@inproceedings{grezes-etal-2025-overview,
title = "Overview of {TRACS}: the Telescope Reference and Astronomy Categorization Dataset {\&} Shared Task",
author = "Grezes, Felix and
Bartlett, Jennifer Lynn and
Lockhart, Kelly and
Accomazzi, Alberto and
Seefried, Ethan and
Pandiri, Anjali and
Ghosal, Tirthankar",
editor = "Accomazzi, Alberto and
Ghosal, Tirthankar and
Grezes, Felix and
Lockhart, Kelly",
booktitle = "Proceedings of the Third Workshop for Artificial Intelligence for Scientific Publications",
month = dec,
year = "2025",
address = "Mumbai, India and virtual",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.wasp-main.2/",
doi = "10.18653/v1/2025.wasp-main.2",
pages = "5--15",
ISBN = "979-8-89176-310-4",
abstract = "To evaluate the scientific influence of observational facilities, astronomers examine the body of publications that have utilized data from those facilities. This depends on curated bibliographies that annotate and connect data products to the corresponding literature, enabling bibliometric analyses to quantify data impact. Compiling such bibliographies is a demanding process that requires expert curators to scan the literature for relevant names, acronyms, and identifiers, and then to determine whether and how specific observations contributed to each publication. These bibliographies have value beyond impact assessment: for research scientists, explicit links between data and literature form an essential pathway for discovering and accessing data. Accordingly, by building on the work of librarians and archivists, telescope bibliographies can be repurposed to directly support scientific inquiry. In this context, we present the Telescope Reference and Astronomy Categorization Shared task (TRACS) and its accompanying dataset, which comprises more than 89,000 publicly available English-language texts drawn from space telescope bibliographies. These texts are labeled according to a new, compact taxonomy developed in consultation with experienced bibliographers."
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<abstract>To evaluate the scientific influence of observational facilities, astronomers examine the body of publications that have utilized data from those facilities. This depends on curated bibliographies that annotate and connect data products to the corresponding literature, enabling bibliometric analyses to quantify data impact. Compiling such bibliographies is a demanding process that requires expert curators to scan the literature for relevant names, acronyms, and identifiers, and then to determine whether and how specific observations contributed to each publication. These bibliographies have value beyond impact assessment: for research scientists, explicit links between data and literature form an essential pathway for discovering and accessing data. Accordingly, by building on the work of librarians and archivists, telescope bibliographies can be repurposed to directly support scientific inquiry. In this context, we present the Telescope Reference and Astronomy Categorization Shared task (TRACS) and its accompanying dataset, which comprises more than 89,000 publicly available English-language texts drawn from space telescope bibliographies. These texts are labeled according to a new, compact taxonomy developed in consultation with experienced bibliographers.</abstract>
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%0 Conference Proceedings
%T Overview of TRACS: the Telescope Reference and Astronomy Categorization Dataset & Shared Task
%A Grezes, Felix
%A Bartlett, Jennifer Lynn
%A Lockhart, Kelly
%A Accomazzi, Alberto
%A Seefried, Ethan
%A Pandiri, Anjali
%A Ghosal, Tirthankar
%Y Accomazzi, Alberto
%Y Ghosal, Tirthankar
%Y Grezes, Felix
%Y Lockhart, Kelly
%S Proceedings of the Third Workshop for Artificial Intelligence for Scientific Publications
%D 2025
%8 December
%I Association for Computational Linguistics
%C Mumbai, India and virtual
%@ 979-8-89176-310-4
%F grezes-etal-2025-overview
%X To evaluate the scientific influence of observational facilities, astronomers examine the body of publications that have utilized data from those facilities. This depends on curated bibliographies that annotate and connect data products to the corresponding literature, enabling bibliometric analyses to quantify data impact. Compiling such bibliographies is a demanding process that requires expert curators to scan the literature for relevant names, acronyms, and identifiers, and then to determine whether and how specific observations contributed to each publication. These bibliographies have value beyond impact assessment: for research scientists, explicit links between data and literature form an essential pathway for discovering and accessing data. Accordingly, by building on the work of librarians and archivists, telescope bibliographies can be repurposed to directly support scientific inquiry. In this context, we present the Telescope Reference and Astronomy Categorization Shared task (TRACS) and its accompanying dataset, which comprises more than 89,000 publicly available English-language texts drawn from space telescope bibliographies. These texts are labeled according to a new, compact taxonomy developed in consultation with experienced bibliographers.
%R 10.18653/v1/2025.wasp-main.2
%U https://aclanthology.org/2025.wasp-main.2/
%U https://doi.org/10.18653/v1/2025.wasp-main.2
%P 5-15
Markdown (Informal)
[Overview of TRACS: the Telescope Reference and Astronomy Categorization Dataset & Shared Task](https://aclanthology.org/2025.wasp-main.2/) (Grezes et al., WASP 2025)
ACL