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Dr. Zhiming
Zhao home page |
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Multiscale
Networked Systems (MNS) University of
Amsterdam Email: z.zhao[at]uva.nl Tel: +31 20
5257599 Office: C.3.145 Science
park 904, 1098XH Amsterdam the Netherlands |
We
are looking for 1. Part time programmers 2. Post doctors 3. PhD students... |
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Recent activities 1. IEEE DAPPS
2022 |
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I am an assistant professor
and senior researcher at University of Amsterdam (UvA). I lead a team on “Quality Critical
Distributed Computing” in the context of Multiscale Networked Systems (MNS) research group, the
System and Networking Lab (SNE). My research
focuses on innovative programming and
control models for quality critical systems on programmable
infrastructures such as Clouds, Edges, and Software Defined Networking using
optimization, semantic linking, blockchain and artificial intelligence
technologies. I am specifically interested in big data management,
infrastructure optimization for data intensive applications, and trustworthy
service level agreement. Since 2014, I obtained more
than 3M euro funding from the EU H2020 research program to support my
research activities in UvA. I am the scientific coordinator of the
project SWITCH (Software
Workbench for interactive time critical and highly self-adaptive cloud
applications). I am the leader of the Data for Science theme
in the environmental science cluster project ENVRIPLUS and
lead the technical development work package in its follow up project ENVRI-FAIR.
I also lead the UvA effort in ARTICONF, CLARIFY, BLUECLOUD, and VRE4EIC projects.
I was involved in a number of other projects, such as the EU FP7 ENVRI project.
I also lead the Virtual Research Environment (VRE) development in the
LifeWatch Virtual Lab & Innovation Center. |
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Research: Quality Critical Applications on Programmable
Infrastructures |
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In both
scientific and industrial contexts, there are distributed application systems
which 1. have very high business value (e.g.
on-demand business collaboration platforms), or social impact (e.g. for early
warning of disasters); and 2. have very critical requirements for
Quality of Service (QoS) (e.g. tsunami emergency response time) or quality of
experience (QoE) (e.g. delivery of ultra-high definition television, or collaborative
business interactions); but 3. are very difficult to develop and
operate because of their distributed nature and the high requirements for the
runtime environment, and in particular the sophisticated optimization
mechanisms needed for developing and integrating the system components. Cloud
environments provide virtualized, elastic, controllable and quality on-demand
services for supporting complex application systems. However, developing,
deploying and executing quality-critical applications in programmable
infrastructure is still difficult and challenging due to a lack of effective
programming and control mechanisms. My research
interests have revolved around modelling, developing, controlling and
optimizing such Distributed Quality-Critical Systems.
I specifically focus on novel models for programming, executing and
optimizing such applications on programmable infrastructures,
such as Cloud- and software-defined networking technologies. My basic
approach is to use autonomous agent technologies to decompose system
complexity, to develop distributed control and optimization intelligence by
combining both application logic and infrastructure programmability, and to
investigate self-adaptable cooperative control models for Cloud-based
quality-critical systems. |
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Leader: Dr. Zhiming Zhao Researchers: ·
Dr. Uraz Odyurt, AI and cloud computing (2021-) ·
Mr. Riccardo Bianchi (M.Sc), DevOps (2020-) ·
Dr. Siamak Farshidi, Knowledge base and data set
search (2020-) ·
Dr. Spiros Koulouzis, DRIP, CONF, VRE and
use cases (2017-) Ph.D. students: ·
Yuandou Wang, Distributed data processing (2020-) ·
Na Li, Knowledge discovery (2020-) ·
HongYun Liu, Cloud resource management (2019-) ·
Zhengqiu Zhu, Incentive models in crowd applications
(2020-) ·
Ruyue Xin, Virtual Infrastructure control and
adaptation (2019-) ·
Zeshun Shi, Trustworthy Virtual infrastructure
(2018-) Visiting scholars: ·
Mr. Ning Chen, Sensor network and robustness (2021-) Former members ·
Dr. Peng Chen, Cloud infrastructure optimization
(2020-2021) ·
Dr. Xiaofeng Liao, Alignment, annotation
(2017-2020) ·
Dr. Paul Martin, Semantic information linking
(2015-2018) ·
Dr. Arie Taal, Time critical applications
(2016-2019) ·
Junchao Wang, Virtual Infrastructure planning
(2015-2020) ·
Hu Yang, Time critical application deployment
(2015-2019) [thesis] ·
Huan Zhou, Virtual infrastructure provisioning
and DevOps (2015-2019)[thesis] |
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Funding and
projects
(PI) |
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1.
EU H2020 CLARIFY
(CLoud ARtificial Intelligence For pathologY). Grant No. 860627.
H2020-MSCA-ITN-2019 call. [Newsletter
in IvI] Duration: Nov 2019-Oct 2023. 2.
EU H2020 BLUECLOUD
(Blue-Cloud: Piloting innovative services for Marine Research & the Blue
Economy).H2020-BG-2018-2020. Grant No. 862409. Duration: Nov 2019-Oct 2022. 3.
EU H2020 ARTICONF (smART socIal media eCOsytstem in
a blockchaiN Federated environment). Grant No 825134.
H2020-ICT-2018-2 call. Duration: January 2019-December 2021 [Newsletter in IvI]. 4.
EU H2020 ENVRIFAIR (ENVironmental Research
Infrastructures building Fair services Accessible for society, Innovation and
Research). Grant No 824068. H2020-INFRAEOSC-2018-2 call. Duration: January
2019-December 2022 [Newsletter in IvI]. Finished projects 1.
EU H2020 ENVRIPLUS (ENVironmental Research
Infrastructures Providing shared soLUtions for Science and
society). Leader of the Data for Science Theme. Grant No. 654182 (News letter in IvI, ENVRIPLUS, EGI). Duration: May 2015- April 2019, Project
website: www.envriplus.eu. 2.
EU H2020 VRE4EIC (A Europe-wide
interoperable Virtual Research Environment to Empower multidisciplinary
research communities and accelerate Innovation and Collaboration). Grant
number 676247. H2020-EINFRA-2015-1.
Duration October 2015- September 2018. (Newsletter in IvI) 3. EU H2020 SWITCH (Software
Workbench for Interactive, Time Critical and Highly self-adaptive cloud
applications). Grant No 643963. H2020-ICT 9-2014-1 call: Tools and methods
for software development. Duration: February 2015- January 2018. (Newsletter in IvI) (SWITCH project). Participated
projects 1.
EU FP7 ENVRI.
Task leader, task 3.4: linking data and infrastructure - Common operations of
Environmental Research Infrastructure (ENVRI). Grant number 283465. 2.
EU FP7 Geysers, Researcher Generalised Architecture for Dynamic
Infrastructure Services 3.
Gigaport/CineGrid, Researcher. Including network QoS in planning
Workflows. 4.
Dutch Virtual
Laboratory for e-Science (VL-e), 2005-2009 5.
EU FP 6 CrossGrid, 2004-2005 |
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Please feel
free contact me for
details. 1. We are looking for part time programmers. 2. Open phd/post doc positions in big
data infrastructures and applications. 3. We welcome CSC (Chinese Scholar Council)
funded students |
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Community |
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Editorial
board 1.
Managing editor, Journal of cloud computing,
advances, systems and applications 2.
International journal of: Blockchains:
research and applications 3.
Journal of Circuits,
Systems and Computers Organizer/co-organizer
1. Special session: Using heterogeneous
environmental data for system-level science, 2018, Vienna, EGU
1. in Digital
Infrastructure for research 2016, Krakow, Poland 2. in Digital Infrastructure for research 2017,
Brussels, Belgium
Summer
school 1. International summer school on data
management in environmental and earth sciences (2018
| 2019
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chair
Program
committee
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Journals 1. Shi, Z., Zhou, H., de Laat, C., Zhao, Z.: A Bayesian
game-enhanced auction model for federated cloud services using blockchain.
Future Generation Computer Systems. S0167739X22001881 (2022). https://doi.org/10.1016/j.future.2022.05.017.
2. Zhao, Z., Koulouzis, S., Bianchi, R., Farshidi, S., Shi, Z., Xin, R., Wang, Y.,
Li, N., Shi, Y., Timmermans, J., Kissling, W.D.: Notebook-as-a-VRE (NaaVRE): From private
notebooks to a collaborative cloud virtual research environment. Softw Pract
Exp. spe.3098 (2022). https://doi.org/10.1002/spe.3098. 3.
Wang, Y., Koulouzis, S., Bianchi, R., Li, N., Shi, Y., Timmermans, J.,
Kissling, W.D., Zhao, Z.: Scaling Notebooks as Re-configurable Cloud
Workflows. Data Intelligence. 4, 409–425 (2022). https://doi.org/10.1162/dint_a_00140. 4.
Wittenburg, P., Hardisty, A., Franc, Y.L., Mozaffari, A., Peer, L.,
Skvortsov, N.A., Zhao, Z., Spinuso, A.: Canonical Workflows to Make Data
FAIR. Data Intelligence. 1–20 (2022). https://doi.org/10.1162/dint_a_00132 5.
Jiang, W., Pan, S., Lu, C., Zhao, Z., Lin, S., Xiong, M., He,
Z.: Label entropy-based cooperative particle swarm optimization algorithm for
dynamic overlapping community detection in complex networks. Int J Intell
Syst. int.22673 (2021). https://doi.org/10.1002/int.22673. 6.
Farshidi, S., Liao, X., Li, N., Goldfarb, D., Magagna, B., Stocker,
M., Jeffery, K., Thijsse, P., Pichot, C., Petzold, A., Zhao, Z.:
Knowledge sharing and discovery across heterogeneous research
infrastructures. Open Res Europe. 1, 68 (2021). https://doi.org/10.12688/openreseurope.13677.1.
7.
Karandikar, N., Abhishek, R., Saurabh, N., Zhao, Z., Lercher,
A., Marina, N., Prodan, R., Rong, C., Chakravorty, A.: Blockchain-based
prosumer incentivization for peak mitigation through temporal aggregation and
contextual clustering. Blockchain: Research and Applications. 2, 100016
(2021). https://doi.org/10.1016/j.bcra.2021.100016 8.
Saurabh, N., Rubia, C., Palanisamy, A., Koulouzis, S., Sefidanoski,
M., Chakravorty, A., Zhao, Z., Karadimce, A., Prodan, R.: The ARTICONF
Approach to Decentralized Car-Sharing. Blockchain: Research and Applications.
100013 (2021). https://doi.org/10.1016/j.bcra.2021.100013.
9.
Zhou, H., Shi, Z., Ouyang, X. Zhao, Z., Building a blockchain-based
decentralized ecosystem for cloud and edge computing: an ALLSTAR approach and
empirical study. Peer-to-Peer Network Application. (2021). https://doi.org/10.1007/s12083-021-01198-z
[OA] 10. Calyam, P., Wilkins‐Diehr,
N., Miller, M., Brookes, E.H., Arora, R., Chourasia, A., Jennewein, D.M.,
Nandigam, V., Drew LaMar, M., Cleveland, S.B., Newman, G., Wang, S.,
Zaslavsky, I., Cianfrocco, M.A., Ellett, K., Tarboton, D., Jeffery, K.G., Zhao,
Z., González - Aranda, J., Perri, M.J., Tucker, G., Candela, L., Kiss,
T., Gesing, S.: Measuring success for a future vision: Defining impact in
science gateways/virtual research environments. Concurrency Computat Pract
Exper. cpe.6099 (2020). https://doi.org/10.1002/cpe.6099. 11. Zhu, Z., Chen, B., Liu, W.,
Zhao, Y., Liu, Z., and Zhao Z., A
Cost-Quality Beneficial Cell Selection Approach for Sparse Mobile
Crowdsensing With Diverse Sensing Costs, in IEEE Internet of Things
Journal, vol. 8, no. 5, pp. 3831-3850, 1 March1, 2021, https://doi.org/10.1109/JIOT.2020.3024833.[OA]. 12. Zhang, L., Jiang, W., Zhao,
Z.: Short -text feature expansion and classification based on nonnegative
matrix factorization. Int Journal of Intelligent Systems. int.22290 (2020)https://doi.org/10.1002/int.22290[OA]. 13. Uriarte, R.B., Zhou, H., Kritikos, K.,
Shi, Z., Zhao, Z., De Nicola, R.:
Distributed service- level agreement management with smart
contracts and blockchain. Concurrency Computat Pract Exper. (2020). https://doi.org/10.1002/cpe.5800. 14. Hu, Y., de Laat, C., Zhao, Z.: Optimizing Service
Placement for Microservice Architecture in Clouds. Applied Sciences. 9, 4663
(2019). https://doi.org/10.3390/app9214663. 15. Hu, Y., Zhou, H., de Laat,
C., Zhao, Z.: Concurrent container
scheduling on heterogeneous clusters with multi-resource constraints. Future
Generation Computer Systems. 102, 562–573 (2020). https://doi.org/10.1016/j.future.2019.08.025. 16. Remy, L., Ivanovic, D.,
Theodoridou, M., Kritsotaki, A., Martin, P., Bailo, D., Sbarra, M., Zhao, Z., Jeffery, K.: Building an
Integrated Enhanced Virtual Research Environment Metadata Catalogue. The
Electronic Library. (2019) https://doi.org/10.1108/EL-09-2018-0183
[OA]. 17. Zhou, H., Hu, Y., Ouyang,
X., Su, J., Koulouzis, S., Laat, C., Zhao,
Z.: CloudsStorm: A framework for seamlessly programming and controlling
virtual infrastructure functions during the DevOps lifecycle of cloud
applications. Softw: Pract Exper. 49, 1421–1447 (2019). https://doi.org/10.1002/spe.2741. 18. Tanhua, T., Pouliquen, S.,
Hausman, J., O’Brien, K., Bricher, P., de Bruin, T., Buck, J.J.H., Burger,
E.F., Carval, T., Casey, K.S., Diggs, S., Giorgetti, A., Glaves, H.,
Harscoat, V., Kinkade, D., Muelbert, J.H., Novellino, A., Pfeil, B.,
Pulsifer, P.L., Van de Putte, A., Robinson, E., Schaap, D., Smirnov, A.,
Smith, N., Snowden, D., Spears, T., Stall, S., Tacoma, M., Thijsse, P.,
Tronstad, S., Vandenberghe, T., Wengren, M., Wyborn, L., Zhao, Z.: Ocean FAIR Data Services. Front. Mar. Sci. 6, 440
(2019). https://doi.org/10.3389/fmars.2019.00440. 19. Martin, P., Remy, L.,
Theodoridou, M., Jeffery, K., Zhao,
Z.: Mapping heterogeneous research infrastructure metadata into a unified
catalogue for use in a generic virtual research environment. Future
Generation Computer Systems. 101, 1–13 (2019). https://doi.org/10.1016/j.future.2019.05.076.
[OA] 20. Zhou, H., Ouyang, X., Su,
J., Laat, C., Zhao, Z.: Enforcing
trustworthy cloud SLA with witnesses: A game theory–based model using smart
contracts. Concurrency Computat Pract Exper. (2019). https://doi.org/10.1002/cpe.5511. 21. Taal, A., Wang, J., de
Laat, C., Zhao, Z.: Profiling the
scheduling decisions for handling critical paths in deadline-constrained
cloud workflows. Future Generation Computer Systems. 100, 237–249 (2019). https://doi.org/10.1016/j.future.2019.05.002. 22. Štefanič, P., Cigale, M.,
Jones, A.C., Knight, L., Taylor, I., Istrate, C., Suciu, G., Ulisses, A.,
Stankovski, V., Taherizadeh, S., Salado, G.F., Koulouzis, S., Martin, P., Zhao, Z.: 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 (2019). https://doi.org/10.1016/j.future.2019.04.008. 23. Liao, X., Zhao, Z.: Unsupervised Approaches for
Textual Semantic Annotation, A Survey. ACM Comput. Surv. 52, 1–45 (2019). https://doi.org/10.1145/3324473. 24. Liao, X., Bottelier, J., Zhao, Z.: A Column Styled Composable
Schema Matcher for Semantic Data-Types. Data Science Journal. 18-25 (2019). https://doi.org/10.5334/dsj-2019-025. 25. Koulouzis, S., Martin, P.,
Zhou, H., Hu, Y., Wang, J., Carval, T., Grenier, B., Heikkinen, J., Laat, C.,
Zhao, Z.: Time-critical data
management in clouds: Challenges and a Dynamic Real-Time Infrastructure
Planner (DRIP) solution. Concurrency Computat Pract Exper. e5269 (2019). https://doi.org/10.1002/cpe.5269. 26. Taherizadeh, S., Jones,
A.C., Taylor, I., Zhao, Z.,
Stankovski, V.: Monitoring self-adaptive applications within edge computing
frameworks: A state-of-the-art review. Journal of Systems and Software. 136,
19–38 (2018). https://doi.org/10.1016/j.jss.2017.10.033. 27. Li, J., Yang, Y., Wang, X.,
Zhao, Z., Li, T.: A novel parallel
distance metric-based approach for diversified ranking on large graphs.
Future Generation Computer Systems. 88, 79–91 (2018). https://doi.org/10.1016/j.future.2018.05.031. 28. Jiang, W., Zhai, Y.,
Zhuang, Z., Martin, P., Zhao, Z.,
Liu, J.-B.: Vertex Labeling and Routing for Farey-Type
Symmetrically-Structured Graphs. Symmetry. 10, 407 (2018). https://doi.org/10.3390/sym10090407. 29. Jiang, W., Zhai, Y.,
Zhuang, Z., Martin, P., Zhao, Z.,
Liu, J.-B.: An Efficient Method of Generating Deterministic Small-World and
Scale-Free Graphs for Simulating Real-World Networks. IEEE Access. 6,
59833–59842 (2018). https://doi.org/10.1109/ACCESS.2018.2875928. 30. Jiang, W., Zhai, Y.,
Martin, P., Zhao, Z.: Structure
Properties of Generalized Farey graphs based on Dynamical Systems for
Networks. Sci Rep. 8, 12194 (2018). https://doi.org/10.1038/s41598-018-30712-2. 31. Wang, J., Taal, A., Martin,
P., Hu, Y., Zhou, H., Pang, J., de Laat, C., Zhao, Z.: Planning virtual infrastructures for time critical
applications with multiple deadline constraints. Future Generation Computer
Systems. 75, 365–375 (2017). https://doi.org/10.1016/j.future.2017.02.001,
[Zenodo]. 32. Koulouzis, S., Belloum,
A.S.Z., Bubak, M.T., Zhao, Z.,
Živković, M., de Laat, C.T.A.M.: SDN-aware federation of distributed data.
Future Generation Computer Systems. 56, 64–76 (2016). https://doi.org/10.1016/j.future.2015.09.032. 33. Zhu, H., van der Veldt, K.,
Zhao, Z., Grosso, P., Pavlov, D.,
Soeurt, J., Liao, X., de Laat, C.: A semantic enhanced Power Budget
Calculator for distributed computing using IEEE 802.3az. Cluster Comput. 18,
61–77 (2015). https://doi.org/10.1007/s10586-014-0395-7. 34. Ghijsen, M., van der Ham,
J., Grosso, P., Dumitru, C., Zhu, H., Zhao,
Z., de Laat, C.: A semantic-web approach for modeling computing
infrastructures. Computers & Electrical Engineering. 39, 2553–2565
(2013). https://doi.org/10.1016/j.compeleceng.2013.08.011. 35. Zhao, Z., Grosso, P., van der Ham, J., Koning, R., de Laat, C.: An agent based
network resource planner for workflow applications. MGS. 7, 187–202 (2011). https://doi.org/10.3233/MGS-2011-0180. 36. Belloum, A., Inda, M.A.,
Vasunin, D., Korkhov, V., Zhao, Z.,
Rauwerda, H., Breit, T.M., Bubak, M., Hertzberger, L.O.: Collaborative
e-Science Experiments and Scientific Workflows. IEEE Internet Comput. 15,
39–47 (2011). https://doi.org/10.1109/MIC.2011.87. 37. Zhao, Z., van Albada, D., Sloot, P.: Agent-Based Flow Control for HLA
Components. SIMULATION. 81, 487–501 (2005). https://doi.org/10.1177/0037549705058060. 38. Kommers, P. and Zhao, Z.: Conceptual
Support with Virtual Reality in Web-based Learning, International Journal
of Continuing Engineering Education and Life-Long Learning, vol. 8, nr 1
1998. ISSN 0957-4344 (1998). https://www.inderscienceonline.com/doi/abs/10.1504/IJCEELL.1998.030134. Editorial
(special issues and proceedings) 39. Wittenburg, P., Hardisty, A., Mozzafari,
A., Peer, L., Skvortsov, N., Spinuso, A., Zhao, Z.: Editors’ Note:
Special Issue on Canonical Workflow Frameworks for Research. Data
Intelligence. 4, 149–154 (2022). https://doi.org/10.1162/dint_e_00122. 40. Rong, C., Zhao, Z.: Welcome to the
new Journal of Cloud Computing by Springer. J Cloud Comp. 10, 49,
s13677-021-00263–5 (2021). https://doi.org/10.1186/s13677-021-00263-5.
41. Zhao, Z., Taylor, I., Prodan, R.: Editorial for
FGCS Special issue on “Time-critical Applications on Software-defined Infrastructures.”
Future Generation Computer Systems. 112, 1170–1171 (2020). https://doi.org/10.1016/j.future.2020.07.056.[OA] [Content] 42. Zhao, Z., Altmeyer, S., Keith J., Atkinson,
M. and Ulisses A.: Nearly
real time data processing and time critical cloud applications. Proceedings
of the 2nd International workshop
on Interoperable infrastructures for interdisciplinary big data sciences
(IT4RIs 16), in the context of IEEE Real-time System Symposium (RTSS), Porto,
Portugal, November 29-December 2, (2016). [doi:10.5281/zenodo.204685] 43. Lu, S., Deelman, E. & Zhao,
Z.: Scientific workflows
special issue. International journal of business process integration
and management (pp. 1-2). Inder science Enterprises Ltd. (2010). [Full text] 44. Zhao, Z., Belloum, A.,
Bubak, M.: Special section on workflow systems and applications in e-Science.
Future Generation Computer Systems. 25, 525–527 (2009). https://doi.org/10.1016/j.future.2008.10.011. 45. Belloum, A., Deelman, E. & Zhao,
Z.: Scientific workflows.
Scientific Programming, 14(3-4), 171-171 (2006). [Full text] Book
(Eds) 46. Zhao, Z., Hellström, M.
eds: Towards Interoperable Research Infrastructures for Environmental and
Earth Sciences: A Reference Model Guided Approach for Common Challenges.
Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4.
[ENVRI archive][Book interview] Book
chapters 47.
Jeffery, K., Pursula, A., Zhao, Z.: ICT Infrastructures for
Environmental and Earth Sciences. In: Zhao,
Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 17–29. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_2. 48.
Magagna, B., Martin, P., de la Hidalga,
A.N., Atkinson, M., Zhao, Z.:
Common Challenges and Requirements. In: Zhao,
Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 30–57. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_3. 49.
de la Hidalga, A.N., Hardisty, A.,
Martin, P., Magagna, B., Zhao, Z.:
The ENVRI Reference Model. In: Zhao,
Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 61–81. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_4. 50.
Zhao, Z., Jeffery, K.: Reference
Model Guided Engineering. In: Zhao, Z. and Hellström, M. (eds.) Towards
Interoperable Research Infrastructures for Environmental and Earth Sciences.
pp. 82–99. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_5. 51.
Martin, P., Liao, X., Magagna, B.,
Stocker, M., Zhao, Z.: Semantic
and Knowledge Engineering Using ENVRI RM. In: Zhao, Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 100–119. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_6. 52.
Quimbert, E., Jeffery, K., Martens, C.,
Martin, P., Zhao, Z.: Data
Cataloguing. In: Zhao, Z. and
Hellström, M. (eds.) Towards Interoperable Research Infrastructures for
Environmental and Earth Sciences. pp. 140–161. Springer International
Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_8. 53.
Koulouzis, S., Martin, P., Zhao, Z.: Virtual Infrastructure
Optimisation. In: Zhao, Z. and
Hellström, M. (eds.) Towards Interoperable Research Infrastructures for
Environmental and Earth Sciences. pp. 192–207. Springer International
Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_11. 54.
Magagna, B., Goldfarb, D., Martin, P.,
Atkinson, M., Koulouzis, S., Zhao, Z.:
Data Provenance. In: Zhao, Z. and
Hellström, M. (eds.) Towards Interoperable Research Infrastructures for
Environmental and Earth Sciences. pp. 208–225. Springer International
Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_12. 55.
Martin, P., Magagna, B., Liao, X., Zhao, Z.: Semantic Linking of
Research Infrastructure Metadata. In: Zhao,
Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 226–246. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_13. 56.
Koulouzis, S., Carval, T., Heikkinen, J.,
Pursula, A., Zhao, Z.: Case Study:
Data Subscriptions Using Elastic Cloud Services. In: Zhao, Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 293–306. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_16. 57.
Zhao,
Z., Jeffery, K., Stocker, M., Atkinson, M., Petzold,
A.: Towards Operational Research Infrastructures with FAIR Data and Services.
In: Zhao, Z. and Hellström, M.
(eds.) Towards Interoperable Research Infrastructures for Environmental and
Earth Sciences. pp. 360–372. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_20. 58. Martin, P., Chen, Y. Hardisty, A.,
Jeffery, K., and Zhao, Z.: Computational Challenges in Global
Environmental Research Infrastructures. in the book of
Terrestrial Ecosystem Research Infrastructures: Challenges, New developments
and Perspectives (2017). [ISBN 9781498751315] [OA]. 59. Zhao, Z., Grosso, P., Ham, J. van
der, Koning, R. & de Laat, C.:
Quality guaranteed media
delivery over advanced network. Chapter in book Next Generation
Content Delivery Infrastructure: Emerging Paradigms and Technologies, IGI,
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Service Control Framework for Decentralized Applications in Cloud
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Z.: DWH-DIM: A Blockchain Based Decentralized Integrity Verification
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[OA] 64. Poon, L., Farshidi, S., Li, N., Zhao,
Z.: Unsupervised Anomaly Detection in Data Quality Control. In: 2021 IEEE
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[OA] 65. Liu H., Chen P., Zhao, Z.,:
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[OA](Best student paper) 66. Shi Ze., Farshidi S., Zhou H., Zhao
Z., An Auction and Witness Enhanced Trustworthy SLA Model for Decentralized Cloud Marketplaces, The
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Z.: CBProf: Customisable Blockchain-as-a-service Performance Profiler in
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van der Linde, Yuandou Wang and Zhiming Zhao, SPIRIT: A
microservice-based framework for interactive Cloud infrastructure planning,
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Bianchi R., Zhao, Z.: FAIR-Cells: an interactive tool for enabling the
FAIRness of code fragments in Jupyter notebooks, in the proceedings of
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Zhao, Z., Rong, C.,
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on Parallel and Distributed Systems (ICPADS). pp. 617–624. IEEE, Hong Kong
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[OA]. 73. Zhou, H., Ouyang, X., Zhao, Z.: ALLSTAR: A Blockchain Based
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Automated Customization and Performance Profiling Framework for Permissioned
Blockchains in a Virtualized Environment. In: 2019 IEEE International
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[OA]. 75. Petzold, A., Asmi, A., Vermeulen, A.,
Pappalardo, G., Bailo, D., Schaap, D., Glaves, H.M., Bundke, U., Zhao, Z.: ENVRI-FAIR - Interoperable
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Ulisses, A.: ARTICONF: Towards a Smart Social Media Ecosystem in a Blockchain
Federated Environment, in the 7th Workshop on Large Scale Distributed Virtual
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Rubia, C., and Zhao, Z.:
Co-located and Orchestrated Network Fabric (CONF): An Automated Cloud Virtual
Infrastructure for Social Network Applications. in the 7th Workshop on Large
Scale Distributed Virtual Environments, in the context of Euro-Par conference
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[OA] Best presentation in the session. 86. Shi, Z., Zhou, H., Hu, Y., Jayachander,
S., de Laat, C., Zhao, Z.: Operating
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Sawtooth. In: 2019 18th International Symposium on Parallel and Distributed
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and Grid Computing (CCGRID). pp. 592–599. IEEE, Larnaca, Cyprus (2019). https://doi.org/10.1109/CCGRID.2019.00076,
[OA] Best paper award. 88. Zhou, H., Koulouzis, S., Hu, Y., Wang,
J., de Laat, C., Ulisses, A., Zhao,
Z.: Migrating Live Streaming Applications onto Clouds: Challenges and a
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Taipei, Taiwan (2012). https://doi.org/10.1109/CloudCom.2012.6427494. 133.
Zhao, Z., Taal, A., Grosso, P., de Laat, C.: Resource
Discovery in Large Scale Network Infrastructure. In: 2011 IEEE Sixth
International Conference on Networking, Architecture, and Storage. pp.
186–190. IEEE, Dalian, China (2011). https://doi.org/10.1109/NAS.2011.43. 134.
Zhao, Z., Grosso, P., Koning, R., van der Ham, J.,
de Laat, C.: An agent based planner for including network QoS in scientific
workflows. In: Proceedings of the International Multiconference on Computer
Science and Information Technology. pp. 231–238. IEEE, Wisla (2010). https://doi.org/10.1109/IMCSIT.2010.5680060,
Best paper award. 135.
Zhao, Z., Grosso, P., Koning, R., van der Ham, J.,
de Laat, C.: Network resource selection for data transfer processes in
scientific workflows. In: The 5th Workshop on Workflows in Support of
Large-Scale Science. pp. 1–6. IEEE, New Orleans, LA, USA (2010). https://doi.org/10.1109/WORKS.2010.5671840. 136.
Zhao, Z., Grosso, P., Koning, R., Ham, J., de
Laat, C.: An Architecture Including Network QoS in Scientific Workflows. In:
2010 Ninth International Conference on Grid and Cloud Computing. pp. 104–109.
IEEE, Nanjing, China (2010). https://doi.org/10.1109/GCC.2010.32. 137.
Zhao, Z., Belloum, A., Bubak, M., Hertzberger, B.:
Support for Cooperative Experiments in VL-e: From Scientific Workflows to
Knowledge Sharing. In: 2008 IEEE Fourth International Conference on eScience.
pp. 329–330. IEEE, Indianapolis, IN, USA (2008). https://doi.org/10.1109/eScience.2008.120. 138.
Wibisono, A., Zhao,
Z., Belloum, A., Bubak, M.: A Framework for Interactive Parameter Sweep
Applications. In: Bubak, M., van Albada, G.D., Dongarra, J., and Sloot,
P.M.A. (eds.) Computational Science – ICCS 2008. pp. 481–490. Springer Berlin
Heidelberg, Berlin, Heidelberg (2008). https://doi.org/10.1007/978-3-540-69389-5_55. 139.
Wibisono, A., Zhao,
Z., Belloum, A., Bubak, M.: A Framework for Interactive Parameter Sweep
Applications. In: 2008 Eighth IEEE International Symposium on Cluster Computing
and the Grid (CCGRID). pp. 703–703. IEEE, Lyon, France (2008). https://doi.org/10.1109/CCGRID.2008.111. 140.
Belloum, A., Zhao,
Z., Bubak, M.: International Workshop on Applications of Workflows in
Computational Science (AWCS 08). In: Bubak, M., van Albada, G.D., Dongarra,
J., and Sloot, P.M.A. (eds.) Computational Science – ICCS 2008. pp. 459–462.
Springer Berlin Heidelberg, Berlin, Heidelberg (2008). https://doi.org/10.1007/978-3-540-69389-5_52. 141.
Zhao, Z., Belloum, A., De Laat, C., Adriaans, P.,
Hertzberger, B.: Using Jade agent framework to prototype an e-Science
workflow bus. In: Seventh IEEE International Symposium on Cluster Computing
and the Grid (CCGrid ’07). pp. 655–660. IEEE, Rio de Janeiro, Brazil (2007). https://doi.org/10.1109/CCGRID.2007.120. 142.
Zhao, Z., Belloum, A., de Laat, C., Adriaans, P.,
Hertzberger, B.: Distributed execution of aggregated multi domain workflows
using an agent framework. In: 2007 IEEE Congress on Services (Services 2007).
pp. 183–190. IEEE, Salt Lake City, UT, USA (2007). https://doi.org/10.1109/SERVICES.2007.30. 143.
Wibisono, A., Vasyunin, D., Korkhov, V., Zhao, Z., Belloum, A., de Laat, C.,
Adriaans, P., Hertzberger, B.: WS-VLAM: A GT4 Based Workflow Management
System. In: Shi, Y., van Albada, G.D., Dongarra, J., and Sloot, P.M.A. (eds.)
Computational Science – ICCS 2007. pp. 191–198. Springer Berlin Heidelberg,
Berlin, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72588-6_34. 144.
Terpstra, F., Zhao,
Z., Mulder, W., Adriaans, P.: Towards a Formal Foundation for Aggregating
Scientific Workflows. In: Shi, Y., van Albada, G.D., Dongarra, J., and Sloot,
P.M.A. (eds.) Computational Science – ICCS 2007. pp. 216–219. Springer Berlin
Heidelberg, Berlin, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72588-6_38. 145.
Zhao, Z., Booms, S., Belloum, A., Laat, C.,
Hertzberger, B.: VLE-WFBus: A Scientific Workflow Bus for Multi e-Science
Domains. In: 2006 Second IEEE International Conference on e-Science and Grid
Computing (e-Science’06). pp. 11–11. IEEE, Amsterdam, The Netherlands (2006).
https://doi.org/10.1109/E-SCIENCE.2006.261095. 146.
Zhao, Z., van Albada, D., Sloot, P.: Rapid
Prototyping of Complex Interactive Simulation Systems. In: 10th IEEE
International Conference on Engineering of Complex Computer Systems
(ICECCS’05). pp. 366–375. IEEE, Shanghai, China (2005). https://doi.org/10.1109/ICECCS.2005.69. 147.
Zhao, Z., Belloum, A., Yakali, H., Sloot, P.,
Hertzberger, B.: Dynamic Work.ow in a Grid Enabled Problem Solving
Environment. In: The Fifth International Conference on Computer and Information
Technology (CIT’05). pp. 339–345. IEEE, Shanghai, China (2005). https://doi.org/10.1109/CIT.2005.101. 148.
Zhao, Z., Belloum, A., Wibisono, A., Terpstra, F.,
de Boer, P.T., Sloot, P., Hertzberger, B.: Scientific workflow management:
between generality and applicability. In: Fifth International Conference on
Quality Software (QSIC’05). pp. 357–364. IEEE, Melbourne, Australia (2005). https://doi.org/10.1109/QSIC.2005.56. 149.
Zhao, Z., Belloum, A., Sloot, P., Hertzberger, B.:
Agent technology and scientific workflow management in an e-science
environment. In: 17th IEEE International Conference on Tools with Artificial
Intelligence (ICTAI’05). pp. 5 pp. – 23. IEEE, Hong Kong, China (2005). https://doi.org/10.1109/ICTAI.2005.29. 150.
Zhao, Z., Belloum, A., Sloot, P., Hertzberger, B.:
Agent Technology and Generic Workflow Management in an e-Science Environment.
In: Zhuge, H. and Fox, G.C. (eds.) Grid and Cooperative Computing - GCC 2005.
pp. 480–485. Springer Berlin Heidelberg, Berlin, Heidelberg (2005). https://doi.org/10.1007/11590354_61. 151.
Zhao, Z. (2004, december 09). An
agent based architecture for constructing Interactive Simulation Systems. UvA Universiteit van Amsterdam.
Promoter/co-promoter: prof. dr. P.M.A. Sloot & dr. G.D. van Albada. [Link] 152.
Zhao, Z., van Albada, D., Sloot, P.: Agent-Based
Flow Control for HLA Components. SIMULATION. 81, 487–501 (2005). https://doi.org/10.1177/0037549705058060. 153.
Zajac, K., Tirado-Ramos, A., Zhao, Z., Sloot, P., Bubak, M.: Grid Services for HLA-Based
Distributed Simulation Frameworks. In: Fernández Rivera, F., Bubak, M., Gómez
Tato, A., and Doallo, R. (eds.) Grid Computing. pp. 147–154. Springer Berlin
Heidelberg, Berlin, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24689-3_19. 154.
Zhao, Z., van Albada, G.D., Tirado-Ramos, A.,
Zajac, K., Sloot, P.M.A.: ISS-Studio: A Prototype for a User-Friendly Tool
for Designing Interactive Experiments in Problem Solving Environments. In:
Sloot, P.M.A., Abramson, D., Bogdanov, A.V., Dongarra, J.J., Zomaya, A.Y.,
and Gorbachev, Y.E. (eds.) Computational Science — ICCS 2003. pp. 679–688.
Springer Berlin Heidelberg, Berlin, Heidelberg (2003). https://doi.org/10.1007/3-540-44860-8_70. 155.
Tirado-Ramos, A., Zajac, K., Zhao, Z., Sloot, P.M.A., van Albada, D., Bubak, M.: Experimental
Grid Access for Dynamic Discovery and Data Transfer in Distributed
Interactive Simulation Systems. In: Sloot, P.M.A., Abramson, D., Bogdanov,
A.V., Dongarra, J.J., Zomaya, A.Y., and Gorbachev, Y.E. (eds.) Computational
Science — ICCS 2003. pp. 284–292. Springer Berlin Heidelberg, Berlin,
Heidelberg (2003). https://doi.org/10.1007/3-540-44860-8_29. 156.
Zhao, Z., Belleman, R.G., van Albada, G.D., Sloot,
P.M.A.: AG-IVE: An Agent Based Solution to Constructing Interactive
Simulation Systems. In: Sloot, P.M.A., Hoekstra, A.G., Tan, C.J.K., and
Dongarra, J.J. (eds.) Computational Science — ICCS 2002. pp. 693–703.
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Zhao, Z., Belleman, R.G., Albada, G.D. van
& Sloot, P.M.A. (2002). Reusability
and Efficiency in Constructing Interactive Simulation Systems. In E.F. Deprettere,
A.S.Z. Belloum, J.W.J. Heijnsdijk & F. van
der Stappen (Eds.), ASCI 2002, Proceedings of the eighth annual
conference of the Advanced School for Computing and Imaging (pp. 268-275).
Delft: ASCI. [Link] 158.
Zhao, Z., Belleman, R.G., Albada, G.D. van
& Sloot, P.M.A. (2002). Scenario
Switches and State Updates in an Agent-based Solution to Constructing
Interactive Simulation Systems. In Proceedings of the Communication Networks
and Distributed Systems Modeling and Simulation Conference (CNDS
2002) (pp. 3-10). [Link] 159.
Zhao, Z., Belleman R.
G., Albada G.D.and Sloot P.M.A. (2001): System integration for interactive
simulation systems using intelligent agents, in
R.L. Lagendijk; J.W.J. Heijnsdijk; A.D. Pimentel and M.H.F.
Wilkinson, editors, Proceedings of the 7th annual conference of the Advanced
School for Computing and Imaging, pp. 399-406. ASCI, May 2001. ISBN
90-803086-6-8. [Link] 160.
Belleman,R.G., Zhao,Z., Albada G.D.
van and Sloot P.M.A (2000) Design considerations for the construction of immersive dynamic
exploration environments, in L.J. van Vliet;
J.W.J. Heijnsdijk; T. Kielmann and P.M.W. Knijnenburg,
editors, ASCI 2000, Proceedings of the sixth annual conference of the
Advanced School for Computing and Imaging, pp. 195-201. ASCI, Delft, June
2000. ISBN 90-803086-5-x. [Link] Peer
reviewed abstracts and posters 161.
Andreas Petzold, Ari Asmi, Rita Gomes, Katrin
Seemeyer, Angeliki Adamaki, Alexander T Vermeulen, Daniele Bailo, Keith G
Jeffery, Helen Glaves, Zhiming Zhao, Markus Stocker, Margareta
Hellström (2021) Creating ENVRI-hub, the Open-Access Platform of the
Environmental Sciences Community in Europe, AGU 162.
Alex Boyko, Siamak Farshidi, Zhiming Zhao,
State-of-the-art instance matching methods for knowledge graphs, The Sixteenth International Workshop on
Ontology Matching
(OM-2021), in the context of 20th International Semantic Web Conference
ISWC-2021, online [OA] 163.
Spiros Koulouzis, Yifang Shi, Yuandou Wan, Riccardo
Bianchi, Daniel Kissling, Zhiming Zhao (2021) Enabling LiDAR data
processing as a service in a Jupyter environment, EGU 2021 [10.5194/egusphere-egu21-8294] 164.
Andreas Petzold, Ari Asmi, Katrin Seemeyer, Angeliki
Adamaki, Alex Vermeulen, Daniele Bailo, Keith Jeffery, Helen Glaves, Zhiming
Zhao, Markus Stocker, Margareta Hellström (2021) Advancing the FAIRness
and Openness of Earth system science in Europe, EGU [10.5194/egusphere-egu21-8052] 165.
Xiaofeng Liao, Doron Goldfarb, Barbara Magagna,
Markus Stocker, Peter Thijsse, Dick Schaap, Zhiming Zhao (2020) ENVRI knowledge base: A community knowledge
base for research, innovation and society,
EGU, April 2020 [10.5194/egusphere-egu2020-20708] 166.
Zhao, Z., Martin, P.,
Koulouzis, S.: (2019)
Optimizing environmental data services on federated Cloud and
e-Infrastructures, EGU, April 2019 [2019EGUGA..21.3683Z] 167.
Koulouzis, S., Carval, T., Martin, P., Grenier, B.,
Chen, Y., Heikkinen, J., Zhao, Z.: Dynamic Optimization for
Time-critical Data Services: A Case Study in Euro-Argo Research
Infrastructure. 20th EGU General
Assembly, EGU2018, Proceedings from the conference held 4-13 April, 2018 in
Vienna, Austria, p.16012. [2018EGUGA..2016012K] 168.
Abraham Nieva de la Hidalga, Alex
R Hardisty, Barbara Magagna, Paul W Martin, Zhiming Zhao (2018)
Use of the ENVRI Reference Model to Support the Design of Environmental
Research Infrastructures, 20th EGU General Assembly, EGU2018, Proceedings
from the conference held 4-13 April, 2018 in Vienna, Austria, p.18552 [2018EGUGA..2018552N] 169.
Kutsch, W. L.; Zhao, Z.; Hardisty,
A.; Hellström, M.; Chin, Y.; Magagna, B.; Asmi,
A.; Papale, D.; Pfeil, B.; Atkinson, M. (2017)
Data interoperabilty between European Environmental Research
Infrastructures and their contribution to global data networks, AGU 2018,
American Geophysical Union, Fall Meeting 2017, abstract #IN44B-01. [2017AGUFMIN44B..01K] Technical
report and newsletters 170.
Zhao, Z., Martin, P. Jeffery K.,
(2017) VRE in the Data for Science Approach to Common Challenges in
ENVRIPLUS, ERCIM, Newsletter, April 2017 171.
Zhao, Z. (2016) Data for science: software
and solutions for the environmental sciences, EGI Newsletter, January 2016. 172.
Zhao, Z., (2015) Data for Science theme:
software and solutions to address common challenges facing environmental
research infrastructures, 1st ENVRIPLUS Newsletter, November 2015. 173.
Ghijsen, M., Ham, J. van der, Grosso,
P., Dumitru, C., Zhu, H., Zhao, Z. & Laat, C.
de (2013). A semantic-web approach
for modeling computing infrastructures. (SNE technical report 2013-01).
Amsterdam: Universiteit van Amsterdam, System and Network
Engineering. [Full text] 174.
Hertzberger, L.O., Belleman, R.G., Jansen,
M.G., Zhao, Z., Hooft, P. van, Belloum,
A.S.Z., Mirzadeh, N., Yakali, H.H., Liere, R.
van, Nuallain, B.S., Verstoep, K., Groep, D.L.
& Bouwhuis, M.C. (2005). Recommendation to VLeIT:
Scientific workflow management systems for the PoC r1. (Internal
report). Amsterdam: Informatics Institute. Supervised
PhD thesis 175.
Yang
Hu (2019) Resource Scheduling for Quality-Critical Applications on Cloud
Infrastructure, University of Amsterdam, [ISBN: 978-94-028-1713-3]. 176.
Huan
Zhou (2019) Seamless Infrastructure Programming and Control for
Quality-critical Cloud Applications, [ISBN: 978-94-028-1727-0] In
Chinese 177.
Zhao, Z., Liao, X., Wang, X.,
Ruan, C., Zhu, Y., Feng, D. (2019), An Reference Model approach for developing
agriculture big data infrastructures, Journal of East China Normal University
(Natural Sc 2019 Vol.2019 (2): 77-96, [10.3969/j.issn.1000-5641.2019.02.009] 178.
Demchenko, Y., Zhao, Z., Grosso,
P., Wibisono, A., de Laat, C., (2013) 科研信息化基础 设施的大数据挑战 (Big Data Challenges for e-Science
Infrastructure) China Science and Technology Resources Review,
Vol.45 No.1 30-35,40 Jan. 2013. ISSN 1674-1544 [10.3772/j.issn.1674-1544.2013.01.006]
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Update date: January 12, 2022