TPDL 2023

News

BEST PAPER AWARD: CORE-GPT: Combining Open Access research and large language models for credible, trustworthy question answering. • (full) David Pride (The Open University); Matteo Cancellieri (The Open University); Petr Knoth (Knowledge Media institute, The Open University)

BEST STUDENT PAPER AWARD: How to Cite a Web Ranking and Make it FAIR • (full) Alessandro Lotta (University of Padua); Gianmaria Silvello (University of Padova)

About The Conference

The International Conference on Theory and Practice of Digital Libraries (TPDL) is a yearly date for researchers on Digital Libraries and related topics. For over twenty-five years TPDL has been an international reference forum focused on digital libraries and associated technical, practical, and social issues. TPDL encompasses the many meanings of the term “digital libraries”, including new forms of information institutions; operational information systems with all manner of digital content; new means of selecting, collecting, organizing, and distributing digital content; and theoretical models of information media, including document genres and electronic publishing. Digital libraries may be viewed as a new form of information institution or as an extension of the services libraries currently provide. Representatives from academia, government, industry, research communities, research infrastructures, and others are invited to participate in this annual conference. The conference draws from a broad and multidisciplinary array of research areas including computer science, information science, librarianship, archival science and practice, museum studies and practice, technology, social sciences, cultural heritage and humanities, and scientific communities. This year its focus is on bridging the wide field of Research and Information Science with the related field of Digital Libraries. Indeed, TPDL historically approached on “Digital libraries” embracing the field at large also comprehending three key areas of interest that can be synthesized as scholarly communication (e.g. research data, research software, digital experiments, digital libraries), e-science/computationally-intense research (e.g. scientific workflows, Virtual Research Environments, reproducibility) and library, archive and information science (e.g. governance, policies, open access, open science). This emphasises TPDL’s role over the last 25 years as a forum that brings together researchers and practitioners whose work intersects with Digital Libraries. Regardless of how your work connects with Digital Libraries, we invite you to participate.

The conference is organized in two tracks:

Registration

You can find information about the registration process HERE

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Keynotes

Laura Hollink

CWI - Centrum Wiskunde & Informatica (Amsterdam)

Laura Hollink specializes in human-centered, responsible AI for the culture & media sector. She is head of the Human-Centered Data Analytics group at the Center for Math and Computer Science (CWI) in the Netherlands. Laura Hollink is motivated by developing AI that can be used responsibly by the entire culture and media sector – not just by big (tech) companies. To this end, she investigates inclusivity, diversity and transparency in a broad range of AI techniques, including statistical AI (machine learning), symbolic AI (knowledge graphs, reasoning), and human computation (crowdsourcing). Laura Hollink maintains close collaborations with professionals from the culture & media sector, as well as social scientists and humanities scholars. She is co-director of the Cultural AI Lab and partner in the AI, Media & Democracy Lab, two interdisciplinary labs where scientists collaborate on real world data and societally relevant use cases.

Title

Responsible AI & GLAM: challenges and opportunities

Date

27 September 2023

Abstract

AI is being used in the GLAM sector for a wide range of tasks such as recommendation, classification, tagging, handwriting recognition, OCR, etc. While the benefits of AI for the sector are clearly visible, there are also valid concerns regarding fairness and bias. Responsible AI is a hot topic in the AI research community, resulting in a large number of fairness metrics and bias mitigation strategies. This keynote will address the specific opportunities and challenges that arise when aiming for Responsible AI in the GLAM sector. Firstly, we will discus differences in fairness goals between the GLAM sector and other sectors. Secondly, we show how the availability of data - or lack thereof - has largely determined the research directions in the field of Responsible AI. Data curation as done in GLAM may be a way forward. Finally, in the GLAM sector, bias may be engrained in collections and/or metadata. An example from the Dutch GLAM sector is the colonial perspective often found in historic collections. This type of bias is hard to address. We show how the AI and GLAM communities may collaborate to measure and mitigate this type of bias.

Beatrice Alex

University of Edinburgh

Dr Beatrice Alex holds a Senior Lectureship and a Chancellor’s Fellowship at the School of Literatures, Languages and Cultures and the Edinburgh Futures Institute at the University of Edinburgh. She leads the Edinburgh Language Technology Group, a research and development group working on text mining and natural language processing and applying algorithms and solutions to different datasets, domains and languages in highly interdisciplinary research projects. Most recently she has been collaborating with the Gaelic Algorithmic Research Group advising on the development of Scottish Gaelic language technology.

Title

AI language technologies and digital collections: the need for interdisciplinary communication and co-design

Date

28 September 2023

Abstract

How can we invite AI into the archive? The majority of language technology development in my group is highly interdisciplinary working directly with domain experts and users. This keynote will showcase two Digital Humanities research projects in which we used natural language processing for conducting Scottish Gaelic handwriting recognition of written descriptions of a sound archive and for detecting bias in an archival catalogue. Both projects have specifically focussed on the data creation and digitisation processes or on the product and presentation of collection documentation. AI should be invited into the archives as it can be extremely useful to make advancements in these areas. However, continuous conversation and co-design between computer scientists, archivists, cataloguers and language experts are required to succeed in this work. I will provide some insights into the successes and challenges we faced in our work, and what is needed to create AI language technologies that can work with the uncertainties and complexities of heritage datasets.