Key Concept/Term(Ch2: Genealogies of Data Science)
-How data scientists are being defined in relation to national statisticians-
[Define: Birth of data scientists]
The emergence of Big Data (volume/velocity/variety), driven by the availability of new data sources -GPS/Smartphone/Sensor -→Difficult to collect these emerging Big Data with the conventional system of statistical organizations
→→Need for identifying emerging “Big Data”
“The emergence of new professions involves identifying and defending an object of concern that calls upon new skills and expertise not currently being met.”
→→→Social needs to handle “Big Data” translated into skill required, and turn into what constitutes a “data scientist”.
How Big Data would practically compare to longstanding and trusted official statistics? Various/numerous demonstrations and pilot project were made.-Learn by doing-
Gain experience in using big data in the context of official statistics.
→In this era, data scientists and statisticians were not separate from the former but together were part and parcel of the struggle to understand the implication of Big Data.
[Differentiate]
| Data Scientist | National Statistician | |
| Where they rise | Emergence of new data sources e.g.GPS/Smartphone | After WWⅡ, social need for gathering global data |
| Typical Institution | Industry | Government/Academia |
| Object work with | Big Data(3V's-volume/velocity/variety-) | Public data(census/survey) |
| Competency/ Skill | Analytical Skill/techniques e.g. machine learning, algorithms,predictive modeling | Data gathering, Trustworthiness e.g. Public accountability |
iStatistician:professional of Statistics 4.0 by Walter Radermacher,
[Defend]
While data scientists are bringing into question the competencies of conventional statisticians, they are also being mobilized to reinforce and defend existing values that they command such as trustworthiness, public accountability, civil service and democratic legitimacy."Data scientists are not 'taking over' or replacing national statisticians but they are being relationally reconfigured through a process of differentiation"
[Key terms]
- Trustworthiness e.g.Facebook Cambridge Analytica Scandal
- Public accountability e.g. Groundbreaking public library run by bid data savvy company in Japan
- Civil service e.g. Big data use case in social media to prevent diseases
- Democratic legitimacy
