Jacek Cała

417 total citations
27 papers, 276 citations indexed

About

Jacek Cała is a scholar working on Information Systems and Management, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Jacek Cała has authored 27 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Information Systems and Management, 19 papers in Computer Networks and Communications and 17 papers in Information Systems. Recurrent topics in Jacek Cała's work include Scientific Computing and Data Management (22 papers), Distributed and Parallel Computing Systems (18 papers) and Research Data Management Practices (11 papers). Jacek Cała is often cited by papers focused on Scientific Computing and Data Management (22 papers), Distributed and Parallel Computing Systems (18 papers) and Research Data Management Practices (11 papers). Jacek Cała collaborates with scholars based in United Kingdom, Iraq and Spain. Jacek Cała's co-authors include Paul Watson, Zhenyu Wen, Simon Woodman, Hugo Hiden, Alexander Romanovsky, Paul Watson, Paolo Missier, Yaobo Xu, Kenji Takeda and David E. Leahy and has published in prestigious journals such as IEEE Access, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences and Future Generation Computer Systems.

In The Last Decade

Jacek Cała

26 papers receiving 267 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jacek Cała United Kingdom 9 211 206 148 22 12 27 276
Amy Krause United Kingdom 5 70 0.3× 191 0.9× 126 0.9× 50 2.3× 5 0.4× 7 257
Anthony Mayer United Kingdom 6 82 0.4× 175 0.8× 92 0.6× 21 1.0× 6 0.5× 8 195
Francesc Lordan Spain 7 105 0.5× 135 0.7× 42 0.3× 14 0.6× 6 0.5× 17 168
Eun-Kyu Byun South Korea 7 278 1.3× 288 1.4× 121 0.8× 20 0.9× 13 1.1× 16 311
Tiziana Ferrari Italy 10 49 0.2× 182 0.9× 37 0.3× 15 0.7× 35 2.9× 23 223
Lee Liming United States 6 59 0.3× 216 1.0× 92 0.6× 29 1.3× 1 0.1× 11 264
Tom Sugden United States 7 66 0.3× 216 1.0× 126 0.9× 38 1.7× 2 0.2× 12 250
Mihai Codoban United States 5 270 1.3× 94 0.5× 28 0.2× 68 3.1× 3 0.3× 8 295
Alexander Papaspyrou Germany 6 120 0.6× 145 0.7× 28 0.2× 26 1.2× 10 0.8× 20 174
Claris Castillo United States 7 215 1.0× 231 1.1× 34 0.2× 21 1.0× 4 0.3× 13 265

Countries citing papers authored by Jacek Cała

Since Specialization
Citations

This map shows the geographic impact of Jacek Cała's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jacek Cała with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacek Cała more than expected).

Fields of papers citing papers by Jacek Cała

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacek Cała. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jacek Cała. The network helps show where Jacek Cała may publish in the future.

Co-authorship network of co-authors of Jacek Cała

This figure shows the co-authorship network connecting the top 25 collaborators of Jacek Cała. A scholar is included among the top collaborators of Jacek Cała based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jacek Cała. Jacek Cała is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cała, Jacek, et al.. (2024). Experience: A Comparative Analysis of Multivariate Time-Series Generative Models: A Case Study on Human Activity Data. Journal of Data and Information Quality. 16(3). 1–18. 1 indexed citations
2.
Wen, Zhenyu, et al.. (2019). Sharing and performance optimization of reproducible workflows in the cloud. Future Generation Computer Systems. 98. 487–502. 4 indexed citations
3.
Missier, Paolo & Jacek Cała. (2019). Efficient Re-Computation of Big Data Analytics Processes in the Presence of Changes: Computational Framework, Reference Architecture, and Applications. University of Birmingham Research Portal (University of Birmingham). 24–34. 1 indexed citations
4.
Cała, Jacek, et al.. (2019). Why-Diff: Exploiting Provenance to Understand Outcome Differences From Non-Identical Reproduced Workflows. IEEE Access. 7. 34973–34990. 5 indexed citations
5.
Missier, Paolo, Tanu Malik, & Jacek Cała. (2019). Report on the First International Workshop on Incremental Re-computation. ACM SIGMOD Record. 47(4). 35–38. 1 indexed citations
6.
Cała, Jacek & Paolo Missier. (2018). Selective and Recurring Re-computation of Big Data Analytics Tasks: Insights from a Genomics Case Study. Big Data Research. 13. 76–94. 3 indexed citations
7.
Cała, Jacek, et al.. (2017). Why-Diff: Explaining differences amongst similar workflow runs by exploiting scientific metadata. Research Explorer (The University of Manchester). 7525. 3031–3041. 2 indexed citations
8.
Wen, Zhenyu, Jacek Cała, Paul Watson, & Alexander Romanovsky. (2016). Cost Effective, Reliable and Secure Workflow Deployment over Federated Clouds. IEEE Transactions on Services Computing. 10(6). 929–941. 64 indexed citations
9.
Cała, Jacek, et al.. (2016). Dynamic Deployment of Scientific Workflows in the Cloud Using Container Virtualization. Newcastle University ePrints (Newcastle Univesity). 269–276. 12 indexed citations
10.
Cała, Jacek, et al.. (2016). Scalable and efficient whole-exome data processing using workflows on the cloud. Future Generation Computer Systems. 65. 153–168. 13 indexed citations
11.
Cała, Jacek, et al.. (2016). A framework for scientific workflow reproducibility in the cloud. Newcastle University ePrints (Newcastle Univesity). 81–90. 23 indexed citations
12.
Cała, Jacek, et al.. (2015). Towards Automated Workflow Deployment in the Cloud Using TOSCA. 1037–1040. 19 indexed citations
13.
Wen, Zhenyu, Jacek Cała, & Paul Watson. (2014). A Scalable Method for Partitioning Workflows with Security Requirements over Federated Clouds. Edinburgh Research Explorer. pp. 122–129. 15 indexed citations
14.
Cała, Jacek, et al.. (2014). From Scripted HPC-Based NGS Pipelines to Workflows on the Cloud. University of Birmingham Research Portal (University of Birmingham). 371. 694–700. 5 indexed citations
15.
Blanquer, Ignácio, Jacek Cała, Fabrizio Gagliardi, et al.. (2013). Supporting NGS pipelines in the cloud. EMBnet journal. 19(A). 14–14. 3 indexed citations
16.
Hiden, Hugo, Simon Woodman, Paul Watson, & Jacek Cała. (2012). Developing cloud applications using the e-Science Central platform. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 371(1983). 20120085–20120085. 64 indexed citations
17.
Watson, Paul, David E. Leahy, Jacek Cała, et al.. (2011). Cloud Computing for Chemical Activity Prediction. School of Computing Science Technical Report Series. 1 indexed citations
18.
Watson, Paul, Hugo Hiden, Simon Woodman, et al.. (2011). The panel of experts cloud pattern. University of Birmingham Research Portal (University of Birmingham). 23–24. 3 indexed citations
19.
Woodman, Simon, et al.. (2011). Developing Applications using the e-Science Central API. 1 indexed citations
20.
Cała, Jacek, et al.. (2007). Zagadnienia implementacji systemu bezpieczeństwa dla interaktywnych aplikacji telemedycznych. 435–448.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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