Changelog

peskas.timor.data.pipeline 3.2.0

Improvements

• Align variables to the Aquatic Food Ontology (AQFO)

peskas.timor.data.pipeline 3.1.0

Improvements

• Estimations are now weighted based on the number of records in each monthly bin. This improve the accuracy of estimations and reduce outliers effect.

peskas.timor.data.pipeline 3.0.0

New features

• Integrated the ingestion of the new survey form “Peskas 2”. The new form was deployed with the aim to be more manageable for enumerators. It also includes some more questions regarding the fish handling and trading.

peskas.timor.data.pipeline 2.0.0

Breaking changes

• Validation step in now implemented using google sheets using the googlesheets4 package.

peskas.timor.data.pipeline 1.4.0

Improvements

• Improve national and municipal estimates combining packags Amelia and mice for missing and outliers data imputation.

• Integrating price per kg into export data

Bug fixes

• Improved revenue outliers identification based on empirical information

peskas.timor.data.pipeline 1.3.0

New features

• Integrated taxa selection and filtering in tracks file deemed to the leaflet map in the portal

peskas.timor.data.pipeline 1.2.0

New features

• Added a new feature in the function ingest_pds_map. The function process and upload a data frame containing the number of trips, CPE (catch per unit effort) and RPE (revenue per unit effort) splitted by grids to produce leaflet maps in the web portal.

peskas.timor.data.pipeline 1.1.0

Improvements

• Improve the estimation of some fish groups’ catches by calculating the weight per individual case by case.

Bug fixes

-Fix error in cleaning of legacy landings: the columns indicating the number of individuals and fish length for catches > 60cm were exchanged

peskas.timor.data.pipeline 1.0.0

Improvements

Adding option to produce Timor map filtered by fishing trips

peskas.timor.data.pipeline 0.20.0

Improvements

• Improve the validation step by flagging those observation characterized by having positive revenue (individuals) despite 0 or null individuals (revenue).

• Use a log model to identify abnormal weight-revenue relationships on Cook’s distance estimation.

• Replace NA catch code with catch code “0” and ensure these observations having non positive individuals and revenue.

• Use total length for weight calculation of MOO in all the landings (weights calculated with FL seem quite unrealistic)

• Use 95° quantile instead of median to summarise weight parameters for catch types, it seems to return more realistic weight estimations by single individuals.

Bug fixes

• Split landings preprocessing in two jobs to avoid to run out of memory (docker exit code 137)

peskas.timor.data.pipeline 0.19.0

New features

• Added a new function ingest_pds_matched_trips to ingest matched pds tracks and survey landings in a zip folder on a monthly scale.

peskas.timor.data.pipeline 0.18.0

New features

• Added nutritional values for each catch by the function get_nutrients_table. The function links to the repository https://github.com/mamacneil/NutrientFishbase and join the estimated nutrients values with the FishBase species data.

peskas.timor.data.pipeline 0.17.0

New features

• Added the folder report containing the scripts useful to generate a pdf report of Peskas. Such report is downloadable from Peskas portal.
• Added a series of functions (get_sync_tracks(), get_full_tracks() ,get_full_trips()) useful to retrieve the complete file of pds tracks.
• Generate and retrieve the pds track map with ingest_pds_map() and get_tracks_map().

peskas.timor.data.pipeline 0.16.0

Breaking changes

• The Docker file now run rocker/r-ver 4.1.1 instead of rocker/geospatial:4.0.3

Bug fixes

• Fixed the bug when calling ingest_rfish_table() in the main pipeline.

peskas.timor.data.pipeline 0.15.0

New features

• Added a series of functions (get_catch_types(), get_fish_length() ,retrieve_lengths()) useful to retrieve morphometric conversion factors from catch types names in metadata tables.
• Added a new metadata table in airtable (morphometric_table) containing length-weight and length-length conversion factors.
• Added join_weights() which integrates morphometric data with merged landings.

peskas.timor.data.pipeline 0.14.0

New features

• We test validated data to ensure its integrity
• Added merge_trips() which integrates data from the landings and tracking together
• Added format_public_data() to format and export data to be used for analytics

peskas.timor.data.pipeline 0.13.0

New features

• Added functions to process and validate pds trips. Namely, preprocess_pds_trips() and validate_pds_trips(). These functions make sure the data types are appropriate, check for trip duplicates and perform basic checks for trip duration and distance.

peskas.timor.data.pipeline 0.11.0

New features

• Added retrieve_pds_trips_data(), retrieve_pds_trips(), retrieve_pds_tracks_data() and retrieve_pds_tracks() to download trips and tracks from Pelagic Data System API.
• Added function get_pds_res() to convert Pelagic Data System API responses to data frames and merge trips and tracks data in a unique file.
• Added ingest_pds_trips() and ingest_pds_tracks() to upload Pelagic Data System data into cloud.
• Created a new bucket (pds-timor-dev) to store pds data.

Bug fixes

• cloud_object_name() returns an empty vector when the bucket is empty

peskas.timor.data.pipeline 0.10.1

Bug fixes

• Fixed the bug in survey retrieve process. Integrating a server response status check in retrieve_survey_data()

peskas.timor.data.pipeline 0.10.0

New features

• Added merge_landings() to merge and upload pre-processed recent and legacy landings data.

peskas.timor.data.pipeline 0.9.1

Improvements

• Simplified jobs in the pipeline workflow

Bug fixes

• Fixed workflow so that runs that are supposed to run in production actually do so

peskas.timor.data.pipeline 0.9.0

New features

• Added clean_catches(), coalist() and clean_legacy_landings() to restructure legacy landings to recent landings.
• Added preprocess_legacy_landings() to clean and ingest preprocessed legacy data.

peskas.timor.data.pipeline 0.8.0

New features

• Added validate_landings() and ingest_validation_tables() to get validation data, check the ladings and upload flags to Airtable.
• Added air_tibble_to_records() and air_upload_records() to create and update records in Airtable
• Added logic to validate IMEIs in the landing data
• Added a script in inst/airtable/edit-submission-link.js which can be used in Airtable to generate a link to the editable submission form

Improvements

• Deactivated check of uniqueness of IMEI per boat in pt_

Breaking changes

• Landings pre-processing now renames a few columns in the data: specifically submission_id (used to be *_id) and landing_date* (used to be date)

peskas.timor.data.pipeline 0.7.0

New features

• Added ingest_legacy_landings to retrieve data from legacy data (SFF landings)

peskas.timor.data.pipeline 0.6.0

New features

• Added air_get_records() and air_records_to_tibble() to retrieve and process records from Airtable
• Added pt_validate_boats(), pt_validate_devices(), and pt_validate_vms_installs() to perform basic data validation from the metadata tables

Improvements

• cloud_object_name() can now also match files by exact name and not just by prefix

Breaking changes

• ingest_metadata_tables() and preprocess_metadata_tables() now use logic to use Airtable instead og Google Sheets

peskas.timor.data.pipeline 0.5.0

New features

• Added ingest_metadata_tables() to ingest data about boats, species, municipalities, etc.
• Added preprocess_metadata_tables() to preprocess the data from the metadata ingestion.
• Added pt_get_devices_table() and pt_validate_flags() as helper functions for the metadata preprocessing.

Improvements

• We use a single function to read the config.file and load the environment parameters
• Added an skeleton pipeline to provide guidance to future development. This is now visible in the README.

peskas.timor.data.pipeline 0.4.0

Breaking changes

• Renamed ingest_timor_landings() to ingest_landings() for brevity and because all functions relate to Timor anyways.

Improvements

• Renamed the job names in the github workflow as the functions that the job calls.
• Improved documentation of the package: particularly the readme and the function reference.

Bug fixes

• We now skip RCurl from windows tests

peskas.timor.data.pipeline 0.3.0

New features

• The preprocessing of East Timor landings is implemented in preprocess_landings()
• Added pt_nest_attachments() to group all attachment columns into a nested column containing data frames.
• Added pt_nest_species() to group all attachment columns into a nested column containing data frames.
• Added cloud_object_name() as a complement to add_version() to return the latest or an specified version of an object in an storage location.
• Added download_cloud_file() to download files from cloud storage providers.

Improvements

• Now using cloud_storage_authenticate() to internally authenticate to cloud storage instead of authenticating separately in each cloud functionjj. This simplifies authentication and ensures authentication is not attempted when credentials have been already validated.

peskas.timor.data.pipeline 0.2.0

Breaking changes

• download_survey_data(), download_survey_metadata(), and download_survey() have been renamed to retrieve_survey_data(), retrieve_survey_metadata(), and retrieve_survey(). This is to avoid confusion with planned functions that download data from cloud locations.
• The suffix raw and metadata that is appended to the prefix when retrieving survey information is now separated using "_" rather than “-”. This is to more easily distinguish between information encoded in the file name.

New features

• The prefix name of surveys is not hard-coded and can be specified in the config file (file_prefix field).

peskas.timor.data.pipeline 0.1.0

Adds infrastructure to download survey data and upload it to cloud storage providers and implements the ingestion of East Timor landings.

New features

• The ingestion of East Timor Landings is implemented in ingest_timor_landings().
• The functions download_survey_data() and download_survey_metadata() which download data and metadata for an electronic survey hosted by kobo, kobohr, or ona.
• download_survey() can be used as a wrapper to download data and metadata in a single call.
• upload_cloud_file() can be used to upload a set of files to a cloud storage bucket. Currently only Google Cloud Services (GCS) is supported.
• add_version() is an utility function that appends date-time and sha information to a string and is used to version file names.
• get_host_url() is an utility function that gets the host url of an electronic survey provider API.

Pipeline

The data pipeline is implemented and run in GitHub Actions on a schedule.