# 🔨 Workshop: Leveraging Zurich Zentralbibliothek’s Jupyter Notebooks for metadata retrieval and analysis from Alma

**URL:** <https://forum.swib.org/t/workshop-leveraging-zurich-zentralbibliothek-s-jupyter-notebooks-for-metadata-retrieval-and-analysis-from-alma/140>\
**Category:** Workshops@SWIB24\
**Tags:** ws-jupyter, ws-slot-eu-africa\
**Created:** [August 28, 2024, 7:58am UTC](https://forum.swib.org/t/workshop-leveraging-zurich-zentralbibliothek-s-jupyter-notebooks-for-metadata-retrieval-and-analysis-from-alma/140 "2024-08-28T07:58:21Z")\
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**Author:** ![saml](https://forum.swib.org/letter_avatar_proxy/v4/letter/s/e480ec/32.png) [@saml](https://forum.swib.org/u/saml)\
**Post date:** [August 28, 2024, 7:58am UTC](https://forum.swib.org/t/workshop-leveraging-zurich-zentralbibliothek-s-jupyter-notebooks-for-metadata-retrieval-and-analysis-from-alma/140/1 "2024-08-28T07:58:21Z")

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> **Event**
>
> **Starts:** November 25, 2024, 8:00am (UTC)\
> **Ends:** November 25, 2024, 12:00pm (UTC)\
> **Link:** <https://ims-realtime.net/join-room?mid=6937-281-294>

### Facilitator

Linda Samsinger (@saml)

### Abstract

Zurich Zentralbibliothek (ZB) has developed a powerful, versatile and user-friendly series of seven Jupyter Notebooks to search, download and analyze library data from the SLSP catalog. This Swiss-wide online repository of metadata in MarcXML format houses over 25 million entries (=Alma).

While library users browse [Swisscovery](https://uzb.swisscovery.slsp.ch/discovery/search?vid=41SLSP_UZB:UZB) to search for media titles, their Excel export is unstructured and limited to 50 entries. In contrast, ZB’s Jupyter Notebooks allows downloading up to 10,000 highly structured metadata records with bespoke calculation and grouping of underlying MARC fields to yield records’ title, author, publisher, year, language, …, summary, epoch, Swisscovery link and link to Table of Contents (ToC). Also, Wikidata/GND data fields can be added upon customization. ToC records are downloadable as PDF en masse. In a second step, the search results can be analyzed using frequency, bar and pie charts, world maps and word clouds, which are PDF exportable. The insights generated could constitute the touchstone for developing brand-new, publication-quality findings about underlying trends and anomalies.

The notebooks are customizable and open-source, a treasure trove for researchers and library professionals alike, who aim to explore and assess library data with data-driven methods. Consequently, these tools can be leveraged for academic projects, their bibliographies curated and citations sourced. Additionally, cataloging entries can be improved and gaps in the library’s collection uncovered, thereby guiding future acquisitions. Following in the steps of the DNB and the ÖNB, as well as the university library Bern, ZB has released its own series of Jupyter Notebooks to extend its data services with newly crafted functionalities. Users should be familiar with Jupyter Notebooks and basic Python programming as well as German.

For more information, visit Zurich Zentralbibliothek Jupyter Notebook’s [project repository](https://data.zb.uzh.ch/map/books/data-map-der-zentralbibliothek-zurich/page/jupyter-notebooks-der-zentralbibliothek-zurich). This resource provides detailed documentation to help users get started with these tools.

> ℹ To register your participation in this workshop click on the “Going” button above. You will then receive an email notification as soon as facilitators post an update. Watch out to not register for two parallel workshops.

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