Currently, we have algorithms and parsers to generate the following metadata:
corrections: generated by outbreak_preprint_matcher, to be appended to litcovid and biorxiv parsersevaluations: generated by altmetrics parser, to be appended to anything with doi or pmidevaluations: generated by covid19_lst_annotations parser, to be appended to litcovid parsertopicCategory: generated by topicCategory classifier, to be appended to all parsers
A general script for appending this metadata is available at: https://github.com/gtsueng/outbreak_misc_meta , but it is unclear whether the script will work within the biothings environment/architecture
For a faster test, apply the script to a parser from one of the smaller resources like figshare or biorxiv rather than the bigger resources like litcovid. An example implementation can be found at: https://github.com/gtsueng/covid_figshare/tree/misc_annotations
Currently, we have algorithms and parsers to generate the following metadata:
corrections: generated by outbreak_preprint_matcher, to be appended to litcovid and biorxiv parsersevaluations: generated by altmetrics parser, to be appended to anything with doi or pmidevaluations: generated by covid19_lst_annotations parser, to be appended to litcovid parsertopicCategory: generated by topicCategory classifier, to be appended to all parsersA general script for appending this metadata is available at: https://github.com/gtsueng/outbreak_misc_meta , but it is unclear whether the script will work within the biothings environment/architecture
For a faster test, apply the script to a parser from one of the smaller resources like figshare or biorxiv rather than the bigger resources like litcovid. An example implementation can be found at: https://github.com/gtsueng/covid_figshare/tree/misc_annotations