# Data Foundry - Jupyter Notebooks

> Collection of Jupyter Notebooks based on the datasets provided by the National Library of Scotland

**Wikidata**: [Q111411199](https://www.wikidata.org/wiki/Q111411199)  
**Source**: https://4ort.xyz/entity/data-foundry-jupyter-notebooks

## Summary
Data Foundry - Jupyter Notebooks is a collection of software tools and computational notebooks released by the National Library of Scotland in 2020. It serves as a creative and functional interface that allows users to perform logical operations and data analysis directly on the library's provided datasets.

## Key Facts
- **Entity Type:** Instance of a collection and software.
- **Release Date:** 2020.
- **Owner:** National Library of Scotland.
- **Website:** https://data.nls.uk/tools/jupyter-notebooks/ (English).
- **Source Code Repository:** Hosted on GitHub at https://github.com/NLS-Digital-Scholarship/collections-as-data.
- **Affiliation:** Part of the International GLAM Labs Community.
- **Technical Composition:** Composed of computer programs and data; functions as a non-tangible executable component.
- **Primary Function:** Facilitates interaction with datasets provided by the National Library of Scotland.

## FAQs
### Q: What exactly is Data Foundry - Jupyter Notebooks?
A: It is a collection of Jupyter Notebooks classified as software, specifically designed to work with datasets from the National Library of Scotland. It was published in 2020 to aid in digital scholarship.

### Q: Who owns and maintains this collection?
A: The collection is owned by the National Library of Scotland and is part of the wider International GLAM Labs Community.

### Q: Where can the code and tools be accessed?
A: The tools are accessible via the National Library of Scotland's Data Foundry website, and the underlying source code is available in a public repository on GitHub under the organization NLS-Digital-Scholarship.

## Why It Matters
Data Foundry - Jupyter Notebooks represents a significant intersection between cultural heritage and digital scholarship. By providing a software-based collection tailored to the National Library of Scotland's datasets, it transforms static data into an interactive, executable environment. This entity lowers the barrier to entry for researchers and the public to engage with library data, embodying the "Collections as Data" movement. As a non-tangible tool, it enables users to leverage the hardware of their own computers to perform complex analysis, thereby extending the utility of the library's digital assets beyond simple viewing.

## Notable For
- **Dual Classification:** Uniquely defined as both a "collection" of resources and "software," bridging the gap between archival assets and executable tools.
- **GLAM Integration:** Serves as a practical implementation of the International GLAM Labs Community's mission to foster digital research in galleries, libraries, archives, and museums.
- **Open Access Infrastructure:** Provides transparent access to its logic via a public GitHub repository, distinguishing it as an open and reproducible academic tool.

## Body
### Definition and Classification
Data Foundry - Jupyter Notebooks is formally classified as a collection and an instance of software. Consistent with the definition of software, it is a non-tangible executable component consisting of computer programs and data. It functions as a tool or means for a computer to perform arithmetic or logical operations specifically on the datasets provided by the National Library of Scotland. It is categorized as a creative work and a written work, aligning with the broader taxonomic structures of software engineering and library science.

### Ownership and Origin
The entity is owned and operated by the **National Library of Scotland**. It was officially published in **2020**. The existence of the collection is a direct result of the library's efforts to digitize and make data accessible for computational use. The repository is organized under the "NLS-Digital-Scholarship" group on GitHub, highlighting its intended use for academic and research purposes.

### Technical Ecosystem
As a piece of software, the Data Foundry - Jupyter Notebooks possesses standard technical attributes:
*   **Architecture:** It is designed to run within a Jupyter environment, utilizing source code to process data.
*   **Repository:** The source code is maintained at `https://github.com/NLS-Digital-Scholarship/collections-as-data`. The repository metadata includes qualifiers linking it to specific identifiers (Q186055, Q364), suggesting integration with standardized knowledge graphs.
*   **Language:** The primary interface and content are in English.

### Community and Usage
The collection is a constituent part of the **International GLAM Labs Community**, a global network focused on digital labs in cultural heritage institutions. It utilizes the datasets provided by the National Library of Scotland, serving as the primary interface for "Collections as Data" initiatives. By providing these notebooks, the library enables users to engage in software studies and data-driven research without needing to build processing tools from scratch.