[dados] metadata

bases/br_bd_metadados/columns/publish.sql

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+/*
+Query para publicar a tabela.
+
+Esse é o lugar para:
+    - modificar nomes, ordem e tipos de colunas
+    - dar join com outras tabelas
+    - criar colunas extras (e.g. logs, proporções, etc.)
+
+Qualquer coluna definida aqui deve também existir em `table_config.yaml`.
+
+# Além disso, sinta-se à vontade para alterar alguns nomes obscuros
+# para algo um pouco mais explícito.
+
+TIPOS:
+    - Para modificar tipos de colunas, basta substituir STRING por outro tipo válido.
+    - Exemplo: `SAFE_CAST(column_name AS NUMERIC) column_name`
+    - Mais detalhes: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types
+*/
+
+CREATE VIEW basedosdados-dev.br_bd_metadados.columns AS
+SELECT 
+SAFE_CAST(table_id AS STRING) table_id,
+SAFE_CAST(name AS STRING) name,
+SAFE_CAST(bigquery_type AS STRING) bigquery_type,
+SAFE_CAST(description AS STRING) description,
+SAFE_CAST(temporal_coverage AS STRING) temporal_coverage,
+SAFE_CAST(covered_by_dictionary AS STRING) covered_by_dictionary,
+SAFE_CAST(directory_column AS STRING) directory_column,
+SAFE_CAST(measurement_unit AS STRING) measurement_unit,
+SAFE_CAST(has_sensitive_data AS STRING) has_sensitive_data,
+SAFE_CAST(observations AS STRING) observations,
+SAFE_CAST(is_in_staging AS STRING) is_in_staging,
+SAFE_CAST(is_partition AS STRING) is_partition
+FROM basedosdados-dev.br_bd_metadados_staging.columns AS t

bases/br_bd_metadados/columns/schema-prod.json

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+[{"name": "table_id", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "name", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "bigquery_type", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "description", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "temporal_coverage", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "covered_by_dictionary", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "directory_column", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "measurement_unit", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "has_sensitive_data", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "observations", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "is_in_staging", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}, {"name": "is_partition", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING", "mode": "NULLABLE"}]

bases/br_bd_metadados/columns/schema-staging.json

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+[{"name": "table_id", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "name", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "bigquery_type", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "description", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "temporal_coverage", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "covered_by_dictionary", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "directory_column", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "measurement_unit", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "has_sensitive_data", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "observations", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "is_in_staging", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}, {"name": "is_partition", "bigquery_type": "string", "description": null, "temporal_coverage": null, "covered_by_dictionary": null, "directory_column": {"dataset_id": null, "table_id": null, "column_name": null}, "measurement_unit": null, "has_sensitive_data": null, "observations": null, "is_in_staging": null, "is_partition": null, "type": "STRING"}]

bases/br_bd_metadados/columns/table_config.yaml

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+# Igual ao dataset.name mas como lower case.
+# Exemplos: br_ibge_populacao, br_inep_censo_escolar
+dataset_id: br_bd_metadados
+
+table_id: columns
+
+# Título da tabela.
+title: Colunas na BD+
+
+# Descreva a tabela. Essas são as primeiras frases que um usuário vai ver.
+# Você não precisa ser muito conciso. Sinta-se a vontade para dar exemplos de
+# como usar os dados.
+# Se souber, liste também aplicações: pesquisa, apps, etc. que usem os dados.,
+description: Colunas na BD+
+
+# As máximas unidades espaciais que a tabela cobre.
+# Exemplo:
+#   - sa.br
+spatial_coverage:
+   - world
+
+# Anos cobertos pela tabela.
+# Preencher como lista de intervalos.
+# Exemplos: ['1995(1)2019'], ['2002(2)2010', '2016', '2020'].
+temporal_coverage: 2022-03-13
+
+# A unidade temporal com qual a tabela é atualizada.
+# Opções em 'https://basedosdados.org/api/3/action/bd_available_options'
+update_frequency: day
+
+# Nível de observação da tabela: o que representa cada linha.
+observation_level:
+    - entity: other
+      columns:
+            - table_id
+
+last_updated: 
+    metadata: '2023-03-07'
+    data: '2023-03-07 14:54:00'
+    release: '2023-03-07 14:54:00'
+
+# Versão da tabela. Seguindo o padrão de semantic versioning.
+# Exemplo: v1.1.3
+version: v1.0
+
+# Quem está preenchendo esses metadados?
+published_by:
+    name: Patrick Teixeira
+    email: [email protected]
+    github_user: tricktx
+    ckan_user: patrickteixeira
+    website:
+
+# Qual organização/departamento/pessoa tratou os dados?
+# As vezes há um ponto intermediário entre os dados originais e subir na Base dos Dados.
+# Se essa pessoa é você, preencha abaixo com suas informações.
+data_cleaned_by:
+    name: Ricardo Dahis
+    email: [email protected]
+    github_user: rdahis
+    ckan_user: rdahis
+    website: www.ricardodahis.com
+
+# Se houve passos de tratamento, limpeza e manipulação de dados, descreva-os aqui.
+data_cleaning_description:
+
+# Url do código de limpeza dos dados.
+data_cleaning_code_url:
+
+# Organização que ajudou institucionalmente na disponibilização dos dados.
+partner_organization:
+    name:
+    organization_id:
+
+# Url dos dados originais no GCP Storage.
+raw_files_url:
+
+# Url dos arquivos auxiliares no GCP Storage.
+auxiliary_files_url:
+
+# Url da tabela de arquitetura no GCP Storage.
+architecture_url:
+
+source_bucket_name: basedosdados-dev
+
+project_id_prod: basedosdados-dev
+
+project_id_staging: basedosdados-dev
+
+# Liste as colunas da tabela que representam partições.
+# Não esqueça de deletar essas colunas nas tabelas .csv na hora de subir para o BigQuery.
+# Isso poupará muito tempo e dinheiro às pessoas utilizando essa tabela.
+# Se não houver partições, não modifique abaixo.
+partitions:
+
+# Quais são as colunas? Certifique-se de escrever uma boa descrição, as pessoas vão gostar
+# para saber sobre o que é a coluna.
+# Adicionar todas as colunas manualmente pode ser bastante cansativo, por isso, quando
+# inicializando este arquivo de configuração, você pode apontar a função para uma amostra de dados que
+# preencherá automaticamente as colunas.
+# Algumas colunas existirão apenas na tabela final, você as construirá em `publish.sql`.
+# Para esses, defina is_in_staging como False.
+# Além disso, você deve adicionar as colunas de partição aqui e definir is_partition como True.
+columns:
+    - name: table_id
+      bigquery_type: string
+      description: Table ID
+      temporal_coverage: (1) 
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: name
+      bigquery_type: string
+      description: Name
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: bigquery_type
+      bigquery_type: string
+      description: Bigquery Type
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: description
+      bigquery_type: string
+      description: Description
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: temporal_coverage
+      bigquery_type: string
+      description: Temporal Coverage
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit: year
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: covered_by_dictionary
+      bigquery_type: string
+      description: Indicates if it is covered by dictionary
+      temporal_coverage: (1)
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: directory_column
+      bigquery_type: string
+      description: Directory Column
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: measurement_unit
+      bigquery_type: string
+      description: Measurement Unit
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: has_sensitive_data
+      bigquery_type: string
+      description: Indicates if it has sensitive data
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: observations
+      bigquery_type: string
+      description: Observations
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: is_in_staging
+      bigquery_type: string
+      description: Is in staging
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+    - name: is_partition
+      bigquery_type: string
+      description: Is Partition
+      temporal_coverage: (1)
+      covered_by_dictionary: no
+      directory_column:
+          dataset_id:
+          table_id:
+          column_name:
+      measurement_unit:
+      has_sensitive_data: no
+      observations:
+      is_in_staging: true
+      is_partition: false
+
+number_rows: 14880
+
+metadata_modified: 

bases/br_bd_metadados/columns/table_description.txt

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+None
+
+Para saber mais acesse:
+Website: 
+Github: 
+
+Ajude a manter o projeto :)
+Apoia-se: https://apoia.se/basedosdados
+
+Publicado por
+-------------
+Nome: None
+Código: 
+Tratado por
+-----------
+Nome: None
+Código: 
+
+
+
+
+
+
+Cobertura Temporal
+------------------
+
+
+
+
+Cobertura Espacial
+------------------
+
+
+
+
+
+
+
+Frequencia de Atualização
+-------------------------
+day

bases/br_bd_metadados/dataset_config.yaml

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+
+# Nome (slug) do conjunto no CKAN
+# Exemplos: br-ibge-populacao, br-tse-eleicoes
+name: br-bd-metadados
+
+# Título do conjunto, a ser exibido no mecanismo de busca.
+# Exemplo: População brasileira
+title: Metadados na BD+
+
+# Qual organização disponibiliza os dados originais?
+# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/organization_list
+# Exemplos: br-ibge, br-tse, br-rj-gov
+organization: br-bd
+
+# Descrição do conjunto
+notes: Informações compiladas sobre os metadados mantidos na plataforma BD+.
+
+# Quais temas caracterizam a base?
+# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/group_list
+# Importante: preencher com a chave, e não o valor.
+groups:
+  - ciencia-tec-inov
+
+# Quais etiquetas caracterizam a base?
+# Opções: escolher dessa lista -> https://basedosdados.org/api/3/action/tag_list
+# Exemplos: fertilidade, preco, desmatamento.
+# Caso crie etiquetas novas, as regras são:
+#    - letras minúsculas
+#    - sem acentos
+#    - sempre no singular
+#    - não repita nomes de grupos (ex. educacao, saude, meio ambiente, economia, etc.)
+tags:
+   - administracao
+   - dados abertos
+
+# Não altere esse campo.
+# Data da última modificação dos metadados gerada automaticamente pelo CKAN.
+metadata_modified: