Conference Agenda (All times are shown in Greenwich Mean Time (GMT) unless otherwise noted)

METSI 2023 is a full-day workshop that provides a platform for research presentations and discussions related to the measurement of information production and use and the analysis of scientific and technical information by students, early-career and established researchers, information professionals, and librarians. The workshop will address relevant fields representing, or of interest to the SIGs’ communities, such as bibliometrics, scientometrics, informetrics, altmetrics, research evaluation and research integrity, scientific and technical information, and science and technology policies. Our goal is to strengthen the exchange of these. Keynote speaker: Mike Thelwall, University of Sheffield, UK. Additional registration fee applies.

This panel focuses on researching phenomena in virtual and physical environments, and features research with participants from underrepresented groups, including LQBTQIA+ communities. Scholars will address their involvement in ongoing projects, which were all impacted by the shifting between physical to virtual methods during the turbulent times of pandemic response and recovery. The panel will discuss the challenges and creative solutions touching on both benefits and limitations of conducting research in multiple environments. One outcome is to parlay the clear advantages of virtual work for accessibility and inclusivity in research design and employ these benefits into other contexts.

Leveraging open data to drive knowledge-based intelligent governance is crucial because it enables evidence-based decision-making, improves service delivery, increases transparency and accountability, and enhances citizen engagement. However, there are challenges associated with the use of data and technology in intelligent governance, including departmental data sharing and openness, practicality and user engagement of government platforms, and security issues. Therefore, our panel invited experts from various fields to discuss and provide solutions to these theoretical and practical challenges. We aim to deeply analyze and reveal the existing problems in theory and practice, and provide solutions to promote the development of knowledge-based intelligent governance. The importance of this panel lies in the promotion of evidence-based decision-making and the development of innovative digital public service capabilities to improve government responsiveness and citizen trust.

Searching as a learning process implies that learning occurs during a search process and might happens incidentally, influenced by the context the search takes place and the system that is used. Searching and learning are not isolated but co-occurring events. Research investigates how search systems can be improved to foster learning processes, integrate information literacy enhancing methods and support user’s sense-making of information. Regarding the advancement of AI algorithms and their implementation in search systems, the concept of searching as a learning process can help to better understand human-computer interactions and future information-seeking processes. The panel advances current research on search systems for learning in non-formal settings, with a focus on investigating the relation between searching and learning processes that influence people’s understanding, assessing and use of information. It will focus on the contributions of information science research and the expectations of future searching behavior with respect to emerging advances in AI.

This panel aims to discuss and critique the position of Information Science (IS) in European countries. This will be achieved through panel presentations and through critical discussion of key questions amongst the participants in the session. The introduction to the panel will identify issues that emerge from studies of IS in European countries, and in particular points that emerged from two previous ASIS&T Annual Meeting Panel Sessions. Presentations on the current situation of IS in the United Kingdom, Portugal, and countries from the former Yugoslavia will be given and briefly compared. The focus will then move to session participants, whose views on the state of IS in their own country will be solicited in a structured manner. Hosted by the European Chapter,

Growing global concerns over food safety, food price inflation, and climate change demand urgent attention in scientific fields. Food information behavior and practice have been a vibrant and growing research area in library and information science, following the user-centered paradigm shift and everyday life information needs, seeking, and use research since the 1970s. Research has shown that people engage with informal and embodied information to guide food practices (e.g., shopping, cooking, eating, and sustainability transitions). Food and health research challenge research methods and approaches in everyday information behavior and inform everyday practices, technological services, policies, and actions. In this panel, following a brief introduction, each panelist will share their research approaches and/or findings about food, health, and information research. We aim to invite and foster an open discussion with audiences to explore research opportunities, challenges, and approaches to studying food in library and information science. Hosted by SIG-HLTH.

The LIS Forward initiative is addressing the urgent question: As LIS evolves within the context of iSchools, how do we best position our research and education programs to lead the field and the future of libraries? The initiative stems from the recognition that the evolution of iSchools presents opportunities and challenges for LIS and that there is great value in iSchools working together on charting directions forward. The growing coalition of iSchools is working to support LIS in taking full advantage of the multidisciplinary knowledge and expertise within iSchools, foster future leaders who will champion LIS within iSchools, and confront the dynamic tensions in research intensive iSchools. This session aims to engage international, professional, and academic stakeholders to guide activities and coalition building that can continue to strengthen LIS in iSchools. A panel will present highlights from a recent position paper to catalyze interactive, facilitated dialogue within the ASIS&T community on critical issues in LIS research and education. Breakout sessions will generate responses and recommendations to advance collaborative planning and strategy of value to LIS academic programs and the profession.

Academics argue that the COVID-19 pandemic has limited students' ability to learn, with significant digital inequities occurring between students from the global North and the global South. Students and academics from developing nations encountered particular challenges and difficulties with the move toward online styles of learning. Much like their colleagues from developed countries, they were unprepared for this predicament, but on top of the crisis context, deeper issues were having to do with digital inequalities and disparities that were exacerbated by the inadequate digital infrastructure (smart devices/gadgets, internet access, and speed) and online interaction abilities and practices. The goal of this panel is to address the pressing issue of digital inclusion in online education, specifically the broader challenge of ensuring that online education is accessible to all.

This paper examines social science and humanity theories that have been applied to studies dealing with misinformation. We identified 273 articles published from 2012 to 2023 from Web of Science, Scopus, and ScienceDirect. These articles are empirical studies that have applied one or more social science or humanity theories. Applying content analysis approach, we identified 124 theories that authors have used in their studies. These theories belong to different disciplines or fields, such as political science, psychology, communication, sociology, and economics. We discuss the top 11 theories and how they have been used to understand misinformation and its impacts. This study provides insights into understanding current misinformation studies and rich resources for information evaluation and information literacy education.

False information, also known as misinformation or disinformation, has long been a serious concern in health information behavior research. The phenomenon of false information in health information behavior is complex and multifaceted, and it involves a range of factors related to the production, dissemination, and consumption of health information. This paper aims to understand through which channels people receive false health information and which information behavior patterns exist towards this kind of information. Based on 21 qualitative semi-structured interviews with interactive and visual participative elements, five patterns of health information behavior towards the receivement of false health information were identified. Further, a strong relationship between these patterns, the context in which false health information was encountered, and the information source was observed. Additionally, two specific information behavior patterns (information avoidance and intentional non-information behavior) as well as the urgency and impact of false information on the health of individuals and society, were identified as potential drivers for the dissemination of false health information.

Focusing on information services to marginalized urban communities in the United States between 1940 and 1975, this paper argues that African American librarians played foundational roles in early Community-Based Librarianship (CBL) initiatives. In doing so, Black librarians skillfully and resourcefully fought information poverty, pushed for social and political equality, and promoted their communities’ well-being through proactive information provision. By fighting the systemic racism throttling inner-city Black communities, moreover, their labors constituted a vital contribution to the post-World War II United States civil rights movement. As a result, theirs was a specifically Black CBL (BCBL). This heretofore hidden history offers fruitful lessons for current library and information science practice. It therefore aligns with the annual meeting theme, “Translating Information Research into Practice, Policy, and Action,” particularly in its emphasis on “creating effective models of information provision," "creating empathetic information services," and "understanding the power of information to develop human happiness, equality, and wellbeing.”

Mass media and big data constitute powerful information tools that fuel extremist, populist messaging. Demagogues turn to mass media and social networks to convey polarizing views, and governments increasingly rely on data and artificial intelligence to manage immigration. The speakers will describe how three global, deep-seated, and historic societal ills—anti-Black racism, anti-immigrant sentiment, and misinformation— converge to typecast, vilify, and pathologize Black diasporic immigrants. The speakers will also share examples of anti-Black, anti-immigrant, and misinformed policymaking, rhetoric, and cultural norms within the United Kingdom and the United States.

The digitization, curation, and utilization of Chinese ancient books are crucial to the digital humanities. Despite progress in these areas, issues with data interoperability, data sharing, and data linkage persist due to a lack of standardized annotated ancient corpus and a general description framework for ancient books. To overcome these challenges, this paper proposes an ontology-based description framework that integrates catalogs of Chinese ancient books from various institutions, creating a standardized, interpretable, and researchable knowledge base. The framework combines general standards with unique ancient book characteristics, revealing complex relationships between books and books, books and people, and books and times, providing a more comprehensive understanding of the knowledge contained within ancient books. Additionally, this paper applied the framework to The National Rare Ancient Book Directory, a catalog containing 13,026 books from over 400 institutes, to develop an interactive system. The system is available at https://rarebib.pkudh.org/. Our results demonstrate that the framework standardizes data and provides a sophisticated and nuanced understanding of the knowledge within ancient books. This has noteworthy implications for individuals engaged in research, scholarship, and reading in the digital age.

Mapping between different representations of similar data is a common challenge in digital humanities (DH). In practical DH collections, the ‘person’ is an essential and centric unit and other parts could link to the ‘person’ to form the knowledge base. However, there is still no general and useful person-oriented ontology in DH community. Many practical DH projects have developed their own ontologies by DH experts, but these ontologies are not interoperable. Therefore, it is important to explore existing biographical ontologies and develop a comprehensive person-oriented ontology for DH.

Using the metadata crosswalk method, we examined the ontologies provided for persons in three DH collections to analyze how they map onto standard ontologies such as FOAF (friend of a friend). This paper uncovers a significant and consistent gap between standard biographical ontologies and those used in practical DH collections, arriving at a set of heterogeneous problems, including different granularities of metadata. Consequently, we propose three key person-oriented ontological types of elements, drawing on this metadata crosswalk: basic biographical elements, relational elements, and explanatory elements (such as career, connected with role and time). This metadata crosswalk provides a foundation for future matching between person-oriented ontologies and facilitates semantic interoperability between DH collections.

Interdisciplinary research plays a crucial role in addressing complex challenges in science, technology, and society. Predicting interdisciplinary links between topics can unveil potential interdisciplinary relationships and foster innovation. Considering topics extracted from interdisciplinary research as interdisciplinary topics, we predict the potential links among them based on their co-word network, and we propose integrating topic semantic content features, author direct-collaboration features, and indirect-collaboration features to improve prediction accuracy. Based on Graph Convolutional Networks (GCN), Graph Attention Networks (GAT), GraphSAGE, Bert, and Node2vec, interdisciplinary topic link prediction models are constructed. We use digital humanities as a case study and our experimental results show that the integration of semantic content, direct-collaboration, and indirect-collaboration features significantly enhances the Area Under the Curve (AUC) and Average Precision (AP) performance, outperforming predictions based solely on the co-word network. The predicted results provide valuable research directions and references for digital humanities scholars, with examples in the fields of cultural heritage and historical geographic information systems.

Named Entity Recognition (NER), the automated identification and tagging of entities in text, is a popular natural language processing task, and has the power to transform restricted data into open datasets of entities for further research. This project benchmarks four NER models–Stanford NER, BookNLP, spaCy-trf and RoBERTa–to identify the most accurate approach and generate an open-access, gold-standard dataset of human annotated entities. To meet a real-world use case, we benchmark these models on a sample dataset of sentences from Native American authored literature, identifying edge cases and areas of improvement for future NER work.