Abstract
The past couple of decades have witnessed exponential growth in data, due to the penetration of information technology across all aspects of science and society; the increasing ease with which we are able to collect more data; and the growth of Internet-scale, planet-wide Web-based and mobile services—leading to the notion of “big data”. While the emphasis so far has been on developing technologies to manage the volume, velocity, and variety of the data, and to exploit available data assets via machine learning techniques, going forward the emphasis must also be on translational data science and the responsible use of all of these data in real-world applications. Data science in the 21st century must provide trust in the data and provide responsible and trustworthy techniques and systems by supporting the notions of transparency, interpretability, and reproducibility. The future offers exciting opportunities for transdisciplinary research and convergence among disciplines—computer science, statistics, mathematics, and the full range of disciplines that impact all aspects of society. Econometrics and economics can find an important role in this convergence of ideas.
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Notes
- 1.
Data and Society, https://datasociety.net/.
- 2.
Convergence Research at NSF: https://www.nsf.gov/od/oia/convergence/index.jsp.
- 3.
- 4.
- 5.
TFoDS Workshop, http://www.cs.rpi.edu/TFoDS/.
- 6.
TFoDS Workshop Report, http://www.cs.rpi.edu/TFoDS/TFoDS_v5.pdf.
- 7.
Apache MXnet, https://aws.amazon.com/mxnet/.
- 8.
Google Tensorflow, https://www.tensorflow.org/.
- 9.
Microsoft Cognitive Toolkit, https://www.microsoft.com/en-us/cognitive-toolkit/.
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IBM Cognitive Computing, https://www.ibm.com/it-infrastructure/us-en/cognitive-computing/.
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Administration Issues Strategic Plan for Big Data Research and Development, https://obamawhitehouse.archives.gov/blog/2016/05/23/administration-issues-strategic-plan-big-data-research-and-development.
- 12.
Structured Query Language, https://www.w3schools.com/sql/sql_intro.asp.
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noSQL Databases, http://nosql-database.org/.
- 14.
Apache Hadoop, http://hadoop.apache.org/.
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Apache Spark, https://spark.apache.org/.
- 16.
Apache Storm, http://storm.apache.org/.
- 17.
Personal communication with R.V. Guha, July 2016.
- 18.
NITRD Big Data Interagency Working Group (BDIWG), https://www.nitrd.gov/nitrdgroups/index.php?title=Big_Data.
- 19.
Translational Data Science workshop, https://cdis.uchicago.edu/tds-17/.
- 20.
Translational Research, wikipedia, https://en.wikipedia.org/wiki/Translational_research.
- 21.
National Center for Advancing Translational Science, https://ncats.nih.gov/.
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Baru, C. (2018). Data in the 21st Century. In: Kreinovich, V., Sriboonchitta, S., Chakpitak, N. (eds) Predictive Econometrics and Big Data. TES 2018. Studies in Computational Intelligence, vol 753. Springer, Cham. https://doi.org/10.1007/978-3-319-70942-0_1
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