Big Data Measurement

  1. Ayankoya, K.; Calitz, A.; Greyling, J.: Intrinsic Relations between Data Science, Big Data, Business Analytics and Datafication. SAICSIT2014, September 29 - October 01, 2014, Centurion, South Africa, pp. 192-198
  2. Berman, J.J.: Principles of Big Data - Preparing, Sharing, and Analyzing Complex Information. Elsevier Publ., Amsterdam, 2013
  3. Chen, S.; Li, W.; Li, M.; Zhang, X.; Min, Y.: Latest Progress and Infrastructure Innovations of Big Data Technology. 2014 International Conference on Cloud Computing and Big Data, CPS, 2014, pp. 8-13
  4. Cheng, X.; Hu, C.; Li, Y.; Lin, W.; Zuo, H.: Data Evolution Analysis of Virtual DataSpace for Managing the Big Data Lifecycle. 2013 IEEE 27th International Symposium on Parallel & Distributed Processing Workshops and PhD Forum, IEEE Computer Society, pp. 2054-2063
  5. Hentschel, J.; Neumann, R.; Hegelwald, H.; Dumke, R.: The Impact of asynchronous and parallel Programming on the Utilization of Server Resources; in Seufert/Ebert/Fehlmann/Pechlivanidis/Dumke: MetriKon 2015 - Praxis der Software-Messung, Shaker-Verlag, Aachen, 2015, S. 147-160
  6. Hentschel J., Schmietendorf A., and Dumke R. R.: Big Data Benefits for the Software Measurement Community. Heidrich, J.; Vogelezang, F. (Eds.): IWSM/Mensura 2016, IEEE Computer Society, CPS, pp. 108-114
  7. Hentschel J.: Bewertung der Integration von Big Data Web APIs in Unternehmens-architekturen. Schmietendorf, A.; Simon, F. (Eds.):: BSOA/BCLOUD 2016, Shaker-Verlag, Aachen, 2016
  8. Kläs M., Putz W., and Lutz T.: Quality Evaluation for Big Data: A Scalable Assessment Approach and First Evaluation Results.  Heidrich, J.; Vogelezang, F. (Eds.): IWSM/Mensura 2016, IEEE Computer Society, CPS, pp. 115-124
  9. Leung, C. K.; MacKinnon, R. K.; Jiang, F.: Reducing the Search Space for Big Data Mining for Interesting Patterns from Uncertain Data. 2014 IEEE International Congress on Big Data, IEEE Computer Society, pp. 315-322
  10. Neumann, R.; Dumke, R.; Schmietendorf, A.; Baumann, M.: Managing Semi-formal Product Data in E-Commerce Applications: A Performance Case Study of Relation vs. XML Databases. In: I. Awan; R. Osman: Performance Engineering - 27th Annual UK Performance Engineering Workshop (UKPEW 2011), July 7-8, 2011, Bradford, UK, Inprint and Design, S. 174-182, , ISBN 978-0-9559703-3-7
  11. Neumann, R. et al.: Towards Optimal Server License Balancing in a Virtual Server; in Seufert/Ebert/Fehlmann/Pechlivanidis/Dumke: MetriKon 2015 - Praxis der Software-Messung, Shaker-Verlag, Aachen, 2015, S. 161-172
  12. Neumann, R. et al.: Efficiency of Scalable Tile Rendering Based on Apache Hadoop; in Seufert/Ebert/Fehlmann/Pechlivanidis/Dumke: MetriKon 2015 - Praxis der Software-Messung, Shaker-Verlag, Aachen, 2015, S. 231-240
  13. Nimala, M. B.:WAN Optimization Tools ,Techniques and Research Issues for Cloud-based Big Data Analytics. 2014 World Congress on Computing and Communication Technologies, CPS, 2014, pp. 280-285
  14. Schmietendorf, A.; Dumke, R.: Entwicklung und Einsatz von Big Data Applikationen: eine kritische Betrachtung der einhergehenden Aufwände. In: Büren et al.: Praxis der Software-Messung, Shaker-Verlag, Aachen, 2014, S. 195-204
  15. Schmietendorf, A.: Wie kann die Software-Messung von den Möglichkeiten einer Big Data Lösung profitieren? in Seufert/Ebert/Fehlmann/ Pechlivanidis/Dumke: MetriKon 2015 - Praxis der Software-Messung, Shaker-Verlag, Aachen, 2015, S. 253-262
  16. Vogel, K. M.: Big Data and the Invisible, Social Dimensions of Science. 1st Workshop on Human-Centered Big Data Research April 1-3, 2014, Raleigh, NC, USA, pp. 1-3
  17. Zeng, D.: Crystal Balls, Statistics, Big Data, and Psychohistory: Predictive Analytics and Beyond. IEEE Intelligent Systems, 2015, pp. 2-4
  18. Zhang, J.; Huang, M. L.; Wang, W. B.; Lu, L. F.; Meng, Z.: Big Data Density Analytics using Parallel Coordinate Visualization. 2014 IEEE 17th International Conference on Computational Science and Engineering, IEEE Computer Society, 2014, pp. 1115-1120
  19. Zheng, Z.; Zhu, J.; Lyu, M. R.: Service-generated Big Data and Big Data-as-a-Service: An Overview. 2013 IEEE International Congress on Big Data, IEEE Computer Society, pp. 403-410