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[CFP] EcoDL 2025: The 1st Workshop on Digital Libraries and AI-based Information Systems for Ecological Research and Practice
by D'Souza, Jennifer 11 Mar '25

11 Mar '25

EcoDL 2025: The 1st Workshop on Digital Libraries and AI-based Information Systems for Ecological Research and Practice in conjunction with TPDL 2025 EcoDL 2025 aims to explore the integration of AI, digital libraries, and FAIR data principles in ecological research to improve knowledge synthesis and predictive modeling. Ecology's complexity and data heterogeneity present challenges in generalization, requiring advanced computational tools for structured knowledge representation, search, and decision support. We invite researchers from ecology, AI, and digital information systems to discuss AI-driven data synthesis, semantic search, causal inference, and machine learning applications in biodiversity and conservation. Through interdisciplinary contributions, EcoDL 2025 seeks to foster innovation in ecological informatics, supporting open science and advancing digital methods for ecological research and environmental sustainability. ************************************************************** Workshop website: https://sites.google.com/view/ecodl2025/ Paper Submission Deadline: 16th May 2025 (AoE) *************************************************************** Topics of interest ------------ The EcoDL 2025 workshop welcomes submissions on, but not limited to, the following topics: · Knowledge graphs and structured ecological data representation o Biodiversity knowledge graphs o Linked open data for integrating scattered ecological knowledge sources o Ontologies for data interoperability in ecology: Standardizing environmental terms and concepts o Semantic annotation and classification of ecological data o AI-driven taxonomy generation for ecological datasets · Advanced search and retrieval for ecological and environmental data o Neural search for literature and reports: Improving retrieval of species, habitats, and ecosystem information o Improving retrieval of study question, research hypothesis and applied method o LLMs for information extraction: Capturing species interactions, climate impacts, and conservation policies o Retrieval-Augmented Generation (RAG) for ecological research: Hybrid AI systems for answering complex scientific questions o Multimodal search for biodiversity and environmental studies: Combining text, image, and geospatial data retrieval o Automated knowledge discovery from climate and biodiversity repositories · FAIR data principles in ecological research o Data interoperability o Open science infrastructure for ecological and environmental data o Ontologies for data interoperability in ecology: Standardizing environmental terms and concepts o FAIR data and software o Data lifecycle management (Create, Store, Share, Reuse) o NanopublicationsMapping-based Knowledge Graph Construction · AI for assisting ecological research o AI-based literature review o AI-driven synthesis of ecological knowledge: taking complexity and context-dependence into account o Monitoring biases in study system, study regions and methods in ecological research o Tracking Misinformation in Climate Science Using NLP: Identifying and mitigating the spread of false environmental claims · Digital libraries and ecological informatics o Methods for digitizing and analyzing historical ecological archives o Indigenous knowledge and digital archives for sustainability o AI-powered environmental storytelling and digital heritage o Human-nature interactions in digital libraries o Digitization and NLP for analyzing historical climate data · Methods for integrating heterogeneous ecological datasets o Integrating remote sensing data with ecological repositories o Multimodal search for biodiversity studies · Applications of AI in ecosystem restoration, conservation planning and decision-making o AI-powered decision support systems for restoration and conservation o Lay summaries based on ecological evidence o Impact assessment of conservation policies via digital libraries · Reflections on knowledge synthesis in ecology and on the contributions of AI o Evaluating the role of AI in ecological research o Challenges and limitations of AI-driven ecological modeling o The impact of automated systems on scientific knowledge creation o Ethical considerations in AI-assisted ecological analysis o Future directions for AI in knowledge synthesis for ecology Submission guidelines ---------------- The EcoDL workshop solicits both long and short paper submissions: § Long Papers: Up to 15 LNCS style pages, including references. § Short Papers: Up to 10 LNCS style pages, including references. All accepted workshop papers will be published in the proceedings of the Springer series Communications in Computer and Information Science (CCIS). For detailed formatting instructions, please refer to the following link<https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…>. Important dates ----------- Paper Submission: 16th May 2025 (AOE) Acceptance Notification: 20th June 2025 (AOE) Camera-ready Version: 10th July 2025 (AOE) Workshop: 23rd September 2025 in Tampere, Finland The EcoDL 2025 Workshop is collocated with the The 29th International Conference on Theory and Practice of Digital Libraries (TPDL 2025) https://tpdl2025.github.io/, 23rd to 26th September 2025. EcoDL 2025 Organising Committee ---------------- Jennifer D'Souza, TIB Leibniz Information Centre for Science and Technology, Hannover, Germany Birgitta König-Ries, University of Jena, Germany Tina Heger, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany Marie Kaiser, Bielefeld University, Germany The list of workshops and tutorials at TPDL this year can be found at https://tpdl2025.github.io/Program/workshops_tutorials.html

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2 Postes MCF Section 71, Université de Lille
by Amel Fraisse 11 Mar '25

11 Mar '25

Chères et chers collègues, L'Université de Lille met au concours deux postes de Maître·sse de conférences en 71e section. Poste "Information, Savoir et Société" (réf. 71 MCF 251968) Poste "Information et Transition Numérique" (réf. 71 MCF 251970) Les deux recrutements relèvent du département Sciences de l’Information et du Document (SID) et du laboratoire GERIICO (ULR 4073). Les fiches complètes des postes sont disponibles ici : https://www.univ-lille.fr/enseignantsetenseignants-chercheurs N’hésitez pas à diffuser ces informations dans vos réseaux. Bien cordialement, <> Amel Fraisse Maitresse de Conférences Directrice Département Sciences de l’information et du Document Université de Lille - ICID - Laboratoire GERiiCO amel.fraisse(a)univ-lille.fr <mailto:prenom.nom@univ-lille.fr> / https://pro.univ-lille.fr/amel-fraisse/ <http://www.univ-lille.fr/> Domaine Universitaire de Pont de Bois - Villeneuve d'Ascq Bât. 2 - bureau B2.467 T. +33 (0)3 20 41 69 38

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Re: 3-year postdoc position in NLP at the University of Oslo
by Lilja Øvrelid 11 Mar '25

11 Mar '25

(Apologies, this time with the correct link). A position as Postdoctoral Research Fellow in Natural Language Processing is available within MediaFutures:Research Centre for Responsible Media Technology & Innovation at the Language Technology Group (LTG) at the University of Oslo (UiO), Norway. The closing date is April 4th. For more information about the position and the research group, please see the full announcement here: https://www.jobbnorge.no/en/available-jobs/job/276909/postdoctoral-research… Please do not hesitate to contact me for any further information. Best regards, Lilja From: Lilja Øvrelid via Corpora <corpora(a)list.elra.info> Reply to: Lilja Øvrelid <liljao(a)ifi.uio.no> Date: Tuesday, 11 March 2025 at 09:31 To: "corpora(a)list.elra.info" <corpora(a)list.elra.info> Cc: "nodali(a)helsinki.fi" <nodali(a)helsinki.fi> Subject: [Corpora-List] 3-year postdoc position in NLP at the University of Oslo A position as Postdoctoral Research Fellow in Natural Language Processing is available within MediaFutures:Research Centre for Responsible Media Technology & Innovation at the Language Technology Group (LTG) at the University of Oslo (UiO), Norway. The closing date is April 4th. For more information about the position and the research group, please see the full announcement here: https://www.jobbnorge.no/en/available-jobs/job/237075/postdoctoral-research… Please do not hesitate to contact me for any further information. Best regards, Lilja

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3-year postdoc position in NLP at the University of Oslo
by Lilja Øvrelid 11 Mar '25

11 Mar '25

A position as Postdoctoral Research Fellow in Natural Language Processing is available within MediaFutures:Research Centre for Responsible Media Technology & Innovation at the Language Technology Group (LTG) at the University of Oslo (UiO), Norway. The closing date is April 4th. For more information about the position and the research group, please see the full announcement here: https://www.jobbnorge.no/en/available-jobs/job/237075/postdoctoral-research… Please do not hesitate to contact me for any further information. Best regards, Lilja

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Call for Papers: Learner Corpus Research in the AI Era: Perspectives from Asia
by Prof CK Jung 10 Mar '25

10 Mar '25

*CALL FOR PAPERS* *Special Issue of The Journal of Asia TEFL *(e-ISSN 2466-1511, ISSN 1738-3102, Indexed in SCOPUS, ESCI) *Learner Corpus Research in the AI Era: Perspectives from Asia* The emergence of generative AI has fundamentally transformed the landscape of corpus linguistics, particularly in the domain of learner corpus research. These powerful technologies are not merely new analytical tools but represent a paradigm shift in how we conceptualise, collect, and interpret learner language data. As large language models become increasingly embedded in language learning environments, researchers must critically examine both the opportunities and challenges they present. In Asian contexts, where technological adoption in education proceeds at remarkable pace, there is an urgent need to investigate how these developments are reshaping our understanding of learner language. This special issue aims to bring together cutting-edge research that explores these transformations from theoretical, methodological and practical perspectives. *1. RESEARCH FOCUS* This special issue invites original contributions that examine how generative AI is reconfiguring learner corpus research. We are particularly interested in empirical studies that demonstrate innovative approaches to corpus compilation, annotation and analysis in the AI era. Successful submissions will offer insights into how corpus linguistics methodologies are adapting to accommodate AI-mediated language learning environments. The integration of AI technologies raises fundamental questions about the nature of learner language itself. How do we distinguish between authentic learner production and AI-assisted output? What new analytical frameworks are required to interpret learner corpora in contexts where AI tools are ubiquitous? How might AI-enhanced analysis reveal patterns in learner language previously undetectable through conventional methods? *Potential topics include:* - Novel approaches to learner corpus compilation and annotation leveraging AI technologies - Methodological innovations in error analysis and pattern identification using AI - Comparative investigations of AI-generated versus authentic learner language - Applications of AI-driven corpus analysis in developing targeted pedagogical interventions - Validity and reliability concerns in corpus research within AI-integrated learning environments - Corpus-informed evaluations of AI feedback systems in language learning contexts *2. SUBMISSION REQUIREMENTS* We welcome empirical studies, methodological papers, and critical analyses that substantively advance our understanding of learner corpus research in the AI era. Submissions should demonstrate technical rigour while addressing practical implications for language teaching and assessment in Asian contexts. Papers should engage critically with existing corpus linguistics methodologies while proposing adaptations necessary for the AI era. *3. IMPORTANT DATES* - *Abstract Submission Deadline: April 7, 2025* - Notification of Acceptance: April 30, 2025 - Full Paper Submission Deadline: November 28, 2025 - Reviews by Reviewers: December 2025 - First Revisions by Authors: January 2026 - Reviews by the Editor: March 2026 - Second Revisions by Authors: April 2026 - Editing for Publishing: April 28 – May 23, 2026 - Expected Publication Date: May 26, 2026 *4. ABSTRACT SUBMISSION GUIDELINES* Abstracts should present a clear articulation of research questions, methodological framework, and the significance of the study to learner corpus research in the AI era. Effective abstracts will demonstrate precision in language and conceptual clarity while highlighting the innovative aspects of the research. Abstracts should not exceed 500 words and must be submitted by April 7, 2025 through the following link: *Abstract submission (Deadline: April 7, 2025)*: https://forms.gle/njjoaBCuv4mGnzUz9 *5. FULL PAPER SUBMISSION GUIDELINES* Authors of accepted abstracts should prepare their manuscripts following The Journal of Asia TEFL guidelines. Full papers must be submitted through the journal's online submission system and will undergo a rigorous double-blind peer review process. Successful papers will present compelling evidence and incisive analysis of how AI technologies are transforming corpus linguistics methodologies and applications. Papers should demonstrate meticulous attention to data collection procedures, analytical frameworks, and the implications of findings for both theory and practice in learner corpus research. For inquiries regarding this special issue, please contact the guest editor, CK Jung, at ckjung(a)inu.ac.kr. We look forward to receiving your contributions to this timely exploration of how generative AI is reshaping the field of learner corpus research. *CK Jung BEng(Hons) Birmingham MSc Warwick EdD Warwick Cert Oxford* Associate Professor | Department of English Language and Literature, Incheon National University, South Korea Director | Institute for Corpus Research, Incheon National University, South Korea Editor-in-Chief | Asia Pacific Journal of Corpus Research, South Korea Editorial Board | Corpora, Edinburgh University Press, UK Editorial Board | English Today, Cambridge University Press, UK

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2nd CFP, 3rd TRR 318 Conference: Contextualizing Explanations (ContEx25), Bielefeld, 17-18 June
by cimiano＠cit-ec.uni-bielefeld.de 10 Mar '25

10 Mar '25

2nd Call for Papers: 3rd TRR 318 Conference: Contextualizing Explanations (ContEx25) http://contex2025.net/ As AI systems are used more and more in high-stakes domains, it also becomes ever-more important to make AI systems transparent to ensure meaningful human control and empower human users to contest or override AI-based decisions. Without sufficient transparency, increasingly complex and autonomous AI systems may leave users feeling overwhelmed and out of control, which is legally and ethically unacceptable, especially in the context of high-stakes decisions. For the users to feel empowered rather than out of control, explanations need to be relevant, providing sufficient information on which basis an output can be contested or challenged. It has been increasingly noted by the XAI community that no one explanation can fit all needs. Further, recent approaches have advocated for a more participative approach to XAI in which users are not only involved but can directly shape and guide the explanations given by a certain AI System. The 3rd TRR 318 Conference: Contextualizing Explanations is an international and interdisciplinary conference focusing on the question how explanations can be contextualized to increase their relevance and empower users. Key research questions that we want to explore during the conference include: How do contextual variables influence the effectiveness of explanations? What are the relevant context factors to be taken into account in adapting an explanation to specific domains, users, or situations? How can context be represented algorithmically to support contextual adaptation of XAI explanations? What new architectures or approaches in XAI support the dynamic adaptation of explanations with respect to changing user needs? How can user modelling support a more personalized explanation process? In which ways can the dynamics of context be modelled? How can the suitability of contextually adapted explanations be studied / validated / evaluated? Which explanation processes are particularly suitable for which context? Which context-specific outcomes are influenced by explanations? How can XAI empower users across diverse contexts to make informed decisions and effectively interact with AI systems? What constitutes a useful taxonomy for categorizing contexts in which explanations are provided? What are the various contexts in which explanations are provided and utilized? The 3rd TRR318 Conference: Contextualizing Explanations invites contributions from a wide range of disciplines (computational but also human/social science) seeking to contribute to advancing research on how explanations can be contextually adapted. We invite interested participants to submit a two page abstract (+ references) using the LNCS Springer template via Easychair: https://easychair.org/conferences/directory?a=33811429 The abstracts will be peer-reviewed and appear as Proceedings published by Bielefeld University Press. The conference is hosted and supported by the TRR 318 “Constructing Explainability”: http://trr318.de <http://trr318.de/> Organizing Committee: Philipp Cimiano (Bielefeld University) Benjamin Paaßen (Bielefeld University) Anna-Lisa Vollmer (BIelefeld University) Invited Speakers: Angelo Cangelosi (University of Manchester) Virginia Dignum (Umeå University) Kacper Sokol (ETH Zurich) Important Dates: Deadline for Submissions: March 31st Notification of Acceptance: April 30th Conference: 17th and 18th of June, Bielefeld Prof. Dr. Philipp Cimiano AG Semantic Computing Coordinator of the Cognitive Interaction Technology Center (CITEC) Co-Director of the Joint Artificial Intelligence Institute (JAII) Universität Bielefeld Tel: +49 521 106 12249 Fax: +49 521 106 6560 Mail: cimiano(a)cit-ec.uni-bielefeld.de Personal Zoom Room: https://uni-bielefeld.zoom-x.de/my/pcimiano Office CITEC-2.307 Universitätsstr. 21-25 33615 Bielefeld, NRW Germany

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Linked Data for Corpora of Images of Text
by Hugh Paterson III 10 Mar '25

10 Mar '25

Greetings, I am wondering if anyone here has encountered a linked data vocabulary for shadows in an image? For example, we have digital scans of 3D text objects. When scanned in orientation "A" the shadows fall in a certain direction, when scanned in orientation "B" they fall in another direction. We are using this difference to enhance text detection algorithms. We need to notate in the metadata of the images which orientation they have relative to their shadows. Has anyone worked with a linked data vocabulary like this? The basic concept of how a shadow falls within an image is fundamental to photography and art in general. I haven't found a vocabulary in use within those domains either. We would be happy to reuse vocabulary terms from such domains. Kind Regards, Hugh Paterson III Krateros Project Manager Institute for Advanced Study https://www.ias.edu/krateros hpaterson(a)ias.edu

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Final call: NLP + social science postdoc at IT University of Copenhagen
by Anna Rogers 10 Mar '25

10 Mar '25

The Data Science section at the IT University of Copenhagen has an open position for a postdoc, funded for 2 years, on the topic of *scaling up qualitative interviews with Large Language Models* (LLMs). The project is a collaboration with the Center for Social Data Science <https://sodas.ku.dk/> at the university of Copenhagen. This is a NLP position, but some relevant background in social sciences or psychology is a plus. *Application deadline is March 17 2025*. Applications can be submitted via ITU job portal: Application link: https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181… IT University of Copenhagen is the leading Danish university dedicated to various aspects of IT technology, and Copenhagen is one of the happiest and most livable cities in the world. The candidates will be part of NLPNorth research group <https://nlpnorth.github.io/> (with 5 full-time faculty working in various areas of NLP), as well as Pioneer Center for AI <https://www.aicentre.dk/>. The postdoc will be hosted by Assoc. Prof. Anna Rogers <https://annargrs.github.io/>, to whom inquiries about the project can be directed (arog(a)itu.dk). The domain expert on this project is Hjalmar Alexander Bang Carlsen (sociology, hc(a)sodas.ku.dk). -- Anna Rogers Associate Professor IT University of Copenhagen http://annargrs.github.io/

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Call for Participation: Shared task on Clickbait Detection and Spoiling in Spanish - TA1C
by Luis Chiruzzo - Inco 10 Mar '25

10 Mar '25

*** Call for Participation for TA1C at IberLEF 2025 *** TA1C (Te Ahorré Un Click) Clickbait Detection and Spoiling in Spanish at IberLEF 2025 https://codalab.lisn.upsaclay.fr/competitions/21819 Clickbait is a widespread phenomenon in online news: it is a way of creating headlines and teasers aimed at capturing readers’ attention in order to increase traffic, relegating the function of informing to a secondary role. There is no clear consensus at the moment about how to define clickbait exactly, with some contradictory definitions that usually are based on the deceptive effect created by the news failing to deliver what they promise, or content based related phenomena such as sensationalism or yellow journalism. For this task we will take the following definition, based on Loewenstein's information gap theory: “Clickbait is a method for generating teasers, especially online, that deliberately omits part of the information with the goal of generating curiosity by creating an information gap, thereby attracting the readers' attention and making them click”. Although clickbait started in low-reputation web-exclusive media that focused on political propaganda or soft-news, such as The Huffington Post, Buzzfeed and Upworthy, it has gained prominence across all types of news and media. However, it is usually perceived as annoying and it can lead to misinformation. Spoiling the clickbait involves satisfying the curiosity by answering the information gap created. This way, the reader could have all of the information and can decide to read the complete article based on interest and not curiosity, just as if the headline was written in a traditional way. In this shared task we will provide a dataset of media tweets written in different varieties of Spanish and from different sources, with their corresponding associated media articles. Participants will be asked to solve the following tasks: * Clickbait Detection: Determine if the content of a tweet that links to a media article is clickbait, given the previous definition of clickbait. This is a binary classification task. * Clickbait Spoiling: Given a clickbait teaser (tweet and title) and the corresponding news article, generate or extract from the article a short text that, as concisely as possible (280 characters max), fills the information gap, satisfying the generated curiosity, or otherwise indicate that the articles has no response for it. The generated text must be in Spanish. How to participate: If you want to participate in this task, please join our Codalab competition <https://codalab.lisn.upsaclay.fr/competitions/21819>: Important Dates: * April 1st, 2025: training and development sets. * May 27th, 2025: test set and open for submissions. * June 3rd, 2025: publication of results. * June 12th, 2025: paper submission. * June 20th, 2025: notification of acceptance. * June 27th, 2025: camera-ready paper submission. * September, 2025: IberLEF 2025 Workshop.

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Full Professorship (tenured W3) in AI and ML, Bonn, Germany
by Prof. Dr. Lucie Flek 10 Mar '25

10 Mar '25

The *University of Bonn*, one of the few selected Universities of Excellence in Germany, is now inviting applications for a tenured and excellently equipped* Full Professorship (W3) in Artificial Intelligence and Machine Learning* as a strategic flagship part of our *Lamarr Institute for Machine Learning and Artificial Intelligence.* Applicants are expected to have demonstrated internationally outstanding research in one or more relevant subfields of Artificial Intelligence with a strong focus on Machine Learning, ideally related to one or more of the major research areas of the Lamarr Institute: - Resource-Aware ML: Optimize algorithms for available resources and new architectures - Trustworthy AI: Make AI ethical, reliable, understandable, and certifiable - Hybrid ML: Combine data and knowledge in ML algorithms - Human-Centered Systems: Exploit human interaction contexts when learning from data - Embodied AI: Build ML algorithms that work in physical and autonomous systems Apply by March 15th, 2025: https://www.uni-bonn.de/en/university/working-at-the-university/job-opportu… The professorship will be appointed as Tenured Full Professor (W3) within the Institute of Computer Science. Dual-career appointments are possible for suitable candidates. German language skills are not required. We expect from the candidate the capability of positioning the Lamarr Institute towards society and industry and willingness to *contribute to the institute’s strategic responsibilities.* The acquisition of third-party research funds and contribution to joint grant activities in computer science are requested. We welcome applications regardless of nationality, ethnic and social origin, religion/belief, age, sexual orientation and identity. Formal requirements are defined by § 36 of the Higher Education Act of North Rhine-Westphalia (Hochschulgesetz Nordrhein-Westfalen).

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2026

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Corpora