IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v107y2016i2d10.1007_s11192-016-1885-6.html
   My bibliography  Save this article

Scientific workflows for bibliometrics

Author

Listed:
  • Arzu Tugce Guler

    (Leiden University Medical Center)

  • Cathelijn J. F. Waaijer

    (Leiden University)

  • Magnus Palmblad

    (Leiden University Medical Center)

Abstract

Scientific workflows organize the assembly of specialized software into an overall data flow and are particularly well suited for multi-step analyses using different types of software tools. They are also favorable in terms of reusability, as previously designed workflows could be made publicly available through the myExperiment community and then used in other workflows. We here illustrate how scientific workflows and the Taverna workbench in particular can be used in bibliometrics. We discuss the specific capabilities of Taverna that makes this software a powerful tool in this field, such as automated data import via Web services, data extraction from XML by XPaths, and statistical analysis and visualization with R. The support of the latter is particularly relevant, as it allows integration of a number of recently developed R packages specifically for bibliometrics. Examples are used to illustrate the possibilities of Taverna in the fields of bibliometrics and scientometrics.

Suggested Citation

  • Arzu Tugce Guler & Cathelijn J. F. Waaijer & Magnus Palmblad, 2016. "Scientific workflows for bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 385-398, May.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1885-6
    DOI: 10.1007/s11192-016-1885-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-016-1885-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-016-1885-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
    2. Feinerer, Ingo & Hornik, Kurt & Meyer, David, 2008. "Text Mining Infrastructure in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i05).
    3. Gagolewski, Marek, 2011. "Bibliometric impact assessment with R and the CITAN package," Journal of Informetrics, Elsevier, vol. 5(4), pages 678-692.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Siyi He & Yue Zhao & Yongsheng Fan & Xue Zhao & Jun Yu & Jie Xie & Chunhong Wang & Jianmei Su, 2019. "Research Trends and Hotspots Analysis Related to Monocarboxylate Transporter 1: A Study Based on Bibliometric Analysis," IJERPH, MDPI, vol. 16(7), pages 1-15, March.
    2. Juan F. Prados-Castillo & Miguel Ángel Solano-Sánchez & Pilar Guaita Fernández & José Manuel Guaita Martínez, 2023. "Potential of the Crypto Economy in Financial Management and Fundraising for Tourism," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
    3. Johanna Andrea Navarro-Espinosa & Manuel Vaquero-Abellán & Alberto-Jesús Perea-Moreno & Gerardo Pedrós-Pérez & Maria del Pilar Martínez-Jiménez & Pilar Aparicio-Martínez, 2022. "Gamification as a Promoting Tool of Motivation for Creating Sustainable Higher Education Institutions," IJERPH, MDPI, vol. 19(5), pages 1-20, February.
    4. Judit Oláh & Eszter Krisán & Anna Kiss & Zoltán Lakner & József Popp, 2020. "PRISMA Statement for Reporting Literature Searches in Systematic Reviews of the Bioethanol Sector," Energies, MDPI, vol. 13(9), pages 1-35, May.
    5. He, Zhihao & Gong, Kaiyuan & Zhang, Zhiliang & Dong, Wenbiao & Feng, Hao & Yu, Qiang & He, Jianqiang, 2022. "What is the past, present, and future of scientific research on the Yellow River Basin? —A bibliometric analysis," Agricultural Water Management, Elsevier, vol. 262(C).
    6. Juan F. Prados-Castillo & Juan Antonio Torrecilla-García & Georgette Andraz & José Manuel Guaita Martínez, 2023. "Blockchain in Peer-to-Peer Platforms: Enhancing Sustainability and Customer Experience in Tourism," Sustainability, MDPI, vol. 15(22), pages 1-17, November.
    7. Tamás Stadler & Ágoston Temesi & Zoltán Lakner, 2022. "Soil Chemical Pollution and Military Actions: A Bibliometric Analysis," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    8. Zoltán Lakner & Brigitta Plasek & Gyula Kasza & Anna Kiss & Sándor Soós & Ágoston Temesi, 2021. "Towards Understanding the Food Consumer Behavior–Food Safety–Sustainability Triangle: A Bibliometric Approach," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    9. Benu George & Pradeep Varathan & T. V. Suchithra, 2020. "Meta-analysis on big data of bioactive compounds from mangrove ecosystem to treat neurodegenerative disease," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1539-1561, March.
    10. Guler, Arzu Tugce & Waaijer, Cathelijn J.F. & Mohammed, Yassene & Palmblad, Magnus, 2016. "Automating bibliometric analyses using Taverna scientific workflows: A tutorial on integrating Web Services," Journal of Informetrics, Elsevier, vol. 10(3), pages 830-841.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stefano Sbalchiero & Maciej Eder, 2020. "Topic modeling, long texts and the best number of topics. Some Problems and solutions," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(4), pages 1095-1108, August.
    2. Daoud, Adel & Kohl, Sebastian, 2016. "How much do sociologists write about economic topics? Using big data to test some conventional views in economic sociology, 1890 to 2014," MPIfG Discussion Paper 16/7, Max Planck Institute for the Study of Societies.
    3. Holand, Øystein & Contiero, Barbara & Næss, Marius W. & Cozzi, Giulio, 2024. "“The Times They Are A-Changin' “ – research trends and perspectives of reindeer pastoralism – A review using text mining and topic modelling," Land Use Policy, Elsevier, vol. 136(C).
    4. Cho, Yung-Jan & Fu, Pei-Wen & Wu, Chi-Cheng, 2017. "Popular Research Topics in Marketing Journals, 1995–2014," Journal of Interactive Marketing, Elsevier, vol. 40(C), pages 52-72.
    5. Motta Queiroz, Mariza & Roque, Carlos & Moura, Filipe & Marôco, João, 2024. "Understanding the expectations of parents regarding their children's school commuting by public transport using latent Dirichlet Allocation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    6. João Guerreiro & Paulo Rita & Duarte Trigueiros, 2016. "A Text Mining-Based Review of Cause-Related Marketing Literature," Journal of Business Ethics, Springer, vol. 139(1), pages 111-128, November.
    7. Abhinav Khare & Qing He & Rajan Batta, 2020. "Predicting gasoline shortage during disasters using social media," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 693-726, September.
    8. Lehotský, Lukáš & Černoch, Filip & Osička, Jan & Ocelík, Petr, 2019. "When climate change is missing: Media discourse on coal mining in the Czech Republic," Energy Policy, Elsevier, vol. 129(C), pages 774-786.
    9. Doblinger, Claudia & Surana, Kavita & Li, Deyu & Hultman, Nathan & Anadón, Laura Díaz, 2022. "How do global manufacturing shifts affect long-term clean energy innovation? A study of wind energy suppliers," Research Policy, Elsevier, vol. 51(7).
    10. Andres, Maximilian & Bruttel, Lisa & Friedrichsen, Jana, 2023. "How communication makes the difference between a cartel and tacit collusion: A machine learning approach," European Economic Review, Elsevier, vol. 152(C).
    11. Hudson Golino & Alexander P. Christensen & Robert Moulder & Seohyun Kim & Steven M. Boker, 2022. "Modeling Latent Topics in Social Media using Dynamic Exploratory Graph Analysis: The Case of the Right-wing and Left-wing Trolls in the 2016 US Elections," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 156-187, March.
    12. Sun, Katherine Qianwen & Slepian, Michael L., 2020. "The conversations we seek to avoid," Organizational Behavior and Human Decision Processes, Elsevier, vol. 160(C), pages 87-105.
    13. Rieger, Jonas & von Nordheim, Gerret, 2021. "corona100d: German-language Twitter dataset of the first 100 days after Chancellor Merkel addressed the coronavirus outbreak on TV," DoCMA Working Papers 4, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA).
    14. Garner, Benjamin & Thornton, Corliss & Luo Pawluk, Anita & Mora Cortez, Roberto & Johnston, Wesley & Ayala, Cesar, 2022. "Utilizing text-mining to explore consumer happiness within tourism destinations," Journal of Business Research, Elsevier, vol. 139(C), pages 1366-1377.
    15. Anke Piepenbrink & Elkin Nurmammadov, 2015. "Topics in the literature of transition economies and emerging markets," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2107-2130, March.
    16. Christian WEISMAYER, 2022. "Applied Research in Quality of Life: A Computational Literature Review," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 17(3), pages 1433-1458, June.
    17. Arenas Gaitán, Jorge & Ramírez-Correa, Patricio E., 2023. "COVID-19 and telemedicine: A netnography approach," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    18. Polyzos, Efstathios & Wang, Fang, 2022. "Twitter and market efficiency in energy markets: Evidence using LDA clustered topic extraction," Energy Economics, Elsevier, vol. 114(C).
    19. Jiang, Hanchen & Qiang, Maoshan & Lin, Peng, 2016. "A topic modeling based bibliometric exploration of hydropower research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 226-237.
    20. Cecilia Elizabeth Bayas Aldaz & Jesus Rodriguez-Pomeda & Leyla Angélica Sandoval Hamón & Fernando Casani, 2020. "Understanding the University-Sustainability Link through Media: A Spanish Perspective," Sustainability, MDPI, vol. 12(12), pages 1-15, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1885-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.