Search results

  • Full text

  • Document type

    • Publication year

  • Organisation

Results: 32
Number of items: 32
  • Open Access
    López-Oramas, A., Kantzas, D., Markoff, S., & The CTA consortium (2022). Prospects for Galactic transient sources detection with the Cherenkov Telescope Array. Proceedings of Science, 395, Article 784. https://doi.org/10.48550/arXiv.2108.03911, https://doi.org/10.22323/1.395.0784
  • Open Access
    Martin, P., Liao, X., Magagna, B., Stocker, M., & Zhao, Z. (2020). Semantic and Knowledge Engineering Using ENVRI RM. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 100-119). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_6
  • Open Access
    Magagna, B., Martin, P., Nieva de la Hidalga, A., Atkinson, M., & Zhao, Z. (2020). Common Challenges and Requirements. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 30-57). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_3
  • Open Access
    Quimbert, E., Jeffery, K., Martens, C., Martin, P., & Zhao, Z. (2020). Data Cataloguing. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 140-161). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_8
  • Open Access
    Magagna, B., Goldfarb, D., Martin, P., Atkinson, M., Koulouzis, S., & Zhao, Z. (2020). Data Provenance. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 208-225). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_12
  • Open Access
    Koulouzis, S., Martin, P., Zhou, H., Hu, Y., Wang, J., Carval, T., Grenier, B., Heikkinen, J., de Laat, C., & Zhao, Z. (2020). Time-critical data management in clouds: challenges and a Dynamic Real-time Infrastructure Planner (DRIP) solution. Concurrency and Computation: Practice and Experience, 32(16), Article e5269. https://doi.org/10.1002/cpe.5269
  • Open Access
    Nieva de la Hidalga, A., Hardisty, A., Martin, P., Magagna, B., & Zhao, Z. (2020). The ENVRI Reference Model. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 61-81). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_4
  • Open Access
    Martin, P., Magagna, B., Liao, X., & Zhao, Z. (2020). Semantic Linking of Research Infrastructure Metadata. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 226-246). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_13
  • Open Access
    Koulouzis, S., Martin, P., & Zhao, Z. (2020). Virtual Infrastructure Optimisation. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 192-207). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_11
  • Štefanič, P., Cigale, M., Jones, A. C., Knight, L., Taylor, I., Istrate, C., Suciu, G., Ulisses, A., Stankovski, V., Taherizadeh, S., Flores Salado, G., Koulouzis, S., Martin, P., & Zhao, Z. (2019). SWITCH workbench: A novel approach for the development and deployment of time-critical microservice-based cloud-native applications. Future Generation Computer Systems, 99, 197-212. https://doi.org/10.1016/j.future.2019.04.008
Page 1 of 4