swMATH – An Information Service for Mathematical Software

Greuel, Gert–Martin; Sperber, Wolfram

doi:10.1007/978-3-662-44199-2_103

Cited by 18 publications

(10 citation statements)

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“… Howison & Bullard (2016) report that articles published in high impact journals mention more software. The platform swMATH ( Greuel & Sperber, 2014 ) aims to establish a mapping of software used in mathematical literature by manually labeling software present in zbMATH articles pre-filtered through an automatic, heuristic search.…”

Section: Related Workmentioning

confidence: 99%

The role of software in science: a knowledge graph-based analysis of software mentions in PubMed Central

Schindler

Bensmann

Dietze

2022

PeerJ Computer Science

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Science across all disciplines has become increasingly data-driven, leading to additional needs with respect to software for collecting, processing and analysing data. Thus, transparency about software used as part of the scientific process is crucial to understand provenance of individual research data and insights, is a prerequisite for reproducibility and can enable macro-analysis of the evolution of scientific methods over time. However, missing rigor in software citation practices renders the automated detection and disambiguation of software mentions a challenging problem. In this work, we provide a large-scale analysis of software usage and citation practices facilitated through an unprecedented knowledge graph of software mentions and affiliated metadata generated through supervised information extraction models trained on a unique gold standard corpus and applied to more than 3 million scientific articles. Our information extraction approach distinguishes different types of software and mentions, disambiguates mentions and outperforms the state-of-the-art significantly, leading to the most comprehensive corpus of 11.8 M software mentions that are described through a knowledge graph consisting of more than 300 M triples. Our analysis provides insights into the evolution of software usage and citation patterns across various fields, ranks of journals, and impact of publications. Whereas, to the best of our knowledge, this is the most comprehensive analysis of software use and citation at the time, all data and models are shared publicly to facilitate further research into scientific use and citation of software.

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Section: Related Workmentioning

confidence: 99%

The role of software in science: a knowledge graph-based analysis of software mentions in PubMed Central

Schindler

Bensmann

Dietze

2022

PeerJ Computer Science

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“…Mozilla Science, GitHub, Zenodo, and Software Heritage facilitate archiving and identification of software releases (Di Cosmo, 2020; Di Cosmo, Gruenpeter, & Zacchiroli, 2019) to support new software citation practices. Digital repositories and registries such as HAL (Hyper articles en Ligne), Astrophysics Source Code Library (ASCL), and swMath catalog software, provide metadata and links to software (Allen & Schmidt, 2014; Di Cosmo, Gruenpeter, Marmol, et al, 2019; Greuel & Sperber, 2014). swMath also tracks citations to the software (Greuel & Sperber, 2014).…”

Section: Related Workmentioning

confidence: 99%

“…Digital repositories and registries such as HAL (Hyper articles en Ligne), Astrophysics Source Code Library (ASCL), and swMath catalog software, provide metadata and links to software (Allen & Schmidt, 2014; Di Cosmo, Gruenpeter, Marmol, et al, 2019; Greuel & Sperber, 2014). swMath also tracks citations to the software (Greuel & Sperber, 2014). The Research Resource Identification initiative (RRID) provides unique identifiers for research resources including software (Bandrowski & Martone, 2016; Bandrowski et al, 2016).…”

Section: Related Workmentioning

confidence: 99%

“…For instance, leveraging the URL patterns specific to R package management system, Li and Yan (2018) achieved a precision of .84 and a recall of .87 in identifying mentions of R packages in 13,694 PLoS journal articles. Rules, once created, scale well, but are limited to specific domains or specific software ecosystems (Greuel & Sperber, 2014; Hwang, Pauloo, & Carlen, 2019).…”

Section: Related Workmentioning

confidence: 99%

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Softcite dataset: A dataset of software mentions in biomedical and economic research publications

Cohoon

Lopez³

et al. 2021

Asso for Info Science & Tech

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Software contributions to academic research are relatively invisible, especially to the formalized scholarly reputation system based on bibliometrics. In this article, we introduce a gold‐standard dataset of software mentions from the manual annotation of 4,971 academic PDFs in biomedicine and economics. The dataset is intended to be used for automatic extraction of software mentions from PDF format research publications by supervised learning at scale. We provide a description of the dataset and an extended discussion of its creation process, including improved text conversion of academic PDFs. Finally, we reflect on our challenges and lessons learned during the dataset creation, in hope of encouraging more discussion about creating datasets for machine learning use.

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“…2 Publication-based approached of swMATH swMATH is one of the most comprehensive information services for MSW [1]. Based on simple heuristics, swMATH identifies MSW in scientific articles from its underlying bibliographic database zbMATH 6 , consisting of nearly 120,000 publications referring to MSW.…”

Section: Introductionmentioning

confidence: 99%

Linking Mathematical Software in Web Archives

Holzmann

Runnwerth

Sperber

2016

Mathematical Software – ICMS 2016

Self Cite

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Abstract. The Web is our primary source of all kinds of information today. This includes information about software as well as associated materials, like source code, documentation, related publications and change logs. Such data is of particular importance in research in order to conduct, comprehend and reconstruct scientific experiments that involve software. swMATH, a mathematical software directory, attempts to identify software mentions in scientific articles and provides additional information as well as links to the Web. However, just like software itself, the Web is dynamic and most likely the information on the Web has changed since it was referenced in a scientific publication. Therefore, it is crucial to preserve the resources of a software on the Web to capture its states over time. We found that around 40% of the websites in swMATH are already included in an existing Web archive. Out of these, 60% of contain some kind of documentation and around 45% even provide downloads of software artifacts. Hence, already today links can be established based on the publication dates of corresponding articles. The contained data enable enriching existing information with a temporal dimension. In the future, specialized infrastructure will improve the coverage of software resources and allow explicit references in scientific publications.

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swMATH – An Information Service for Mathematical Software

Cited by 18 publications

References 0 publications

The role of software in science: a knowledge graph-based analysis of software mentions in PubMed Central

The role of software in science: a knowledge graph-based analysis of software mentions in PubMed Central

Softcite dataset: A dataset of software mentions in biomedical and economic research publications

Linking Mathematical Software in Web Archives

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