Stabilizing knowledge through standards - A perspective for the humanities

It is usual to consider that standards generate mixed feelings among scientists. They are often seen as not really reflecting the state of the art in a given domain and a hindrance to scientific creativity. Still, scientists should theoretically be at the best place to bring their expertise into standard developments, being even more neutral on issues that may typically be related to competing industrial interests. Even if it could be thought of as even more complex to think about developping standards in the humanities, we will show how this can be made feasible through the experience gained both within the Text Encoding Initiative consortium and the International Organisation for Standardisation. By taking the specific case of lexical resources, we will try to show how this brings about new ideas for designing future research infrastructures in the human and social sciences

The hunt for submarines in classical art: mappings between scientific invention and artistic interpretation

This is a report to the AHRC's ICT in Arts and Humanities Research Programme. This report stems from a project which aimed to produce a series of mappings between advanced imaging information and communications technologies (ICT) and needs within visual arts research. A secondary aim was to demonstrate the feasibility of a structured approach to establishing such mappings. The project was carried out over 2006, from January to December, by the visual arts centre of the Arts and Humanities Data Service (AHDS Visual Arts).1 It was funded by the Arts and Humanities Research Council (AHRC) as one of the Strategy Projects run under the aegis of its ICT in Arts and Humanities Research programme. The programme, which runs from October 2003 until September 2008, aims ‘to develop, promote and monitor the AHRC’s ICT strategy, and to build capacity nation-wide in the use of ICT for arts and humanities research’.2 As part of this, the Strategy Projects were intended to contribute to the programme in two ways: knowledge-gathering projects would inform the programme’s Fundamental Strategic Review of ICT, conducted for the AHRC in the second half of 2006, focusing ‘on critical strategic issues such as e-science and peer-review of digital resources’. Resource-development projects would ‘build tools and resources of broad relevance across the range of the AHRC’s academic subject disciplines’.3 This project fell into the knowledge-gathering strand. The project ran under the leadership of Dr Mike Pringle, Director, AHDS Visual Arts, and the day-to-day management of Polly Christie, Projects Manager, AHDS Visual Arts. The research was carried out by Dr Rupert Shepherd

Gower as Data: Exploring the Application of Machine Learning to Gower’s Middle English Corpus

Distant reading, a digital humanities method in wide use, involves processing and analyzing a large amount of text through computer programs. In treating texts as data, these methods can highlight trends in diction, themes, and linguistic patterns that individual readers may miss or critical traditions may obscure. Though several scholars have undertaken projects using topic models and text mining on Middle English texts, the nonstandard orthography of Middle English makes this process more challenging than for our counterparts in later literature. This collaborative project uses Gower’s Confessio Amantis as a small, fixed corpus for analysis. We employ natural language processing to reexamine the Confessio’s themes, adding data analysis to the more traditional close reading strategies of Gower scholarship. We use Gower’s work as a case study both to help reduce the potential variants across textual versions and to more deeply investigate the corpus than distant reading normally allows. Here, we share our initial findings as well as our methodologies. We hope to share resources that will allow other scholars to engage in similar types of projects

Oral evidence

Oral evidence given to the House of Commons BIS Select Committee Inquiry into Open Access

Pattern recognition in narrative: Tracking emotional expression in context

Using geometric data analysis, our objective is the analysis of narrative, with narrative of emotion being the focus in this work. The following two principles for analysis of emotion inform our work. Firstly, emotion is revealed not as a quality in its own right but rather through interaction. We study the 2-way relationship of Ilsa and Rick in the movie Casablanca, and the 3-way relationship of Emma, Charles and Rodolphe in the novel {\em Madame Bovary}. Secondly, emotion, that is expression of states of mind of subjects, is formed and evolves within the narrative that expresses external events and (personal, social, physical) context. In addition to the analysis methodology with key aspects that are innovative, the input data used is crucial. We use, firstly, dialogue, and secondly, broad and general description that incorporates dialogue. In a follow-on study, we apply our unsupervised narrative mapping to data streams with very low emotional expression. We map the narrative of Twitter streams. Thus we demonstrate map analysis of general narratives

A Conceptual Model for Scholarly Research Activity

This paper presents a conceptual model for scholarly research activity, developed as part of the conceptual modelling work within the ???Preparing DARIAH??? European e-Infrastructures project. It is inspired by cultural-historical activity theory, and is expressed in terms of the CIDOC Conceptual Reference Model, extending its notion of activity so as to also account, apart from historical practice, for scholarly research planning. It is intended as a framework for structuring and analyzing the results of empirical research on scholarly practice and information requirements, encompassing the full research lifecycle of information work and involving both primary evidence and scholarly objects; also, as a framework for producing clear and pertinent information requirements, and specifications of digital infrastructures, tools and services for scholarly research. We plan to use the model to tag interview transcripts from an empirical study on scholarly information work, and thus validate its soundness and fitness for purpose