-This part of the project collects tranliterations of key phrases related to COVID-19 using Wikidata. We search the Wikidata API for entities in `src/wikidata_search.py` and then we make simple SPARQL queries in `src/wikidata_transliterations.py` to collect labels and aliases the entities. The labels come with language metadata. This seems to provide a decent initial list of relevant terms across multiple languages.
+This code finds trending web searches related to the COVID-19 pandemic using Google trends (`collect_trends.py`). It then searches for relevant keywords on Wikidata (`wikidata_search`) in order to find high-quality translations of important words and phrases (`wikidata_translations.py`). The goal is to support efforts expanding the Observatory to information in many languages beyond English.
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+We search the Wikidata API for entities in `src/wikidata_search.py` and then we make simple SPARQL queries in `src/wikidata_translations.py` to collect labels and aliases the entities. The labels come with language metadata. This seems to provide a decent initial list of relevant terms across multiple languages.
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+The output data lives at [covid19.communitydata.science](https://covid19.communitydata.science/datasets/keywords).
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+The output files have 4 colums:
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+- `itemid` links to the wikidata entity
+- `label` is the translation of the relevant keyword
+- `langcode` is the [iso 639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) code corresponding the language of the label.
+- `is_alt` indicates whether the label is an [alias](https://www.wikidata.org/wiki/Help:Aliases).
projects / covid19.git / blobdiff