Daniel Erhart

– Schandôhalbar –

documentation-tracks

Schandôhalbar is a project, which presents the content of books in a new and discoverable way. It rethinks the linear system of visualizations by introducing a "verifiable approach". Starting from a printed book, an iterative cycle of analysis and digitalization took part. Through the digital capabilities it was possible to gain a fundamental understanding of the complex text-to-data translation. With various interactive visualizations users can explore the whole dataset one a web based application.

The name Schandôhalbar is a term, which is used in the Bregenzerwald and means "for the sake of orderliness". It suits perfectly to this project because by dealing with datasets it is necessary to bring the data in order before visualizing it.

originalausgabe

The original book from 1863.
Thank you Feldermuseum for collaborating.

231 pages were digitized for this project

The verifiable approach.

It rethinks the methodology of the text-to-data translation. Using this approach, every researcher can easily access all the important data with one single click. By preserving the contextualized embedment of each character in the dataset it is easy to refer to the source.

By dealing with complex qualitative datasets, information can be easily misinterpreted. Most of the time the underlying dataset is often not accessible, or not referred to any source. Therefore, I was focused on building a data architecture which present a transparent image of the dataset.

documentation-tracks

I developed an algorithm, which scans the document based on predefined character keywords. It helps to gain an overview on the naming cluster in the document itself. You can easily find pattern and get contextualized information about the embedment.

By hovering the marked sentences, users get a readable preview. This enhances the understanding of the structure and of the document itself.

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The next step was to transform the qualitative data into a quantitative data. It is more easily to compare quantitative datasets on a linear scale. Therefore I came up with a visualization, which presents all the textual information in an easy and comparable way.

The "verifiable approach" provides every user complete access to the underlying qualitative dataset. This verifiable approach delivers not only the contextualized feedback, it gives users also information about the position in their printed books.

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The data is presented in a novel interface, which provides a clear hierarchical structure. It´s minimal style reduce cognitive load and let user's experience the information in a meaningful way. It not only allow users to explore the dataset, it also give them the opportunity to download the generated dataset with one single click. The supported document formats are CSV and TSV.

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If you like to have more information about this project, feel free to ask.

What's next?

Tracks
Renovated
U-Smart Mirror
U-Smart Mirror
Schräg
Schräg