• Alessio Antonini ,
• Francesca Benatti

Open University

Keywords: history of DH, humanities of the digital, DH disciplinary intersections

The Digital Humanities community is growing at a steady pace, as reflected by the number and variety of contributions to the ADHO DH conference. This growth includes a wider participation of researchers from different disciplines (e.g. computer science) who are engaged in 1) reframing, re-adapting and re-using their methodologies within a Humanities agenda and 2) in bringing back to their disciplines new perspectives and methods from the Humanities.

The DH cross-disciplinary “melting pot” has pushed three main visions [1] (waves). A first wave, “digitized humanities”, focused on the digital conversion of sources. A second, “numerical humanities”, focused on algorithmic and statistical methods and large scale data-driven studies. Lastly, a third (parallel) wave, “humanities of the digital”, focused on computer-mediated interactions within society, which has the unfulfilled potential to be a synthesis of the two [1].

This contribution reflects on the cultural challenges associated with these visions of DH. The digitized humanities brought the challenge of defining digital formats and standards, e.g. TEI and CIDOC CRM, but also questions concerning how the selection of sources for digitization could create or exacerbate existing biases, addressed by gender and post-colonial studies [2,3]. The numerical humanities introduced the challenge of data integration and legacy systems, but also questions concerning the impact of computational methods in the Humanities agenda [4] and the value of legacy data [5].

Concerning the humanities of the digital, we outline the emerging questions arising from the relations between DH and the design of digital objects. Following Liu’s mapping of DH [6], we address the relations between DH and new media studies, with a focus on hypertext and e-literature. Lastly, considering exemplar works in other disciplines [7], we question the potential impact of DH on technical disciplines and therefore on the design of new digital objects.

REFERENCES

1. Roth, C. (2019) ‘Digital, digitized, and numerical humanities’, Digital Scholarship in the Humanities, 34(3), pp. 616–632. doi: 10.1093/llc/fqy057.
2. Mandell, L. (2019) ‘Gender and Cultural Analytics: Finding or Making Stereotypes?’, in Gold, M. K. and Klein, L. F. (eds) Debates in the Digital Humanities 2019. 1st edn. Minneapolis MN: University of Minnesota Press (Debates in the Digital Humanities, 5). 
3. Global Outlook::Digital Humanities http://www.globaloutlookdh.org/ 
4. Antonini, A. and Benatti, F. ‘*ing the Written Word: Digital Humanities Methods for Book History’. In press, SHARP 2020: Power of the Written Word Conference Abstracts. https://sharp2020.nl/ 
5. Antonini, A., Benatti, F. and King, E. Restoration and Repurposing of DH Legacy Projects. In press, DH2020: carrefours/intersections. https://dh2020.adho.org 
6. Liu, A. (2015) ‘A Map of the Digital Humanities’. Available at: https://alanyliu.org/map-of-dh/ 
7. Bardzell, J., Bardzell, S., Blythe, M. Critical Theory and Interaction Design. The MIT Press. 2019.

¹ https://tei-c.org/ 

² http://www.cidoc-crm.org/

• Bingjun Liu ,
• Simon Mahony ,
• Yaming Fu

Beijing Normal University at Zhuhai

Keywords: iSchools, digital humanities, curriculum development

The iSchools Consortium is a collective of Information Schools with a shared interest in the relationships between information, people, and technology. Both the University of Sheffield and UCL are active members of the iSchools network; the Information School at Sheffield hosted the 2018 annual conference and the Department of Information Studies at UCL offers Master's and PhD programmes in DH. 

Two main educational areas that we seek to advance are those of data science and digital humanities. This presentation presents the findings of the iSchools Consortium committee for Digital Humanities Curriculum Design with a particular focus on education management and administration. We are working to develop a more comprehensive picture of the iSchool approach to DH and to formulate our path forward in this dynamic field. We wish to capitalise on the interdisciplinary methods already embedded in iSchool curricula and to facilitate opportunities for collaboration with other institutional departments and initiatives. To that end, the committee sees itself as having a crucial role in helping to define recommendations for digital humanities coursework and instructional resources as well as envisioning long-term goals and strategies for iSchool degree programmes in the field. 

One motivation for this initiative is the increasing number of job announcements asking for DH graduates, which emphasises the importance of curriculum and skills development in this field. Our aim is to see how iSchools can take this forward by asking what our role might be in the DH community. What might be the unique approach of iSchools in DH and what is it that distinguishes an iSchool's DH programme as opposed to one in other faculties and the wider academy? How might accreditation work and would it be advantageous or counter-productive by restricting innovation and diversity of curricula? What is the synergy between DH and the iSchool and what is the role for the latter in this arena? These are the questions addressed here.

• Barbara McGillivray ,
• Sarah Ames ,
• Beatrice Alex ,
• Guyda Armstrong ,
• David Beavan ,
• Arianna Ciula ,
• Giovanni Colavizza ,
• James Cummings ,
• David De Roure ,
• Adam Farquhar ,
• Simon Hengchen ,
• Lorna Hughes ,
• Anouk Lang ,
• James Loxley ,
• Eirini Goudarouli ,
• Federico Nanni ,
• Andrea Nini ,
• Julianne Nyhan ,
• Nicola Osborne ,
• Thierry Poibeau ,
• Mia Ridge ,
• Sonia Ranade ,
• James Smithies ,
• Melissa Terras ,
• Andreas Vlachidis ,
• Pip Willcox

The Alan Turing Institute

Since 2017, the Alan Turing Institute, the British national-level research institute for data science and artificial intelligence, has supported a Turing Special Interest group on the Humanities and Data Science. With regular discussions, meetings, and community engagement, the group has convened to identify priorities and recommendations that can help drive forward the integration of the communities. We present here our forthcoming white paper on the topic.

We identify an increased interest in undertaking large scale data-led research involving humanities scholars, GLAM organizations, and data science researchers. This may be prompted by the increased availability of large datasets coupled with available quantitative research frameworks and relatively cheap computing resources.

We see four general intersections between humanities and data science:

1. Computational humanities research: analyzing data sets to answer novel humanities questions;
2. Infrastructure for Cultural Heritage: creating, storing and providing access to repositories of complex and nuanced digital (structured and unstructured) data from GLAM organizations;
3. History and critique of data science: including ethical, methodological, and historical approaches;
4. Algorithmic creativity and cultural activity: performing creative tasks with the aid of computation.

We enumerate challenges and opportunities to further adoption including: difficulties in reframing humanities research methods; or in identifying and making transparent best practice; the challenges of reproducible and open data research in the humanities; the need for shared technical infrastructure and support; issues with funding, research assessment, career progression and training; and the need to communicate the benefits to data science from the integration of humanities approaches, including skill sets, value systems, methods, Humanities expertise and ethical approaches which the AI and data science community can learn from in a two-way exchange of knowledge. 

We welcome the chance to discuss our roadmap with attendees at the Digital Humanities Congress 2022.

 1.Data Science is defined at the Turing as the field that “brings together researchers in computer science, mathematics, statistics, machine learning, engineering and the social sciences” to study “the drive to turn [large amounts of] data into useful information, and to understand its powerful impact on science, society, the economy and our way of life.” https://www.turing.ac.uk/about-us/frequently-asked-questions. 

2. https://www.turing.ac.uk/research/interest-groups/humanities-and-data-science

3.A first draft of this white paper, by the authors of the article will be published in August 2020, in time for the Digital Humanities Congress: McGillivray et al. (Forthcoming, 2020), “Reflections on Humanities and Data Science from the Turing: challenges and prospects”, The Alan Turing Institute White Paper.