Keynote 1

Linked Data for Digital Humanities

Terhi Nurmikko-Fuller
Associate Professor, Australian National University
Abstract:

Two years ago, OpenAI’s launch of ChatGPT brought generative AI into the mainstream. The last 24 months have been a rollercoaster ride of inflated hype and troughs of disillusionment. As we look to embrace a more nuanced and realistic attitude to the set of tools that comprises the monolithic term of “AI”, a more deliberate and clearly articulated approach to research ethics is called for. As a society, and as a community of practice in this space, we need to actively seek to identify (and where possible correct) embedded prejudices, whether it apply to training data bias, algorithmic bias, or the cognitive biases that affect our analyses.

What we need is not just more data, but smarter data. What we need is knowledge that represents various perspectives, including those of women and minority groups. What we need is to provide this new behemoth of computational and data science with contextualized information. In doing so we can start to look at ways to reduce historical and social bias and to maximize the power and potential of bringing thoughtfully and CAREfully mapped data and increasingly powerful algorithms together.

CCS Concepts: • Information systems → Digital libraries and archives; • Applied computing → Arts and humanities; • Computing methodologies → Ontology engineering.

Keywords: ontologies, philosophical engineering, knowledge graphs, linked data

Biography:

Associate Professor Terhi Nurmikko-Fuller is an interdisciplinary researcher and a Linked Data methodologist. Her work has a specific focus on the application of computational tools to data from the Humanities and Social Sciences and in the context of cultural heritage. She holds a PhD and an MSc in Web Science from the University of Southampton, UK, as well as an MSc in Museum Studies (University of Leicester), and both an MPhil in Cuneiform and Near Eastern Studies and a First Class Honours BA in Ancient History and Archaeology from the University of Birmingham, UK.

Her international standing as an expert is reflected in a number of external appointments globally in both academia and the public sector: she is a co-chair of the Australian Government Linked Data Working Group; a Fellow of the Software Sustainability Institute (2016), UK; an eResearch South Australia (eRSA) HASS DEVL (Humanities Arts and Social Sciences Data Enhanced Virtual Laboratory) Champion; an iSchool Research Fellow at the University of Illinois at Urbana-Champaign, USA (2019 – 2021), and a British Library Researcher in Residence (Collections), UK. In 2023, she was the GALE Scholar Asia Pacific Digital Humanities Oxford Fellow and at this time was also a Short-Term Visiting Fellow at Jesus College, University of Oxford.

Her commissioned monograph “Linked Data for Digital Humanities” (part of the Digital Research in the Arts and Humanities series) was published in 2023 by Routledge.


Keynote 2

AI-Driven Innovation Indexing Framework

Wei Lu
Vice President and Distinguished Professor, Wuhan University
Abstract:

With the rapid expansion of scientific literature, identifying innovative and transformative research efficiently has become a critical challenge. Emerging artificial intelligence technologies, particularly large language models (LLMs), offer promising methodologies for processing, interpreting, and evaluating scientific work. Building on these advancements, we propose an AI-driven framework for innovation indexing and evaluation.

This framework employs advanced AI techniques such as layout and content analysis, named entity recognition, mechanism extraction, and integrity verification to develop a comprehensive understanding of scientific texts. It provides technical support for content description, academic impact evaluation, and innovation assessment. By combining shallow syntactic analysis with deep semantic understanding, the framework introduces quantifiable metrics and establishes a foundation for assessing scientific contributions, enabling evidence-based policymaking, funding allocation, and strategies to advance innovation.

Biography:

Wei Lu is the Vice President and a Distinguished Professor at Wuhan University. His research interests include knowledge organization, data intelligence, and AI governance. He has led numerous high-profile research projects, including the National 2030 “New Generation Artificial Intelligence” major initiative and a key project funded by the National Social Science Foundation of China. Additionally, he has been granted over 20 national standards and patents and also developed several software systems, including the question answering robot RobertAI and the scientific information processing platform ScienceAI. His work has been published in top-tier journals and conferences such as AAAI, ACL, SIGIR, EMNLP, JASIST, IP&M, and Research Policy. He has received several prestigious awards, including the Excellent Achievement Award in Humanities and Social Sciences from the Ministry of Education. He is also actively involved in academic and professional organizations, serving as a member of the Education Guidance Committee for Management Science and Engineering of the Ministry of Education, Vice Chairman of the China Index Society, Vice Chairman of the China Information Systems Professional Committee (CNAIS), Editor-in-Chief of Data and Information Management, and Executive Director of the China Science and Technology Information Society.