Netscity workshop - Geocollab Project

Transcript

1. NETSCITY tutorial – GEOCOLLAB Workshop 2022
   Unveiling world scale scientific production and collaborations between
   cities
   

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2. GEOCOLLAB project
   Two main research areas:
   oMarine science (research on seaweeds and algae)
   o Gene editing
   o Else?
   Possible sources (what do we already have access to?):
   o Bibliographic databases (WoS, Scopus, …)
   o Conference data (to be identified)
   oResearch Projects data (ERC, ANR, Research in Svalbard…)
   o Contracts (science-industry partnerships); Patents…
   o Phd theses (Theses.fr, etc.)
   

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3. Spatial information
   • Postal address:
   5 cours des Humanités, 93000, Aubervilliers, FR
   • Organisation (without a city field):
   University of Edinburgh, Scotland, UK (It can be in Roslin or Edinburgh)
   • Organisation + ROR/Grid ID (Dimensions.ai; OpenAlex)
   Caltech, https://ror.org/05dxps055
   Max Planck Society, https://ror.org/01hhn8329 (with many child institutes)
   

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4. Existing softwares for bibliometric mapping
   CiteSpace, Leydesdorff’s programs and Sci2 Tool
   o geocoding data at the street level
   o mapping network data using Google Earth Maps and Yahoo! Maps using KML files
   From Chen, 2016
   A practical guide for mapping
   Scientific litterature
   

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5. Bibliographic data – what is the row material we need?
   « CITY, PROVINCE, COUNTRY »
   city province country
   Monterotondo RM Italy
   Milan Italy
   Rome Italy
   Khania Greece
   POSTAL ADDRESSES
   

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6. Other types of sources: e.g. conference attendance
   Netconf project
   With B. Bernela
   & F. Briatte
   

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7. Map by M. Maisonobe, CNRS. Data: LORD & TAI-NUI
   

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8. Data processing :
   1) Extraction of
   addresses
   1) Geocoding
   1) Clustering at the
   urban
   area/country
   levels
   File with bibliographic
   metadata
   Sources: Web Of
   Science, Scopus, or
   personal files in .csv
   Input Netscity Outputs
   ●
   Cartes
   ● Tables
   ● Fichier
   d’export
   Context
   

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9. Many heterogeneities, transliteration issues and data entry errors
   

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10. Why should we agregate the geocoded data at the urban area level?
    The output of the geocoding process for 2012 Web of Science publications – Québec area
    

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11. Why should we agregate the geocoded data at the urban area level?
    The output of the geocoding process for 2012 Web of Science publications – London area
    

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12. The case of Rome
    

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13. The variable administrative fragmentation of the territory at the world level
    

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14. Methods: grouping into agglomerations
    Issues
    ▪ Group together publication sites that are in the same urban area.
    ▪ Globally comparable urban areas, despite very different urban realities
    ➢ Search for a delimitation adapted to the urban phenomenon
    ➢ Delimitation by spatial crossing between urban population density and
    scientific publications’ spatial distribution
    Maisonobe, Jégou & Eckert, 2018, Delineating urban agglomerations across the world: a dataset for
    studying the spatial distribution of academic research at city level
    DOI : 10.4000/cybergeo.29637
    

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16. Counting methods:
    arbitrating bet. Full & fractional countings
    References: Van Hooydonk, 1997; Gauffriau et al., 2008, Leydesdorff & Park, 2017
    • Full: the total number of addresses/urban areas/countries per publications
    • Fractional: the sum of each fractioned credit totals one (avoiding double counts)
    → With NETSCITY the reference unit for normalization can be the address, the urban area
    or the country
    

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17. Counting methods:
    arbitrating bet. Full & fractional countings
    2 variables can be normalised and mapped with NETSCITY
    1. Number of publications/projects per geographical entity (the total number
    geographical entities involved in a publication/project)
    1. Intensity of scientific collaboration between geographical entities (the total
    number of links between the geographical entities involved in a
    publication/project)
    For instance, if a given publication stems from three different urban areas, each inter-urban link receives
    1/3 as a weight for this publication. More generally, if a publication is co-signed from 𝑛 urban areas, each
    pair of urban areas (A, B), with A < B,
    is assigned a value 𝑙 equals to:
    1/𝑛(𝑛 − 1)/2 = 2/(𝑛(𝑛 − 1))
    

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18. Weighted projection method
    This method is the normalised counting method used in the web application NETSCITY (Maisonobe et al. 2019)
    A variant: « Newman » projection method (2001). See https://toreopsahl.com/tnet/two-mode-networks/
    2-mode 1-mode
    

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19. Query on the Web of Science Core Collection
    

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20. Export format (Tab-delimited)
    

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21. https://www.irit.fr/netscity/
    The example of scientific production about Ectocarpus indexed in the WoS CC between 1920 & 2022
    

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22. Select the source format
    

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23. Wait while the geocoding
    

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24. Geocoding report
    

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25. Manual correction
    

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26. Export and/or check the address table
    

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28. Normalised nb of publications per country
    

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29. Normalised nb of publications per urban area
    

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30. Normalised nb of collab. bet. countries
    

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31. Normalised nb of collab. bet. urban areas
    

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32. Diagrammes & histogrammes (.csv et
    .jpg can be exported)
    

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33. Stock map at the country level
    

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34. Stock map at the urban area level
    

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35. Flow map bet. countries
    

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36. Carte des collaborations fractionnées
    entre aires urbaines
    

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37. Network of collab. bet. countries
    

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38. Network of collab. bet. urban areas
    

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39. Application case
    Go on page: https://geoscimo.univ-tlse2.fr/analysis-of-the-
    ectocarpus-corpus-march-2022/
    

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40. Seaweeds and algae research
    Topic query:
    TS = (seaweed* OR alga OR kelp* OR algae* OR algal* OR seagrass* OR sea plant* OR phyco*
    OR Chlorell* OR Protothec* OR Charophy* OR Chlorophyt* OR Rhodophy* OR Cryptophy* OR
    Haptophy* OR Charophy* OR Chlorarachniophy* OR Glaucophy* OR rockweed* OR dulse* OR
    dillisk* OR dilsk* OR carragheen moss* OR sea lettuce* OR Chondrus)
    Should we add: microalga, macroalga, phytoplankton, cyanobacteria? Else?
    See: https://www.sciencedirect.com/science/article/pii/B9780128170762000135
    

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41. The scientific production on algae and seaweeds in Scotland
    

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42. Distribution of Scotland’s publications on algae per scientific specialities
    

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46. Prospects
    • Collaborative space: internal repository for the project with
    useful datasets and scripts
    • R workshop and tutorial (tidyverse + cartigraph)
    • Issue of corpus delineation
    

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47. Reference
    Marion Maisonobe, Laurent Jégou, Nikita Yakimovich, Guillaume
    Cabanac (2019).
    NETSCITY: a geospatial application to analyse and map world
    scale production and collaboration data between cities.
    In ISSI’19: Proceedings of the 17th International Conference on
    Scientometrics and Informetrics, Tome 1, p. 631-642, Rome:
    Edizioni Efesto. [PDF]
    

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