTATION", + "AuthorName": "FILL UP MANUALLY - CHECK DOCUMENTATION" + } + ] + } + }, + "schema_transformation": { + "drop_variables": [], + "add_variables": { + "filename": { + "source": "@filename", + "schema": { + "type": "string", + "units": "1", + "long_name": "Filename of the source file" + } + }, + "timestamp": { + "source": "@function:year_to_datetime", + "schema": { + "type": "int64", + "units": "1", + "long_name": "Partition timestamp" + } + }, + "polygon": { + "source": "@partitioning:spatial_extent", + "schema": { + "type": "string", + "units": "1", + "long_name": "Spatial partition polygon" + } + } + }, + "functions": { + "year_to_datetime": { + "extract_method": "from_variables", + "method": { + "creation_code": "def time_creation_from_variables(df): import pandas; return pandas.to_datetime(df[\"start_year\"],format=\"%Y\")" + } + } + }, + "partitioning": [ + { + "source_variable": "timestamp", + "type": "time_extent", + "time_extent": { + "time_varname": "timestamp", + "partition_period": "Y" + } + }, + { + "source_variable": "polygon", + "type": "spatial_extent", + "spatial_extent": { + "lat_varname": "lat", + "lon_varname": "lon", + "spatial_resolution": 90 + } + } + ], + "global_attributes": { + "set": { + "title": "IMOS - Aggregated Seagrass Data Product" + } + } + } +} diff --git a/aodn_cloud_optimised/config/dataset/diver_photoquadrat_score_qc.json b/aodn_cloud_optimised/config/dataset/diver_photoquadrat_score_qc.json index 2c2dcb22..d232d999 100644 --- a/aodn_cloud_optimised/config/dataset/diver_photoquadrat_score_qc.json +++ b/aodn_cloud_optimised/config/dataset/diver_photoquadrat_score_qc.json @@ -5,8 +5,8 @@ "run_settings": { "paths": [ { - "type": "parquet", - "s3_uri": "s3://data-uplift-public/products/reef_life_survey/public_reef_life_survey_2025-11-04T03:14:37.parquet" + "s3_uri": "s3://aodn-processing/stored/datauplift/nrmn/public/ep_m13_pq_scores.parquet", + "type": "parquet" } ], "cluster": { @@ -15,7 +15,7 @@ }, "clear_existing_data": true, "raise_error": false, - "batch_size": 5, + "batch_size": 4, "force_previous_parquet_deletion": false }, "metadata_uuid": "0a65be6d-1c76-49ac-a151-80acf123612c", @@ -158,14 +158,14 @@ "col_tags": "annotation|label|tag" }, "label_count": { - "type": "double", + "type": "int64", "nullable": "True", "long_name": "Count of organisms", "standard_name": "count", "col_tags": "annotation|coverage" }, "dataset_total_label_count": { - "type": "double", + "type": "int64", "nullable": "True", "long_name": "Label Count", "col_tags": "annotation|coverage" @@ -179,12 +179,12 @@ "col_tags": "annotation|coverage" }, "sq_annotation_set_id": { - "type": "double", + "type": "int64", "nullable": "True", "long_name": "SQ Annotation Set Identifier", "col_tags": "squidle|survey metadata" }, - "method": { + "annotation_method": { "type": "string", "nullable": "True", "long_name": "Annotation Method", @@ -274,7 +274,7 @@ "type": "time_extent", "time_extent": { "time_varname": "date", - "partition_period": "M" + "partition_period": "Y" } }, { @@ -283,18 +283,11 @@ "spatial_extent": { "lat_varname": "latitude", "lon_varname": "longitude", - "spatial_resolution": 5 + "spatial_resolution": 90 } } ], "global_attributes": { - "delete": [ - "geospatial_lat_max", - "geospatial_lat_min", - "geospatial_lon_max", - "geospatial_lon_min", - "date_created" - ], "set": { "title": "IMOS - National Reef Monitoring Network Sub-Facility - Photo Quadrat Scores" } diff --git a/notebooks/README.md b/notebooks/README.md index 3fb22da0..06dc66de 100644 --- a/notebooks/README.md +++ b/notebooks/README.md @@ -56,6 +56,9 @@ More information available [here](https://github.com/conda-forge/miniforge?tab=r # AODN Notebooks directly loadable into Google Colab +- [aggregated_kelp_nonqc.ipynb](https://githubtocolab.com/aodn/aodn_cloud_optimised/blob/main/notebooks/aggregated_kelp_nonqc.ipynb) +- [aggregated_seabird_nonqc.ipynb](https://githubtocolab.com/aodn/aodn_cloud_optimised/blob/main/notebooks/aggregated_seabird_nonqc.ipynb) +- [aggregated_seagrass_nonqc.ipynb](https://githubtocolab.com/aodn/aodn_cloud_optimised/blob/main/notebooks/aggregated_seagrass_nonqc.ipynb) - [amsa_vessel_tracking.ipynb](https://githubtocolab.com/aodn/aodn_cloud_optimised/blob/main/notebooks/amsa_vessel_tracking.ipynb) - [animal_acoustic_tracking_delayed_qc.ipynb](https://githubtocolab.com/aodn/aodn_cloud_optimised/blob/main/notebooks/animal_acoustic_tracking_delayed_qc.ipynb) - [animal_ctd_satellite_relay_tagging_delayed_qc.ipynb](https://githubtocolab.com/aodn/aodn_cloud_optimised/blob/main/notebooks/animal_ctd_satellite_relay_tagging_delayed_qc.ipynb) diff --git a/notebooks/aggregated_kelp_nonqc.ipynb b/notebooks/aggregated_kelp_nonqc.ipynb new file mode 100644 index 00000000..4d98d786 --- /dev/null +++ b/notebooks/aggregated_kelp_nonqc.ipynb @@ -0,0 +1,287 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a76be700", + "metadata": {}, + "source": [ + "## Access Aggregated Kelp Nonqc (Parquet)\n", + "This Jupyter notebook demonstrates how to access and plot aggregated_kelp_nonqc data, available as a [Parquet](https://parquet.apache.org) dataset stored on S3.\n", + "\n", + "🔗 More information about the dataset is available [in the AODN metadata catalogue](https://catalogue-imos.aodn.org.au/geonetwork/srv/eng/catalog.search#/metadata/None).\n", + "\n", + "📌 The source of truth for this notebook is maintained on [GitHub](https://github.com/aodn/aodn_cloud_optimised/tree/main/notebooks/aggregated_kelp_nonqc.ipynb).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f734baa1", + "metadata": {}, + "outputs": [], + "source": [ + "dataset_name = \"aggregated_kelp_nonqc\"" + ] + }, + { + "cell_type": "markdown", + "id": "19149b31", + "metadata": {}, + "source": [ + "## Install/Update packages and Load common functions" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "38a4f0a8", + "metadata": {}, + "outputs": [], + "source": [ + "import os, requests, importlib.util\n", + "\n", + "open('setup.py', 'w').write(requests.get('https://raw.githubusercontent.com/aodn/aodn_cloud_optimised/main/notebooks/setup.py').text)\n", + "\n", + "spec = importlib.util.spec_from_file_location(\"setup\", \"setup.py\")\n", + "setup = importlib.util.module_from_spec(spec)\n", + "spec.loader.exec_module(setup)\n", + "\n", + "setup.install_requirements()\n", + "setup.load_dataquery()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e3930fce", + "metadata": {}, + "outputs": [], + "source": [ + "from DataQuery import GetAodn" + ] + }, + { + "cell_type": "markdown", + "id": "44a5f77f", + "metadata": {}, + "source": [ + "# Understanding the Dataset" + ] + }, + { + "cell_type": "markdown", + "id": "61655f7a", + "metadata": {}, + "source": [ + "## Understanding Parquet Partitioning\n", + "\n", + "Parquet files can be **partitioned** by one or more columns, which means the data is physically organised into folders based on the values in those columns. This is similar to how databases use indexes to optimise query performance.\n", + "\n", + "Partitioning enables **faster filtering**: when you query data using a partitioned column, only the relevant subset of files needs to be read—improving performance significantly.\n", + "\n", + "For example, if a dataset is partitioned by `\"site_code\"`, `\"timestamp\"`, and `\"polygon\"`, filtering on `\"site_code\"` allows the system to skip unrelated files entirely.\n", + "\n", + "In this notebook, the `GetAodn` class includes built-in methods to efficiently filter data by **time** and **latitude/longitude** using the **timestamp** and **polygon** partitions. Other partitions can be used for filtering via the `scalar_filter`.\n", + "\n", + "Any filtering on columns that are **not** partitioned can be significantly slower, as all files may need to be scanned. However, the `GetAodn` class provides a `scalar_filter` method that lets you apply these filters at load time—before the data is fully read—helping reduce the size of the resulting DataFrame.\n", + "\n", + "Once the dataset is loaded, further filtering using Pandas is efficient and flexible.\n", + "\n", + "See further below in the notebook for examples of how to filter the data effectively.\n", + "\n", + "To view the actual partition columns for this dataset, run:\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b2e5ec94", + "metadata": {}, + "outputs": [], + "source": [ + "aodn = GetAodn()\n", + "dname = f'{dataset_name}.parquet'\n", + "%time aodn_dataset = aodn.get_dataset(dname)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8c1c5ac", + "metadata": {}, + "outputs": [], + "source": [ + "aodn_dataset.dataset.partitioning.schema" + ] + }, + { + "cell_type": "markdown", + "id": "56bf9a8a", + "metadata": {}, + "source": [ + "## List unique partition values" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "91df87e9", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "unique_partition_value = aodn_dataset.get_unique_partition_values('YOUR_PARTITION_KEY')\n", + "print(list(unique_partition_value)[0:2]) # showing a subset only" + ] + }, + { + "cell_type": "markdown", + "id": "d50a003a", + "metadata": {}, + "source": [ + "## Visualise Spatial Extent of the dataset\n", + "This section plots the polygons representing the areas where data is available. It helps to identify and create a bounding box around the regions containing data." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "14239bed", + "metadata": {}, + "outputs": [], + "source": [ + "aodn_dataset.plot_spatial_extent()" + ] + }, + { + "cell_type": "markdown", + "id": "34c36715", + "metadata": {}, + "source": [ + "## Get Temporal Extent of the dataset" + ] + }, + { + "cell_type": "markdown", + "id": "e1299d72", + "metadata": {}, + "source": [ + "Similary to the spatial extent, we're retrieving the minimum and maximum timestamp partition values of the dataset. This is not necessarely accurately representative of the TIME values, as the timestamp partition can be yearly/monthly... but is here to give an idea" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3c2c77b8", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "aodn_dataset.get_temporal_extent()" + ] + }, + { + "cell_type": "markdown", + "id": "b866c439", + "metadata": {}, + "source": [ + "## Read Metadata\n", + "\n", + "For all Parquet datasets, we create a sidecar file named **_common_metadata** in the root of the dataset. This file contains both the dataset-level and variable-level attributes. \n", + "The metadata can be retrieved below as a dictionary, and it will also be included in the pandas DataFrame when using the `get_data` method from the `GetAodn` class." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4d02ca37", + "metadata": {}, + "outputs": [], + "source": [ + "metadata = aodn_dataset.get_metadata()\n", + "metadata" + ] + }, + { + "cell_type": "markdown", + "id": "1c89d027", + "metadata": {}, + "source": [ + "# Data Query and Plot" + ] + }, + { + "cell_type": "markdown", + "id": "8d1a1b83", + "metadata": {}, + "source": [ + "## Create a TIME and BoundingBox filter\n", + "\n", + "This cell loads a subset of the dataset based on a time range and a spatial bounding box. The result is returned as a pandas DataFrame, and basic information about its structure is displayed." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bbb5bb8a", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "df = aodn_dataset.get_data(date_start='2022-12-01', \n", + " date_end='2023-01-01',\n", + " lat_min=-34, \n", + " lat_max=-28, \n", + " lon_min=151, \n", + " lon_max=160, \n", + " )\n", + "\n", + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ba744653", + "metadata": {}, + "outputs": [], + "source": [ + "## Download Subsetted Data as CSV\n", + "\n", + "# This cell downloads the filtered dataset as a ZIP-compressed CSV file. \n", + "# The CSV includes metadata at the top as commented lines, and a `FileLink` object is returned to allow downloading directly from the notebook.\n", + "\n", + "\n", + "df.aodn.download_as_csv()" + ] + }, + { + "cell_type": "markdown", + "id": "683d1e18", + "metadata": {}, + "source": [ + "## Create a TIME and scalar/number filter\n", + "\n", + "This cell filters the dataset by time range and a scalar value (from a Parquet partition) using the `scalar_filter` argument. \n", + "This leverages Parquet partitioning to apply efficient, server-side filtering, which significantly speeds up data loading." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6e100b61", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "df = aodn_dataset.get_data(date_start='2006-07-12', \n", + " date_end='2023-02-05',\n", + " scalar_filter={'YOUR_PARTITION_KEY': 1901740})\n", + "df.info()" + ] + } + ], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/aggregated_seabird_nonqc.ipynb b/notebooks/aggregated_seabird_nonqc.ipynb new file mode 100644 index 00000000..5b9eedfa --- /dev/null +++ b/notebooks/aggregated_seabird_nonqc.ipynb @@ -0,0 +1,287 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3f77d1ce", + "metadata": {}, + "source": [ + "## Access Aggregated Seabird Nonqc (Parquet)\n", + "This Jupyter notebook demonstrates how to access and plot aggregated_seabird_nonqc data, available as a [Parquet](https://parquet.apache.org) dataset stored on S3.\n", + "\n", + "🔗 More information about the dataset is available [in the AODN metadata catalogue](https://catalogue-imos.aodn.org.au/geonetwork/srv/eng/catalog.search#/metadata/None).\n", + "\n", + "📌 The source of truth for this notebook is maintained on [GitHub](https://github.com/aodn/aodn_cloud_optimised/tree/main/notebooks/aggregated_seabird_nonqc.ipynb).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dcb09bf7", + "metadata": {}, + "outputs": [], + "source": [ + "dataset_name = \"aggregated_seabird_nonqc\"" + ] + }, + { + "cell_type": "markdown", + "id": "9017dc7c", + "metadata": {}, + "source": [ + "## Install/Update packages and Load common functions" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5dc0d3e2", + "metadata": {}, + "outputs": [], + "source": [ + "import os, requests, importlib.util\n", + "\n", + "open('setup.py', 'w').write(requests.get('https://raw.githubusercontent.com/aodn/aodn_cloud_optimised/main/notebooks/setup.py').text)\n", + "\n", + "spec = importlib.util.spec_from_file_location(\"setup\", \"setup.py\")\n", + "setup = importlib.util.module_from_spec(spec)\n", + "spec.loader.exec_module(setup)\n", + "\n", + "setup.install_requirements()\n", + "setup.load_dataquery()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "253038ce", + "metadata": {}, + "outputs": [], + "source": [ + "from DataQuery import GetAodn" + ] + }, + { + "cell_type": "markdown", + "id": "35f0e3a2", + "metadata": {}, + "source": [ + "# Understanding the Dataset" + ] + }, + { + "cell_type": "markdown", + "id": "1eb12a96", + "metadata": {}, + "source": [ + "## Understanding Parquet Partitioning\n", + "\n", + "Parquet files can be **partitioned** by one or more columns, which means the data is physically organised into folders based on the values in those columns. This is similar to how databases use indexes to optimise query performance.\n", + "\n", + "Partitioning enables **faster filtering**: when you query data using a partitioned column, only the relevant subset of files needs to be read—improving performance significantly.\n", + "\n", + "For example, if a dataset is partitioned by `\"site_code\"`, `\"timestamp\"`, and `\"polygon\"`, filtering on `\"site_code\"` allows the system to skip unrelated files entirely.\n", + "\n", + "In this notebook, the `GetAodn` class includes built-in methods to efficiently filter data by **time** and **latitude/longitude** using the **timestamp** and **polygon** partitions. Other partitions can be used for filtering via the `scalar_filter`.\n", + "\n", + "Any filtering on columns that are **not** partitioned can be significantly slower, as all files may need to be scanned. However, the `GetAodn` class provides a `scalar_filter` method that lets you apply these filters at load time—before the data is fully read—helping reduce the size of the resulting DataFrame.\n", + "\n", + "Once the dataset is loaded, further filtering using Pandas is efficient and flexible.\n", + "\n", + "See further below in the notebook for examples of how to filter the data effectively.\n", + "\n", + "To view the actual partition columns for this dataset, run:\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "91501547", + "metadata": {}, + "outputs": [], + "source": [ + "aodn = GetAodn()\n", + "dname = f'{dataset_name}.parquet'\n", + "%time aodn_dataset = aodn.get_dataset(dname)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5350e456", + "metadata": {}, + "outputs": [], + "source": [ + "aodn_dataset.dataset.partitioning.schema" + ] + }, + { + "cell_type": "markdown", + "id": "137e2880", + "metadata": {}, + "source": [ + "## List unique partition values" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "39950040", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "unique_partition_value = aodn_dataset.get_unique_partition_values('YOUR_PARTITION_KEY')\n", + "print(list(unique_partition_value)[0:2]) # showing a subset only" + ] + }, + { + "cell_type": "markdown", + "id": "fbc0ebe0", + "metadata": {}, + "source": [ + "## Visualise Spatial Extent of the dataset\n", + "This section plots the polygons representing the areas where data is available. It helps to identify and create a bounding box around the regions containing data." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "15f8dfd2", + "metadata": {}, + "outputs": [], + "source": [ + "aodn_dataset.plot_spatial_extent()" + ] + }, + { + "cell_type": "markdown", + "id": "c0b44462", + "metadata": {}, + "source": [ + "## Get Temporal Extent of the dataset" + ] + }, + { + "cell_type": "markdown", + "id": "747cc97c", + "metadata": {}, + "source": [ + "Similary to the spatial extent, we're retrieving the minimum and maximum timestamp partition values of the dataset. This is not necessarely accurately representative of the TIME values, as the timestamp partition can be yearly/monthly... but is here to give an idea" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7426bfc8", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "aodn_dataset.get_temporal_extent()" + ] + }, + { + "cell_type": "markdown", + "id": "ff3bd4dd", + "metadata": {}, + "source": [ + "## Read Metadata\n", + "\n", + "For all Parquet datasets, we create a sidecar file named **_common_metadata** in the root of the dataset. This file contains both the dataset-level and variable-level attributes. \n", + "The metadata can be retrieved below as a dictionary, and it will also be included in the pandas DataFrame when using the `get_data` method from the `GetAodn` class." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2263479b", + "metadata": {}, + "outputs": [], + "source": [ + "metadata = aodn_dataset.get_metadata()\n", + "metadata" + ] + }, + { + "cell_type": "markdown", + "id": "3c92d38a", + "metadata": {}, + "source": [ + "# Data Query and Plot" + ] + }, + { + "cell_type": "markdown", + "id": "84e53091", + "metadata": {}, + "source": [ + "## Create a TIME and BoundingBox filter\n", + "\n", + "This cell loads a subset of the dataset based on a time range and a spatial bounding box. The result is returned as a pandas DataFrame, and basic information about its structure is displayed." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f53a83c9", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "df = aodn_dataset.get_data(date_start='2022-12-01', \n", + " date_end='2023-01-01',\n", + " lat_min=-34, \n", + " lat_max=-28, \n", + " lon_min=151, \n", + " lon_max=160, \n", + " )\n", + "\n", + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e06bfeb1", + "metadata": {}, + "outputs": [], + "source": [ + "## Download Subsetted Data as CSV\n", + "\n", + "# This cell downloads the filtered dataset as a ZIP-compressed CSV file. \n", + "# The CSV includes metadata at the top as commented lines, and a `FileLink` object is returned to allow downloading directly from the notebook.\n", + "\n", + "\n", + "df.aodn.download_as_csv()" + ] + }, + { + "cell_type": "markdown", + "id": "e5a899c7", + "metadata": {}, + "source": [ + "## Create a TIME and scalar/number filter\n", + "\n", + "This cell filters the dataset by time range and a scalar value (from a Parquet partition) using the `scalar_filter` argument. \n", + "This leverages Parquet partitioning to apply efficient, server-side filtering, which significantly speeds up data loading." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "03efb372", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "df = aodn_dataset.get_data(date_start='2006-07-12', \n", + " date_end='2023-02-05',\n", + " scalar_filter={'YOUR_PARTITION_KEY': 1901740})\n", + "df.info()" + ] + } + ], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/aggregated_seagrass_nonqc.ipynb b/notebooks/aggregated_seagrass_nonqc.ipynb new file mode 100644 index 00000000..b53984f2 --- /dev/null +++ b/notebooks/aggregated_seagrass_nonqc.ipynb @@ -0,0 +1,287 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "13bbe6f8", + "metadata": {}, + "source": [ + "## Access Aggregated Seagrass Nonqc (Parquet)\n", + "This Jupyter notebook demonstrates how to access and plot aggregated_seagrass_nonqc data, available as a [Parquet](https://parquet.apache.org) dataset stored on S3.\n", + "\n", + "🔗 More information about the dataset is available [in the AODN metadata catalogue](https://catalogue-imos.aodn.org.au/geonetwork/srv/eng/catalog.search#/metadata/None).\n", + "\n", + "📌 The source of truth for this notebook is maintained on [GitHub](https://github.com/aodn/aodn_cloud_optimised/tree/main/notebooks/aggregated_seagrass_nonqc.ipynb).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fb22d170", + "metadata": {}, + "outputs": [], + "source": [ + "dataset_name = \"aggregated_seagrass_nonqc\"" + ] + }, + { + "cell_type": "markdown", + "id": "762f84e8", + "metadata": {}, + "source": [ + "## Install/Update packages and Load common functions" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6c843df1", + "metadata": {}, + "outputs": [], + "source": [ + "import os, requests, importlib.util\n", + "\n", + "open('setup.py', 'w').write(requests.get('https://raw.githubusercontent.com/aodn/aodn_cloud_optimised/main/notebooks/setup.py').text)\n", + "\n", + "spec = importlib.util.spec_from_file_location(\"setup\", \"setup.py\")\n", + "setup = importlib.util.module_from_spec(spec)\n", + "spec.loader.exec_module(setup)\n", + "\n", + "setup.install_requirements()\n", + "setup.load_dataquery()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a33a7f5a", + "metadata": {}, + "outputs": [], + "source": [ + "from DataQuery import GetAodn" + ] + }, + { + "cell_type": "markdown", + "id": "aa76f2a4", + "metadata": {}, + "source": [ + "# Understanding the Dataset" + ] + }, + { + "cell_type": "markdown", + "id": "8cdc1325", + "metadata": {}, + "source": [ + "## Understanding Parquet Partitioning\n", + "\n", + "Parquet files can be **partitioned** by one or more columns, which means the data is physically organised into folders based on the values in those columns. This is similar to how databases use indexes to optimise query performance.\n", + "\n", + "Partitioning enables **faster filtering**: when you query data using a partitioned column, only the relevant subset of files needs to be read—improving performance significantly.\n", + "\n", + "For example, if a dataset is partitioned by `\"site_code\"`, `\"timestamp\"`, and `\"polygon\"`, filtering on `\"site_code\"` allows the system to skip unrelated files entirely.\n", + "\n", + "In this notebook, the `GetAodn` class includes built-in methods to efficiently filter data by **time** and **latitude/longitude** using the **timestamp** and **polygon** partitions. Other partitions can be used for filtering via the `scalar_filter`.\n", + "\n", + "Any filtering on columns that are **not** partitioned can be significantly slower, as all files may need to be scanned. However, the `GetAodn` class provides a `scalar_filter` method that lets you apply these filters at load time—before the data is fully read—helping reduce the size of the resulting DataFrame.\n", + "\n", + "Once the dataset is loaded, further filtering using Pandas is efficient and flexible.\n", + "\n", + "See further below in the notebook for examples of how to filter the data effectively.\n", + "\n", + "To view the actual partition columns for this dataset, run:\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9c421ea5", + "metadata": {}, + "outputs": [], + "source": [ + "aodn = GetAodn()\n", + "dname = f'{dataset_name}.parquet'\n", + "%time aodn_dataset = aodn.get_dataset(dname)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5311245c", + "metadata": {}, + "outputs": [], + "source": [ + "aodn_dataset.dataset.partitioning.schema" + ] + }, + { + "cell_type": "markdown", + "id": "54ba70d3", + "metadata": {}, + "source": [ + "## List unique partition values" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b34e14d2", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "unique_partition_value = aodn_dataset.get_unique_partition_values('YOUR_PARTITION_KEY')\n", + "print(list(unique_partition_value)[0:2]) # showing a subset only" + ] + }, + { + "cell_type": "markdown", + "id": "9e465377", + "metadata": {}, + "source": [ + "## Visualise Spatial Extent of the dataset\n", + "This section plots the polygons representing the areas where data is available. It helps to identify and create a bounding box around the regions containing data." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8d12dea4", + "metadata": {}, + "outputs": [], + "source": [ + "aodn_dataset.plot_spatial_extent()" + ] + }, + { + "cell_type": "markdown", + "id": "98f8d761", + "metadata": {}, + "source": [ + "## Get Temporal Extent of the dataset" + ] + }, + { + "cell_type": "markdown", + "id": "8fafa0a2", + "metadata": {}, + "source": [ + "Similary to the spatial extent, we're retrieving the minimum and maximum timestamp partition values of the dataset. This is not necessarely accurately representative of the TIME values, as the timestamp partition can be yearly/monthly... but is here to give an idea" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "968273ad", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "aodn_dataset.get_temporal_extent()" + ] + }, + { + "cell_type": "markdown", + "id": "8092d6f4", + "metadata": {}, + "source": [ + "## Read Metadata\n", + "\n", + "For all Parquet datasets, we create a sidecar file named **_common_metadata** in the root of the dataset. This file contains both the dataset-level and variable-level attributes. \n", + "The metadata can be retrieved below as a dictionary, and it will also be included in the pandas DataFrame when using the `get_data` method from the `GetAodn` class." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "edf63455", + "metadata": {}, + "outputs": [], + "source": [ + "metadata = aodn_dataset.get_metadata()\n", + "metadata" + ] + }, + { + "cell_type": "markdown", + "id": "0b2d082f", + "metadata": {}, + "source": [ + "# Data Query and Plot" + ] + }, + { + "cell_type": "markdown", + "id": "85d038a3", + "metadata": {}, + "source": [ + "## Create a TIME and BoundingBox filter\n", + "\n", + "This cell loads a subset of the dataset based on a time range and a spatial bounding box. The result is returned as a pandas DataFrame, and basic information about its structure is displayed." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5b377a02", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "df = aodn_dataset.get_data(date_start='2022-12-01', \n", + " date_end='2023-01-01',\n", + " lat_min=-34, \n", + " lat_max=-28, \n", + " lon_min=151, \n", + " lon_max=160, \n", + " )\n", + "\n", + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9739ca4b", + "metadata": {}, + "outputs": [], + "source": [ + "## Download Subsetted Data as CSV\n", + "\n", + "# This cell downloads the filtered dataset as a ZIP-compressed CSV file. \n", + "# The CSV includes metadata at the top as commented lines, and a `FileLink` object is returned to allow downloading directly from the notebook.\n", + "\n", + "\n", + "df.aodn.download_as_csv()" + ] + }, + { + "cell_type": "markdown", + "id": "596e4f7e", + "metadata": {}, + "source": [ + "## Create a TIME and scalar/number filter\n", + "\n", + "This cell filters the dataset by time range and a scalar value (from a Parquet partition) using the `scalar_filter` argument. \n", + "This leverages Parquet partitioning to apply efficient, server-side filtering, which significantly speeds up data loading." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bcc43c9c", + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "df = aodn_dataset.get_data(date_start='2006-07-12', \n", + " date_end='2023-02-05',\n", + " scalar_filter={'YOUR_PARTITION_KEY': 1901740})\n", + "df.info()" + ] + } + ], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/diver_photoquadrat_score_qc.ipynb b/notebooks/diver_photoquadrat_score_qc.ipynb index 435e4c94..4c9e3b7a 100644 --- a/notebooks/diver_photoquadrat_score_qc.ipynb +++ b/notebooks/diver_photoquadrat_score_qc.ipynb @@ -74,7 +74,17 @@ "id": "36a34c34", "metadata": {}, "source": [ - "# Understanding the Dataset" + "# Understanding the Dataset\n", + "\n", + "## Background\n", + "\n", + "### What is the diver_photoquadrat_score_qc Dataset?\n", + "\n", + "The Reef Life Survey (RLS) is a non-profit, global citizen science program that utilizes trained volunteer SCUBA divers and snorkelers to monitor the health of marine ecosystems worldwide.\n", + "\n", + "It essentially acts as one of the world's largest standardized \"ocean censuses.\" Volunteers follow strict methods to collect high-quality data on rocky and coral reefs, recording three main types of information: the abundance of fish, the presence of mobile invertebrates (like sea stars and lobsters), and the composition of the reef's seafloor (such as coral and algae cover).\n", + "\n", + "With surveys spanning dozens of countries, the data collected provides an essential snapshot of marine biodiversity and ecosystem health. Scientists, conservationists, and governments rely on the RLS database to track long-term changes, assess the effectiveness of marine protected areas (MPAs), and study the impacts of environmental pressures like climate change and pollution. The program makes its data and resources, like the Reef Species of the World online field guide, accessible for global research and conservation efforts." ] }, { @@ -103,7 +113,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "5dda6eac", "metadata": {}, "outputs": [ @@ -124,7 +134,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "c3edeb26", "metadata": {}, "outputs": [ @@ -154,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "57cdac44", "metadata": {}, "outputs": [ @@ -185,7 +195,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "ac02c762", "metadata": {}, "outputs": [ @@ -199,7 +209,7 @@ }, { "data": { - "image/png": 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\n", 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", 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" ] @@ -230,7 +240,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "3500c4dc", "metadata": {}, "outputs": [ @@ -271,7 +281,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "a545aa15", "metadata": {}, "outputs": [ diff --git a/pyproject.toml b/pyproject.toml index 0374b73b..834f0868 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -95,6 +95,9 @@ tqdm = ">=4.67.1" [project.scripts] #cloud_optimised_srs_oc_ljco_to_parquet = "aodn_cloud_optimised.bin.srs_oc_ljco_to_parquet:main" +cloud_optimised_aggregated_kelp_nonqc = "aodn_cloud_optimised.bin.aggregated_kelp_nonqc:main" +cloud_optimised_aggregated_seabird_nonqc = "aodn_cloud_optimised.bin.aggregated_seabird_nonqc:main" +cloud_optimised_aggregated_seagrass_nonqc = "aodn_cloud_optimised.bin.aggregated_seagrass_nonqc:main" cloud_optimised_amsa_vessel_tracking = "aodn_cloud_optimised.bin.amsa_vessel_tracking:main" cloud_optimised_animal_acoustic_tracking_delayed_qc = "aodn_cloud_optimised.bin.animal_acoustic_tracking_delayed_qc:main" cloud_optimised_animal_ctd_satellite_relay_tagging_delayed_qc = "aodn_cloud_optimised.bin.animal_ctd_satellite_relay_tagging_delayed_qc:main"