A Study of Computational Reproducibility using URLs Linking to Open Access Datasets and Software

Lamia Salsabil, Jian Wu, Muntabir Hasan Choudhury, William A. Ingram, Edward A. Fox, Sarah M. Rajtmajer, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Datasets and software packages are considered important resources that can be used for replicating computational experiments. With the advocacy of Open Science and the growing interest of investigating reproducibility of scientific claims, including URLs linking to publicly available datasets and software packages has become an institutionalized part of research publications. In this preliminary study, we investigated the disciplinary dependency and chronological trends of including open access datasets and software (OADS) in electronic theses and dissertations (ETDs), based on a hybrid classifier called OADSClassifier, consisting of a heuristic and a supervised learning model. The classifier achieves the best F1 of 0.92. We found that the inclusion of OADS-URLs exhibited a strong disciplinary dependence and the fraction of ETDs containing OADS-URLs has been gradually increasing over the past 20 years. We developed and share a ground truth corpus consisting of 500 manually labeled sentences containing URLs from scientific papers. The dataset and source code are available at https://github.com/lamps-lab/oadsclassifier.

Original languageEnglish (US)
Title of host publicationWWW 2022 - Companion Proceedings of the Web Conference 2022
PublisherAssociation for Computing Machinery, Inc
Pages784-788
Number of pages5
ISBN (Electronic)9781450391306
DOIs
StatePublished - Apr 25 2022
Event31st ACM Web Conference, WWW 2022 - Virtual, Online, France
Duration: Apr 25 2022 → …

Publication series

NameWWW 2022 - Companion Proceedings of the Web Conference 2022

Conference

Conference31st ACM Web Conference, WWW 2022
Country/TerritoryFrance
CityVirtual, Online
Period4/25/22 → …

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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