Monitorology the art of observing the world

In the age of ever increasing demand for big data and data analytics, a question of collecting the data becomes fundamental. What and how to collect the data is essential as it has direct impact on decision making, system operation and control. Specifically, we focus on the art of observing the world by electronic devices such as sensors and meters that, in general, we call monitors. We define five challenges to ensure effective and efficient monitoring that still need a lot of research. Additionally, we illustrate each challenge by example. Since reliance on big data and data analytics is continuously increasing, these challenges will become ever more relevant to save the world from flood of meaningless, dumb data, leading frequently to false conclusions and wrong decisions whose impact may range from a minor inconvenience to major disasters and even loss of lives.

[1]  Michael Stonebraker,et al.  Aurora: a new model and architecture for data stream management , 2003, The VLDB Journal.

[2]  Isabelle Guyon,et al.  An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..

[3]  Mohamed F. Younis,et al.  Strategies and techniques for node placement in wireless sensor networks: A survey , 2008, Ad Hoc Networks.

[4]  Roger Clarke,et al.  Big Data's Big Unintended Consequences , 2013, Computer.

[5]  Huan Liu,et al.  Toward integrating feature selection algorithms for classification and clustering , 2005, IEEE Transactions on Knowledge and Data Engineering.

[6]  Miroslaw Malek,et al.  A Friend or a Foe? Detecting Malware using Memory and CPU Features , 2016, SECRYPT.

[7]  Veda C. Storey,et al.  A Framework for Analysis of Data Quality Research , 1995, IEEE Trans. Knowl. Data Eng..

[8]  Kishor S. Trivedi,et al.  A Best Practice Guide to Resource Forecasting for Computing Systems , 2007, IEEE Transactions on Reliability.

[9]  Marta Indulska,et al.  20 Years of Data Quality Research: Themes, Trends and Synergies , 2011, ADC.

[10]  Qiang Chen,et al.  Aurora : a new model and architecture for data stream management ) , 2006 .

[11]  Martin H. Weik Communications standard dictionary , 1981 .

[12]  Miroslaw Malek,et al.  Call Availability Prediction in a Telecommunication System: A Data Driven Empirical Approach , 2006, 2006 25th IEEE Symposium on Reliable Distributed Systems (SRDS'06).

[13]  Miroslaw Malek,et al.  Comprehensive logfiles for autonomic systems , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[14]  Mark David Hansen Zero defect data , 1991 .

[15]  Jorge Bernardino,et al.  A Survey on Data Quality: Classifying Poor Data , 2015, 2015 IEEE 21st Pacific Rim International Symposium on Dependable Computing (PRDC).

[16]  Kamesh Munagala,et al.  Local Search Heuristics for k-Median and Facility Location Problems , 2004, SIAM J. Comput..

[17]  Andreas Krause,et al.  Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies , 2008, J. Mach. Learn. Res..

[18]  Yoshihiko Akaiwa,et al.  Signal and Systems , 2015 .