Reproducibility and Explainability in Digital Humanities

Fabian Offert's picture

Your network editor has reposted this from H-Announce. The byline reflects the original authorship.

Type: 
Call for Papers
Date: 
September 1, 2022
Subject Fields: 
Digital Humanities

The International Journal of Digital Humanities (IJDH) invites articles for a special issue on "Reproducibility and Explainability in Digital Humanities", planned for summer 2023. Fabian Offert (UCSB), Karina Van Dalen-Oskam (UvA), and Thorsten Ries (UTA) are editing this special issue. It will feature invited contributions by Maria Antoniak, James Dobson, Andreas Fickers, Béatrice Joyeux-Prunel, Sarah Lang, and others. Researchers at all career stages and from different research disciplines are encouraged to submit an abstract.

Theme: “Reproducibility” and “explainability” are important methodological considerations in the Sciences, and are increasingly relevant in Digital Humanities. The discussions around Nan Z. Da’s The Computational Case against Computational Literary Studies (2019), Katherine Bode’s Why You Can’t Model Away Bias (2020), Beatrice Fazi’s Beyond Human: Deep Learning, Explainability and Representation (2020) and Perceptual Bias and Technical Metapictures (2020) by Fabian Offert and Peter Bell foregrounded a crucial methodological desideratum for the interconnection of digital methods, humanities research, and critical approaches. Many methods and tools prevalent in Digital Humanities research are not reproducible. With the advent of AI, the predictions of many models are not explainable. Finally, Digital Humanities research still has to develop standards, as well as a culture, of comprehensive documentation and “understanding by reproducing”. This special issue of IJDH will explore practical, methodological, theoretical, and critical approaches to the reproducibility and explainability of digital scholarship in the humanities (and adjacent disciplines, including e.g. social sciences, life sciences, and computer science), in order to promote the development of best practices and standards that ensure transparency and accountability on a methodological level, improve the integration of digital scholarship in the humanities, and develop methods and source criticism as an integrated aspect of DH.     

We would like to invite methodologically oriented work as well as case studies on “reproducibility” and “explainability”, related, but not restricted to, the following topic areas: 

  • Concepts: Conceptual aspects of “reproducibility” and “explainability”, and their role in accountable, transparent humanities research, and perspectives on “understanding” / “reading” in the (digital) humanities. Tools, methods and concepts of AI explainability in (digital) humanities research.
    “What is “reproducibility” / “explainability”, what does that mean in a DH context?”
  • Research Methods: Case studies and best practice examples for reproducible, explainable DH research, challenges and (possible) solutions. Aspects of robustness of digital methods, reproducible code and data documentation and open data / open methods.
    “How do we do reproducible research and how are AI, ML explainable, using which methods and tools?”
  • Interpretation / Reproduction / XAI: Case studies and conceptual contributions on critical reproduction of studies, explainable AI, critical AI, data interpretation theory.
    “How do we read data and results by reproducing, what is the interpretation theory for data criticism?”
  • Culture: Studies on equitable and sustainable access to knowledge, methods, tools, technology and resources to make DH research reproducible and explainable, “understanding by reproducing”, critical reproduction, and intersectional aspects of reproducibility and explainability.
    “What does it take to create a culture of reproducible, explainable, equitable and sustainable research in DH?”
  • Teaching: Best practices on how to teach reproducibility and explainability as student-empowering concepts and access to DH research.
    “How can we teach principles, practices, methods and understanding of reproducibility and explainability in the DH classroom?”

Timeline, deadlines: Please submit short abstracts of about 200 words by September 01, 2022 via this online form. The editors will notify contributors by September 31, 2022. The articles are due for submission to IJDH peer review on March 01, 2023. The publication of the special issue is planned for Summer 2023. 

Submission: Please submit your abstract (about 200 words) here: online form.

International Journal of Digital Humanities: IJDH is an academic, fully peer reviewed Digital Humanities journal, published online and in print since 2019 with Springer. The journal’s focus is digital media and the development, application and reflection of digital research methodology in the Humanities. It also covers the history, current practice, and theory of Digital Humanities. IJDH is a hybrid open / closed access publication with Springer’s Open Choice program, and offers gold open access publication to members of many selected institutions and partners. If you care about open access, please go ahead and check whether your institution or institutional context is covered by the Open Choice program.   

Contact Info: 

Fabian Offert

Contact Email: 
Keywords: CFP