divinity-library/open-theology

Dataset Card for Dataset Name

Journal articles from Open Theology, Volume 12, Issue 1 (2026)

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

Dataset Details

Dataset Description

The dataset consists of theology articles (16 total, as of 9-12-2026) written in English from the latest volume of Open Theology (Volume 12, Issue 1, 2026), published by De Gruyter. All articles are open-access under Creative Commons Attribution 4.0.

• —Curated by: Yale Divinity Library's Computational Theology Lab
• —Funded by [optional]: [More Information Needed]
• —Shared by [optional]: [More Information Needed]
• —Language(s) (NLP): English
• —License: Creative Commons Attribution 4.0

Dataset Sources [optional]

https://www.degruyterbrill.com/journal/key/opth/12/1/html

Uses

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Direct Use

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Out-of-Scope Use

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Dataset Structure

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Dataset Creation

Curation Rationale

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Source Data

PDF copies of theology articles from Open Theology, Volume 12, Issue 1

Data Collection and Processing

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Who are the source data producers?

Journal articles are taken from Open Theology, Volume 12, Issue 1, published by De Gruyter. Authors whose articles are used in the dataset are as follows: Murat Sariyar; Roberto Mata and Samuel S. Cao; Katelyn Zeser; Abbas Jong; Stefano Furlan, Roberto Paura, and Daniele Puleio; Giovanni Hermanin de Reichenfeld; Zia Ul Haq; Malgorzata Gruchola; Edoardo Mattei; Bradley C. Dart; Héctor Varela Rios; Ian Davies; Ianire Angulo Ordorika; Carolina Montero Orphanopoulos; María Soledad Del Villar Tagle; and Juan Bautista Duhau.

Annotation process

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Who are the annotators?

Clifford Anderson, William Potter, Jonah Causin, Morgan Fuksa, Dominic Abraham

Personal and Sensitive Information

The dataset includes theology articles that contain the names of authors, their institutional affiliation (if any), their email address, and ORCID iD.

Bias, Risks, and Limitations

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Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.