| _version_ | 1866902268805120000 |
|---|---|
| author | Samsinger, Linda |
| author_facet | Samsinger, Linda |
| contents | Digital tools are essential in modern research endeavors. For research, the Swiss Library Service Platform (SLSP) houses over 25 million media items, yet navigating this vast collection of records is challenging without proper tools. Hence, Zurich Zentralbibliothek proposes a series of Jupyter Notebooks (JN) to quickly access and analyze metadata en masse sourced from the online catalog of a nationwide network of Swiss libraries. Through its SLSP-API integration, users can easily search and export their results into structured formats like Excel or JSON with bibliographic fields and Wikidata/GND enrichment. JNs offer robust data analysis, particularly through natural language processing and visualizations, such as charts, world maps and word clouds. Table of contents and statistical charts are exportable as PDF. Additionally, the notebooks' transparency allows customization of the codebase. Overall, this solution offers a user-friendly approach to navigating SLSP's vast repository, fostering data-driven strategies for stakeholders in the digital humanities. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_14943122 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Leveraging Zurich Zentralbibliothek's Jupyter Notebooks for Metadata Retrieval and Analysis from Alma Samsinger, Linda DHd2025 Paper Poster Search&Retrieval Python Jupyter Notebooks XML-Bibliothekskatalog API Natural Language Processing Data Visualization Digital Humanities Library Science MARC-fields Wikidata GND Metadata Spreadsheet Table Statistics Visualisierung Bibliographie Daten Metadaten Forschung Forschungsprozess Digital tools are essential in modern research endeavors. For research, the Swiss Library Service Platform (SLSP) houses over 25 million media items, yet navigating this vast collection of records is challenging without proper tools. Hence, Zurich Zentralbibliothek proposes a series of Jupyter Notebooks (JN) to quickly access and analyze metadata en masse sourced from the online catalog of a nationwide network of Swiss libraries. Through its SLSP-API integration, users can easily search and export their results into structured formats like Excel or JSON with bibliographic fields and Wikidata/GND enrichment. JNs offer robust data analysis, particularly through natural language processing and visualizations, such as charts, world maps and word clouds. Table of contents and statistical charts are exportable as PDF. Additionally, the notebooks' transparency allows customization of the codebase. Overall, this solution offers a user-friendly approach to navigating SLSP's vast repository, fostering data-driven strategies for stakeholders in the digital humanities. |
| title | Leveraging Zurich Zentralbibliothek's Jupyter Notebooks for Metadata Retrieval and Analysis from Alma |
| topic | DHd2025 Paper Poster Search&Retrieval Python Jupyter Notebooks XML-Bibliothekskatalog API Natural Language Processing Data Visualization Digital Humanities Library Science MARC-fields Wikidata GND Metadata Spreadsheet Table Statistics Visualisierung Bibliographie Daten Metadaten Forschung Forschungsprozess |
| url | https://doi.org/10.5281/zenodo.14943122 |