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ir_metadata: An Extensible Metadata Schema for IR Experiments

Published: 07 July 2022 Publication History

Abstract

The information retrieval (IR) community has a strong tradition of making the computational artifacts and resources available for future reuse, allowing the validation of experimental results. Besides the actual test collections, the underlying run files are often hosted in data archives as part of conferences like TREC, CLEF, or NTCIR. Unfortunately, the run data itself does not provide much information about the underlying experiment. For instance, the single run file is not of much use without the context of the shared task's website or the run data archive. In other domains, like the social sciences, it is good practice to annotate research data with metadata. In this work, we introduce \textttir\_metadata - an extensible metadata schema for TREC run files based on the PRIMAD model. We propose to align the metadata annotations to PRIMAD, which considers components of computational experiments that can affect reproducibility. Furthermore, we outline important components and information that should be reported in the metadata and give evidence from the literature. To demonstrate the usefulness of these metadata annotations, we implement new features in \textttrepro\_eval that support the outlined metadata schema for the use case of reproducibility studies. Additionally, we curate a dataset with run files derived from experiments with different instantiations of PRIMAD components and annotate these with the corresponding metadata. In the experiments, we cover reproducibility experiments that are identified by the metadata and classified by PRIMAD. With this work, we enable IR researchers to annotate TREC run files and improve the reuse value of experimental artifacts even further.

Supplementary Material

MP4 File (SIGIR22-rs1684.mp4)
Experimentation in information retrieval (IR) research is an inherently data-driven process that often results in experimental artifacts - so-called run files. We propose making the run files even more valuable by annotating them with metadata to promote the comparability, transparency, and reproducibility of IR experiments. This video introduces the outlined metadata schema and an overview of the related resources. From a practical point of view, we propose to add the metadata, similar to a file header, as comments at the beginning of the run file. Furthermore, we align the metadata schema to the PRIMAD model, providing a conceptual taxonomy for reproducible IR experiments. Besides the metadata schema, we introduce the software support of repro_eval (also with the help of a Colab notebook) and provide annotated runs as a curated dataset hosted in a Zenodo archive. Finally, we show how the metadata facilitates meta-evaluations by the use-case of reproducibility studies.

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cover image ACM Conferences
SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
July 2022
3569 pages
ISBN:9781450387323
DOI:10.1145/3477495
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  • (2024)Browsing and Searching Metadata of TRECProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657873(313-323)Online publication date: 10-Jul-2024
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  • (2023)The Information Retrieval Experiment PlatformProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591888(2826-2836)Online publication date: 19-Jul-2023
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