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Simpan dan kategorikan konten berdasarkan preferensi Anda.
Halaman ini menjelaskan cara mendaftarkan data pengguna dengan Consent Management API.
Elemen data didaftarkan dengan Consent Management API dan dihubungkan ke izin menggunakan pemetaan data pengguna. Data pengguna tidak pernah disimpan di
Consent Management API.
Pemetaan data pengguna, yang ditampilkan sebagai resource UserDataMappings, mencakup elemen berikut:
ID pengguna yang mengidentifikasi pengguna. ID ini cocok dengan ID yang diberikan aplikasi ke Consent Management API saat mendaftarkan izin.
ID data yang mengidentifikasi data pengguna yang disimpan di tempat lain, seperti di
Google Cloud atau di lokal. ID data dapat berupa ID buram, URL, atau
ID lainnya.
Atribut resource, yang menjelaskan karakteristik data pengguna menggunakan nilai atribut resource yang dikonfigurasi untuk penyimpanan izin menggunakan definisi atribut. Misalnya, data dapat menyertakan attribute_definition_iddata_identifiable dengan nilai de-identified.
Diagram berikut menunjukkan alur data untuk membuat pemetaan data pengguna:
Kolom data_id dari resource pemetaan data pengguna berisi string yang ditentukan pelanggan yang menjelaskan data yang dirujuk oleh resource pemetaan data pengguna. String apa pun diizinkan, seperti ID atau URI buram.
ID data dapat sekecil yang diperlukan oleh aplikasi Anda. Jika
data yang Anda daftarkan dapat dijelaskan di tingkat
tabel atau bucket, tentukan data_id sebagai jalur REST ke resource tersebut.
Jika data yang Anda daftarkan memerlukan perincian lebih lanjut, Anda dapat menentukan baris atau sel tertentu. Jika aplikasi Anda menggunakan resource konseptual, seperti tindakan yang diizinkan atau class data, Anda harus menentukan data_id dengan konvensi yang mendukung kasus penggunaan tersebut.
Contoh data_id yang menjelaskan data yang disimpan di berbagai layanan dan pada berbagai tingkat perincian mencakup, tetapi tidak terbatas pada, hal berikut:
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[[["\u003cp\u003eThis page explains the process of registering user data with the Consent Management API, which involves creating user data mappings without storing the actual user data in the API.\u003c/p\u003e\n"],["\u003cp\u003eUser data mappings contain a user ID, a data ID, and resource attributes that describe the characteristics of the user data, all stored elsewhere.\u003c/p\u003e\n"],["\u003cp\u003eTo create a user data mapping, you must use the \u003ccode\u003eprojects.locations.datasets.consentStores.userDataMappings.create\u003c/code\u003e method and provide necessary details like the parent consent store name, user ID, data ID, resource attributes, and an access token.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003edata_id\u003c/code\u003e field in user data mapping can be any string, such as an opaque ID or a URI, and should describe the referenced data's location and granularity, like a Google Cloud Storage object or a BigQuery row.\u003c/p\u003e\n"],["\u003cp\u003eThe provided examples demonstrate the proper way to register data from multiple sources, such as Amazon S3 objects, BigQuery elements, or even conceptual representations.\u003c/p\u003e\n"]]],[],null,["# Registering user data\n\nThis page describes how to register user data with the Consent Management API.\n\nData elements are registered with the Consent Management API and connected to\nconsents using user data mappings. User data is never stored in the\nConsent Management API.\n\nThe user data mappings, represented as [`UserDataMappings`](/healthcare-api/docs/reference/rest/v1/projects.locations.datasets.consentStores.userDataMappings)\nresources, include the following elements:\n\n- A user ID that identifies the user. This ID matches the ID the application provided the Consent Management API when registering the consent.\n- A data ID that identifies user data stored elsewhere, such as on Google Cloud or on-premises. The data ID can be an opaque ID, a URL, or any other identifier.\n- Resource attributes, which describe the characteristics of the user data using resource attribute values configured for the consent store using attribute definitions. For example, the data could include the `attribute_definition_id` `data_identifiable` with the value of `de-identified`.\n\nThe following diagram shows the data flow for creating user data mappings:\n\nRegistering user data mappings\n------------------------------\n\nTo create a user data mapping, use the\n[`projects.locations.datasets.consentStores.userDataMappings.create`](/healthcare-api/docs/reference/rest/v1/projects.locations.datasets.consentStores.userDataMappings/create)\nmethod. Make a `POST` request and specify the following information in the\nrequest:\n\n- The name of the parent consent store\n- A unique and opaque `userID` that represents the user with whom the data element is associated\n- An identifier for the user data resource, such as the REST path to a unique resource\n- A set of `RESOURCE` attributes that describe the data element\n- An access token\n\n### curl\n\nThe following sample shows a `POST` request using `curl`: \n\n```bash\ncurl -X POST \\\n -H \"Authorization: Bearer $(gcloud auth application-default print-access-token)\" \\\n -H \"Content-Type: application/consent+json; charset=utf-8\" \\\n --data \"{\n 'user_id': '\u003cvar class=\"edit\" translate=\"no\"\u003eUSER_ID\u003c/var\u003e',\n 'data_id' : '\u003cvar class=\"edit\" translate=\"no\"\u003eDATA_ID\u003c/var\u003e',\n 'resource_attributes': [{\n 'attribute_definition_id': 'data_identifiable',\n 'values': ['de-identified']\n }]\n }\" \\\n\"https://healthcare.googleapis.com/v1/projects/\u003cvar class=\"edit\" translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e/locations/\u003cvar class=\"edit\" translate=\"no\"\u003eLOCATION\u003c/var\u003e/datasets/\u003cvar class=\"edit\" translate=\"no\"\u003eDATASET_ID\u003c/var\u003e/consentStores/\u003cvar class=\"edit\" translate=\"no\"\u003eCONSENT_STORE_ID\u003c/var\u003e/userDataMappings\"\n```\n\nIf the request is successful, the server returns a response similar to the\nfollowing sample in JSON format: \n\n```\n{\n \"name\": \"projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID/consentStores/CONSENT_STORE_ID/userDataMappings/USER_DATA_MAPPING_ID\",\n \"dataId\": \"DATA_ID\",\n \"userId\": \"USER_ID\",\n \"resourceAttributes\": [\n {\n \"attributeDefinitionId\": \"data_identifiable\",\n \"values\": [\n \"de-identified\"\n ]\n }\n ]\n}\n```\n\n### PowerShell\n\nThe following sample shows a `POST` request using Windows PowerShell: \n\n```bash\n$cred = gcloud auth application-default print-access-token\n$headers = @{ Authorization = \"Bearer $cred\" }\n\nInvoke-WebRequest `\n -Method Post `\n -Headers $headers `\n -ContentType: \"application/consent+json; charset=utf-8\" `\n -Body \"{\n 'user_id': '\u003cvar class=\"edit\" translate=\"no\"\u003eUSER_ID\u003c/var\u003e',\n 'data_id' : '\u003cvar class=\"edit\" translate=\"no\"\u003eDATA_ID\u003c/var\u003e',\n 'resource_attributes': [{\n 'attribute_definition_id': 'data_identifiable',\n 'values': ['de-identified']\n }]\n }\" `\n -Uri \"https://healthcare.googleapis.com/v1/projects/\u003cvar class=\"edit\" translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e/locations/\u003cvar class=\"edit\" translate=\"no\"\u003eLOCATION\u003c/var\u003e/datasets/\u003cvar class=\"edit\" translate=\"no\"\u003eDATASET_ID\u003c/var\u003e/consentStores/\u003cvar class=\"edit\" translate=\"no\"\u003eCONSENT_STORE_ID\u003c/var\u003e/userDataMappings\" | Select-Object -Expand Content\n```\n\nIf the request is successful, the server returns a response similar to the\nfollowing sample in JSON format: \n\n```\n{\n \"name\": \"projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID/consentStores/CONSENT_STORE_ID/userDataMappings/USER_DATA_MAPPING_ID\",\n \"dataId\": \"DATA_ID\",\n \"userId\": \"USER_ID\",\n \"resourceAttributes\": [\n {\n \"attributeDefinitionId\": \"data_identifiable\",\n \"values\": [\n \"de-identified\"\n ]\n }\n ]\n}\n```\n\n\u003cbr /\u003e\n\nConfiguring data IDs\n--------------------\n\nThe `data_id` field of the user data mapping resource contains a\ncustomer-specified string that describes the data that the user data mapping resource\nrefers to. Any string is permitted, such as an opaque ID or URI.\n\nData IDs can be as granular as is required by your application. If\nthe data you are registering can be described at the\ntable or bucket level, define `data_id` as the REST path to that resource.\nIf the data you are registering requires more granularity,\nthen you may want to specify specific rows or cells. If your application uses conceptual resources, such as permitted actions or classes of data, you should\ndefine `data_id` with a convention that supports those use-cases.\n\nExamples of a `data_id` that describes data stored in different services and at\nvarious levels of granularity include, but are not limited to, the following:\n\nGoogle Cloud Storage object\n\n\u003cbr /\u003e\n\n```\n 'data_id' : 'gs://BUCKET_NAME/OBJECT_NAME'\n \n```\n\n\u003cbr /\u003e\n\nAmazon S3 object \n\n```\n 'data_id' : 'https://BUCKET_NAME.s3.REGION.amazonaws.com/OBJECT_NAME'\n \n```\n\nBigQuery table\n\n\u003cbr /\u003e\n\n```\n 'data_id' : 'bigquery/v2/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID'\n \n```\n\n\u003cbr /\u003e\n\nBigQuery row (there is no REST path for a BigQuery row, so your own identifier is necessary - one possible approach is below)\n\n\u003cbr /\u003e\n\n```\n 'data_id' : 'bigquery/v2/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID/myRows/ROW_ID'\n \n```\n\n\u003cbr /\u003e\n\nBigQuery cell (there is no REST path for a BigQuery cell, so your own identifier is necessary - one possible approach is below)\n\n\u003cbr /\u003e\n\n```\n 'data_id' : 'bigquery/v2/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID/myRows/ROW_ID/myColumns/COLUMN_ID'\n \n```\n\n\u003cbr /\u003e\n\nFHIR resource\n\n\u003cbr /\u003e\n\n```\n 'data_id' : 'https://healthcare.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/datasets/DATASET_ID/fhirStores/FHIR_STORE_ID/fhir/Patient/PATIENT_ID'\n \n```\n\n\u003cbr /\u003e\n\nConceptual representation\n\n\u003cbr /\u003e\n\n```\n 'data_id' : 'wearables/fitness/step_count/daily_sum'\n \n```\n\n\u003cbr /\u003e"]]
