# ezlinavis

> Easy Linavis (ezlinavis) generates CSV files with network data from simple segmentations of literary texts that you can further visualise and analyse

**Wikidata**: [Q126084932](https://www.wikidata.org/wiki/Q126084932)  
**Source**: https://4ort.xyz/entity/ezlinavis

## Summary
Easy Linavis (ezlinavis) is a software tool developed for the digital humanities that generates network data from segmented literary texts. It allows researchers to convert text segmentations into CSV files suitable for further visualization and structural analysis. The tool serves as a bridge between literary text segmentation and network science methodologies.

## Key Facts
- **Entity Type:** Software / Research Tool
- **Primary Function:** Generates CSV files containing network data from simple segmentations of literary texts.
- **Created By:** Frank Fischer and Carsten Milling.
- **Initial Release:** 2017.
- **License:** MIT License.
- **Output Format:** Comma-separated values (CSV).
- **Primary Uses:** Data visualization, network analysis, and visual analysis.
- **Latest Recorded Version:** 1.9.0 (released May 21, 2018).
- **Website:** https://ezlinavis.dracor.org/
- **Source Code:** Hosted on GitHub under the organization `dracor-org`.

## FAQs
### Q: What is the primary purpose of ezlinavis?
A: ezlinavis is designed to transform simple segmentations of literary texts into network data. It outputs this data as CSV files, which researchers can then use for visualization and analysis in other tools.

### Q: Who developed ezlinavis?
A: The software was created by Frank Fischer, a researcher in digital humanities, and Carsten Milling.

### Q: Is ezlinavis free to use?
A: Yes, the software is released under the MIT License, which is a permissive free software license.

### Q: Where can the software be accessed?
A: The tool is accessible via its website at `ezlinavis.dracor.org`, and its source code is available in a GitHub repository managed by the `dracor-org` organization.

## Why It Matters
ezlinavis addresses a specific technical gap in the digital humanities: the difficulty of converting qualitative literary texts into quantitative network models. By automating the extraction of network data based on text segmentation, it lowers the barrier to entry for scholars wishing to apply network analysis to literature.

The tool is significant because it streamlines the workflow between reading a text and analyzing its character interactions or structural connections. Instead of manually compiling node and edge lists, researchers can use ezlinavis to generate standard CSV files immediately. This capability facilitates "distant reading" practices, allowing for the comparison of narrative structures across large corpora. Its inclusion in repositories like the Social Sciences and Humanities Open Marketplace and TAPoR (Text Analysis Portal for Research) underscores its relevance as a standardized utility in text-based research.

## Notable For
- **Specialized Domain Function:** It is distinctively tailored for literary text segmentation rather than general data conversion.
- **Integration with Research Ecosystems:** The tool is indexed by specialized academic portals including the Social Sciences and Humanities Open Marketplace and TAPoR.
- **Open Source Accessibility:** It provides transparent, open-source code under the MIT License, hosted on GitHub.
- **Founder Expertise:** Developed by Frank Fischer, a noted figure in the digital humanities field, ensuring the tool is built for specific scholarly needs.
- **Rapid Iteration:** The project showed active development velocity in its first year, releasing multiple stable versions (1.2.0 through 1.9.0) between August 2017 and May 2018.

## Body

### Functionality and Utility
ezlinavis functions as a data transformation layer for literary scholars. The software accepts simple segmentations of literary texts as input. It processes these segmentations to identify relationships and structures, which it then formats into network data. The primary output format is Comma-Separated Values (CSV), a universal format compatible with most network analysis and visualization software (such as Gephi or Palladio). The tool supports three main categories of use: data visualization, network analysis, and visual analysis.

### Development and History
The project was initiated in 2017. It is attributed to the collaborative efforts of Frank Fischer—a researcher, editor, and writer in the digital humanities—and Carsten Milling.

The software underwent frequent updates following its inception. The development history indicates a focus on refinement and feature addition, with specific releases recorded as:
- **v1.2.0:** Released August 10, 2017.
- **v1.4.1:** Released December 6, 2017.
- **v1.7.0 & v1.7.1:** Released March 24, 2018.
- **v1.9.0:** Released May 21, 2018.

### Technical Specifications and Access
ezlinavis is classified as a "non-tangible executable component of a computer" (software) and a "research tool." It is distinct for its lightweight approach, focusing strictly on the generation of network data rather than the visualization itself.

**Availability:**
- **Web Interface:** The tool is hosted live at `https://ezlinavis.dracor.org/`.
- **Repository:** The source code is maintained at `https://github.com/dracor-org/ezlinavis`.
- **Documentation:** The software is described and cataloged at persistent identifiers including `https://tapor.ca/tools/1504` and `https://marketplace.sshopencloud.eu/tool-or-service/f9JraR`, as well as having a cited DOI (`10.5281/zenodo.10478399`).

## References

1. [Source](https://marketplace.sshopencloud.eu/tool-or-service/f9JraR)
2. [Source](https://tapor.ca/tools/1504)
3. [Release 1.2.0. 2017](https://github.com/dracor-org/ezlinavis/releases/tag/v1.2.0)
4. [Release 1.2.1. 2017](https://github.com/dracor-org/ezlinavis/releases/tag/v1.2.1)
5. [Release 1.2.2. 2017](https://github.com/dracor-org/ezlinavis/releases/tag/v1.2.2)
6. [Release 1.4.1. 2017](https://github.com/dracor-org/ezlinavis/releases/tag/v1.4.1)
7. [Release 1.5.0. 2017](https://github.com/dracor-org/ezlinavis/releases/tag/v1.5.0)
8. [Release 1.6.0. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v1.6.0)
9. [Release 1.7.0. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v1.7.0)
10. [Release 1.7.1. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v1.7.1)
11. [Release 1.8.0. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v1.8.0)
12. [Release 1.9.0. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v1.9.0)
13. [Release 1.10.0. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v1.10.0)
14. [Release 1.10.1. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v1.10.1)
15. [Release 1.11.0. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v1.11.0)
16. [Release 2.0.0. 2018](https://github.com/dracor-org/ezlinavis/releases/tag/v2.0.0)
17. [Release 2.1.0. 2021](https://github.com/dracor-org/ezlinavis/releases/tag/v2.1.0)
18. [Release 2.2.0. 2021](https://github.com/dracor-org/ezlinavis/releases/tag/v2.2.0)
19. [Release 2.3.0. 2024](https://github.com/dracor-org/ezlinavis/releases/tag/v2.3.0)
20. [Release 2.4.0. 2025](https://github.com/dracor-org/ezlinavis/releases/tag/v2.4.0)
21. [Release 2.4.1. 2025](https://github.com/dracor-org/ezlinavis/releases/tag/2.4.1)