q2014 – special session big data vienna, 4 june 2014 quality approaches to big data peter struijs...
TRANSCRIPT
![Page 1: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/1.jpg)
Q2014 – Special Session Big Data Vienna, 4 June 2014
Quality Approaches to Big DataPeter Struijs and Piet Daas
![Page 2: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/2.jpg)
2
Limitations of the established quality frameworks and methodology
Options
What to doin the changing context of making statistics
![Page 3: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/3.jpg)
Approaches and data sources
Surveys / questionnaires
e.g. sampling theory
Administrative data sources
Where does Big Data fit in? 3
![Page 4: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/4.jpg)
Two levels of quality
Quality as related to methodology
General quality criteria as defined in Code of Practice:
‐ Relevance‐ Accuracy and reliability‐ Timeliness and punctuality‐ Coherence and comparability‐ Accessibility and clarity
4
![Page 5: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/5.jpg)
5
Limitations of the established quality frameworks and methodology
![Page 6: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/6.jpg)
Small, medium-sized & large vehicles
22
![Page 7: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/7.jpg)
7
Figure 1. Development of daily, weekly and monthly aggregates of social media sentiment from June 2010 until November 2013, in green, red and black, respectively. In the insert the development of consumer confidence is shown for the identical period.
![Page 8: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/8.jpg)
Daytime population based on mobile phone data
![Page 9: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/9.jpg)
The top three issues
9
Population not known
Unbalanced
coverage
Relevance of data not
clear
![Page 10: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/10.jpg)
10
Options
![Page 11: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/11.jpg)
Population not known
11
Derive background information
Relate population at meso- or macro-level to other information
![Page 12: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/12.jpg)
Unbalanced coverage
12
Use modeling approaches
![Page 13: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/13.jpg)
Relevance of data not clear
13
Calibration / fitting
Study correlations
Use Big Data for “stand alone”
information
![Page 14: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/14.jpg)
14
What to doin the changing context of making statistics
![Page 15: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/15.jpg)
15
![Page 16: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/16.jpg)
Strategic aspects
Others start producing statistics• there may be quality issues• but they are extremely rapid• and there is obviously demand
Need for good, impartial informationwill remain• without a monopoly for NSIs
NSIs must validate information produced by others
16
![Page 17: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/17.jpg)
The way forward
Get to know Big Data
Use Big Data for efficiency and response burden reduction
Use Big Data for early indicators
Start with Big Data, not with the desired outcome
Create the right environment
17
![Page 18: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/18.jpg)
18
![Page 19: Q2014 – Special Session Big Data Vienna, 4 June 2014 Quality Approaches to Big Data Peter Struijs and Piet Daas](https://reader036.vdocuments.us/reader036/viewer/2022062517/56649ebb5503460f94bc2deb/html5/thumbnails/19.jpg)
19