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Datasets, working papers, and peer-reviewed articles produced by MultiObs researchers.

Showing 1–4 of 4

  1. Dataset2026Open Access
    Material suplementar do artigo "A Década do Oceano promove acesso aberto à produção científica no Brasil?"(opens in a new tab)

    Canto, Fabio; Barata, Germana; Lemos, Wadson; Segundo, Washington

    Material suplementar da pesquisa “A Década do Oceano promove acesso aberto à produção científica no Brasil?”, artigo aceito para apresentação na Conferência Lusófona de Ciência Aberta (ConfOA 2026). Este conjunto reúne os dados e materiais suplementares utilizados na pesquisa sobre a produção científica brasileira relacionada ao oceano e sua disponibilidade em Acesso Aberto no contexto da Década das Nações Unidas da Ciência Oceânica para o Desenvolvimento Sustentável. Os dados bibliográficos foram recuperados por meio da API do OpenAlex, considerando publicações entre 2018 e 2025, com pelo menos um autor afiliado a uma instituição brasileira e restritas aos tipos documentais artigo e revisão. O conjunto final analisado é composto por 24.958 publicações. A recuperação foi realizada a partir de duas estratégias complementares: uma baseada na estrutura de classificação temática do OpenAlex, contemplando as subáreas de Oceanografia e Engenharia do Oceano e 46 tópicos relacionados; e outra baseada em busca textual por termos em português e inglês associados ao ambiente marinho, biodiversidade, mudanças climáticas, comunidades costeiras, economia azul e temas correlatos, aplicados aos campos de título e resumo. Os registros foram deduplicados pelo identificador único de trabalho do OpenAlex (work_id). O material suplementar contém os dados utilizados nas análises apresentadas no artigo e a documentação das estratégias de busca empregadas na constituição do corpus. As análises incluem a condição de Acesso Aberto das publicações, modalidades de acesso, publicação em fontes de Acesso Aberto, registros e valores de Article Processing Charges (APC), indicadores de citação e classificações por subáreas do conhecimento. O conjunto é disponibilizado com o objetivo de favorecer a transparência, a reprodutibilidade e a reutilização dos dados da pesquisa.

    DOI: 10.5281/zenodo.22698270
  2. Dataset2026Open Access
    Data for 'Bringing public attention to disease into global health priority-setting'(opens in a new tab)

    Arroyo-Machado, Wenceslao; Ràfols, Ismael; A. Diaz-Faes, Adrian

    This dataset contains the data underlying the study Bringing public attention to disease into global health priority-setting. The study maps diseases from the Global Burden of Disease (GBD) 2023 classification across three dimensions, namely epidemiological burden, public attention and research effort, for the period 2016 to 2023. Burden is measured through disability-adjusted life years (DALYs) retrieved from the GBD 2023 release. Public attention is measured through monthly Wikipedia pageviews, restricted to human traffic, across all language editions. Research effort is measured through publications indexed in OpenAlex under the corresponding MeSH descriptors as a major topic. The deposit includes the manual mapping that links each GBD cause to MeSH descriptors and Wikipedia articles, the raw indicator files retrieved from each source, and the aggregated datasets used in the analysis. All processing scripts are available at https://github.com/Wences91/gbd_misalignment. Contents matching_2023.xlsx The core mapping of the study, produced manually and validated against external sources. The sheet Classification holds the four-level GBD 2023 hierarchy of 333 causes, after excluding injury-related causes. The sheet Mapping links each cause to its MeSH descriptors, with qualifiers where applicable, and to its primary Wikipedia article. In total, 236 specific diseases are matched, of which 129 belong to level 3 and 107 to level 4. Raw_data.zip Source data retrieved from each of the three dimensions, together with the lookup tables derived from the mapping. gbd_all_dalys_1423.csv - Global DALYs by cause and year. gbd_all_dalys_countries_1623_1.csv and gbd_all_dalys_countries_1623_2.csv - DALYs by cause, country and year, for the 25 countries where the selected Wikipedia languages hold official or national status. mesh_papers.csv and mesh_papers_with_q.csv - Publications indexed under each MeSH descriptor as a major topic, without and with qualifiers, extracted from OpenAlex. openalex_countries.csv - Country of the first author affiliation for each publication. wiki_pageviews_user.tsv - Monthly pageviews by Wikipedia article and language edition. level_3_MESH.tsv and level_3_Wikipedia.tsv - Lookup tables linking each specific disease to its MeSH descriptors and to its Wikipedia article. Aggregated_data.zip Analytical datasets built from the files above. Each record reports publication counts, pageviews and DALYs for the period 2016 to 2023. results_final_lv2.tsv - The 19 GBD level-2 disease groups. results_final_lv3.tsv - The 158 GBD level-3 diseases, of which 138 have complete data across the three dimensions. results_final_lv2_year.tsv - Level-2 disease groups broken down by publication year. results_final_lv2_country.tsv and results_final_lv3_country.tsv - Levels 2 and 3 disaggregated by language edition. Fourteen editions are included, of which German, Persian, Swahili and Vietnamese are analysed in the article.

    DOI: 10.5281/zenodo.21694438Public healthGlobal healthBurden of diseaseRaw dataHierarchy
  4. Dataset2026Open Access
    A Hierarchical IPC-Based Search System for Patents in the Brazilian IP Office (IPC Scheme)(opens in a new tab)

    Lorensi do Canto, Fábio; Carneiro, Renan; Dias, Thiago; Talau, Marcos; Segundo, Washington

    This dataset provides a structured JSON representation of the International Patent Classification (IPC) scheme used in the prototype described in the associated paper. The dataset encodes the hierarchical organization of IPC symbols, supporting navigation across classification levels and the construction of Boolean search strategies for exact and hierarchical patent retrieval. The JSON structure was prepared to support a web-based patent search prototype that enables bilingual IPC navigation in English and Portuguese and assists users in formulating IPC-based queries for execution in the beta version of the new patent search system of the Brazilian Industrial Property Office (INPI). By making the IPC scheme available as a reusable dataset, this deposit supports transparency, reproducibility, and reuse of the classification structure employed in the study. This dataset is intended as a research component associated with the paper and may be used for studies or systems involving patent information retrieval, IPC-based query expansion, hierarchical classification browsing, and the development of search interfaces based on patent classification schemes.

    DOI: 10.5281/zenodo.21044428JSONReuse