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Results: 23
Number of items: 23
  • Open Access
    Wilkinson, S. R., Aloqalaa, M., Belhajjame, K., Crusoe, M. R., de Paula Kinoshita, B., Gadelha, L., Garijo, D., Gustafsson, O. J. R., Juty, N., Kanwal, S., Khan, F. Z., Köster, J., Peters-von Gehlen, K., Pouchard, L., Rannow, R. K., Soiland-Reyes, S., Soranzo, N., Sufi, S., Sun, Z., ... Goble, C. (2025). Applying the FAIR Principles to computational workflows. Scientific Data, 12, Article 328. https://doi.org/10.1038/s41597-025-04451-9
  • Open Access
    Gustafsson, O. J. R., Wilkinson, S. R., Bacall, F., Soiland-Reyes, S., Leo, S., Pireddu, L., Owen, S., Juty, N., Fernández, J. M., Brown, T., Ménager, H., Grüning, B., Capella-Gutierrez, S., Coppens, F., & Goble, C. (2025). WorkflowHub: a registry for computational workflows. Scientific Data, 12, Article 837. https://doi.org/10.1038/s41597-025-04786-3
  • Open Access
    Soiland-Reyes, S. (2025). FAIR Research Objects and computational workflows: A Linked Data approach. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Soiland-Reyes, S., Goble, C., & Groth, P. (2024). Evaluating FAIR Digital Object and Linked Data as distributed object systems. PeerJ Computer Science, 10, Article e1781. https://doi.org/10.7717/PEERJ-CS.1781
  • Open Access
    Wittner, R., Holub, P., Mascia, C., Frexia, F., Müller, H., Plass, M., Allocca, C., Betsou, F., Burdett, T., Cancio, I., Chapman, A., Chapman, M., Courtot, M., Curcin, V., Eder, J., Elliot, M., Exter, K., Goble, C., Golebiewski, M., ... Geiger, J. (2024). Toward a common standard for data and specimen provenance in life sciences. Learning Health Systems, 8(1), Article e10365. https://doi.org/10.1002/lrh2.10365
  • Soiland-Reyes, S. (2023, June 26). Comparison tables for evaluating FAIR Digital Object and Linked Data [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8075230
  • Open Access
    David, R., Soiland-Reyes, S., BY-COVID project community, & ISIDORe project community (2023). Umbrella Data Management Plans to integrate FAIR data: Lessons from the ISIDORe and BY-COVID consortia for pandemic preparedness. (v4 ed.) Zenodo. https://doi.org/10.5281/zenodo.7516084
  • Open Access
    Meurisse, M., Estupiñán-Romero, F., González-Galindo, J., Martínez-Lizaga, N., Royo-Sierra, S., Saldner, S., Dolanski-Aghamanoukjan, L., Degelsegger-Marquez, A., Soiland-Reyes, S., Van Goethem, N., Bernal-Delgado, E., & BeYond-COVID project (2023). Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment. BMC Medical Research Methodology, 23, Article 248. https://doi.org/10.1186/s12874-023-02068-3
  • Open Access
    David, R., Soiland-Reyes, S., BY-COVID project community, & ISIDORe project community (2023). Umbrella Data Management Plans to Integrate FAIR Data: Lessons From the ISIDORe and BY-COVID Consortia for Pandemic Preparedness. Data Science Journal, 22, Article 35. https://doi.org/10.5334/dsj-2023-035
  • Open Access
    Soiland-Reyes, S., Goble, C., & Groth, P. (2023). Evaluating FAIR Digital Object and Linked Data as distributed object systems. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2306.07436
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