openArtBrowser http://openartbrowser.org invites you to browse through the world of arts, enjoy beautiful artworks and learn interesting things. We provide paintings, drawings and sculptures all over the world and from many periods.
This project contains:
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Scripts to crawl relevant data about artworks, artists, genres, locations, materials, motifs and movements from Wikidata
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Scripts to preprocess the crawled data
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Angular frontent
To start the frontend:
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download and install Node.js.
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open a terminal and install Angular CLI globally:
npm install -g @angular/cli -
for development mode:
ng servefrom artbrowser/app folder, app will be available in a browser on localhost:4200 -
for deployment:
ng build --prodon server and copy files to target directory
Frontend configuration:
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default elasticSearch url is 'http://openartbrowser.org/api/_search'
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to call a locally running elasticsearch docker container, run
npm run start_dockerorng build --configuration=e_local -
To change elasticSearch url to another server, change the above url in ‚app/src/app/core/services/data.service.ts‘
To build and run the elasticsearch docker container for local development, run the docker_elastic.sh script in the scripts directory. The building might take some time because of the included wiki crawling. For the docker container the wiki crawling is limited to a specific amount of objects per category. This amount is represented by the DEV_LIMIT variable in the get_wikidata_items.py script and thus can be adjusted there.