Data
IOB3-3-24
Samenvatting Colleges en materialen
,Inhoud
Week 1........................................................................................................................................ 3
College .................................................................................................................................... 3
Week 2........................................................................................................................................ 4
Lecture Data-ecologies ........................................................................................................... 4
How to shape data-ecologies ................................................................................................. 4
Key Concepts .......................................................................................................................... 4
Week 3 Data Modeling ............................................................................................................... 5
Lectures .................................................................................................................................. 5
Key Concepts .......................................................................................................................... 6
Interview................................................................................................................................. 6
Week 4 Data Collection .............................................................................................................. 7
Lectures .................................................................................................................................. 7
Key concepts........................................................................................................................... 8
Workshop ............................................................................................................................... 9
Week 5 Data Responsibility ...................................................................................................... 10
Lecture .................................................................................................................................. 10
All these worlds are yours (ChatGPT)................................................................................... 10
Key concepts......................................................................................................................... 11
Week 6 Data visualisation ........................................................................................................ 12
Lecture .................................................................................................................................. 12
Key Concepts ........................................................................................................................ 13
Week 7 Data Interaction .......................................................................................................... 14
Lecture .................................................................................................................................. 14
Key Concepts ........................................................................................................................ 16
Week 8 Data analysis ............................................................................................................... 17
Lecture .................................................................................................................................. 17
Key Concepts ........................................................................................................................ 18
2
, Week 1
College
Digital transformation: het proces en het effect van nieuwe digitale technologieën om
problemen op te lossen.
Digitale technologieën zijn overal en data is de brandstof.
Digitisation: analoge informatie digitaal maken.
Digitalization: processen en andere onderdelen van ons leven om digitale technologie en
informatie structureren.
Digitale technologie heft een grote invloed op de samenleving.
Digital society: effect op hoe we: communiceren, socialize, werken, leren, gezond blijven,
politiek.
Data (raw) → information (organized and structured) →
knowledge (analyzing, interpreting and analyzing) → wisdom
The map is not the territory; the representation might not be valid/ accurate
Real world = sum of all facts data = representation of all these facts
What does the data capture and what doesn’t it capture.
Types of data analytics: descriptive (what happened), diagnostic (why/ how did it happen),
predictive (what/ when will happen), prescriptive (how should we react).
Garbage in, garbage out: bad data in, bad behavior out.
Data wordt verzameld met sensors. Mensen zijn ook sensors.
Type of data sources: ad hoc, spontaneous, crowdsourcing
Data to understand design problem, data for inspiration, data as part of product, data for
testing.
Interacting with data, data for technology, data creating value for business.
3
IOB3-3-24
Samenvatting Colleges en materialen
,Inhoud
Week 1........................................................................................................................................ 3
College .................................................................................................................................... 3
Week 2........................................................................................................................................ 4
Lecture Data-ecologies ........................................................................................................... 4
How to shape data-ecologies ................................................................................................. 4
Key Concepts .......................................................................................................................... 4
Week 3 Data Modeling ............................................................................................................... 5
Lectures .................................................................................................................................. 5
Key Concepts .......................................................................................................................... 6
Interview................................................................................................................................. 6
Week 4 Data Collection .............................................................................................................. 7
Lectures .................................................................................................................................. 7
Key concepts........................................................................................................................... 8
Workshop ............................................................................................................................... 9
Week 5 Data Responsibility ...................................................................................................... 10
Lecture .................................................................................................................................. 10
All these worlds are yours (ChatGPT)................................................................................... 10
Key concepts......................................................................................................................... 11
Week 6 Data visualisation ........................................................................................................ 12
Lecture .................................................................................................................................. 12
Key Concepts ........................................................................................................................ 13
Week 7 Data Interaction .......................................................................................................... 14
Lecture .................................................................................................................................. 14
Key Concepts ........................................................................................................................ 16
Week 8 Data analysis ............................................................................................................... 17
Lecture .................................................................................................................................. 17
Key Concepts ........................................................................................................................ 18
2
, Week 1
College
Digital transformation: het proces en het effect van nieuwe digitale technologieën om
problemen op te lossen.
Digitale technologieën zijn overal en data is de brandstof.
Digitisation: analoge informatie digitaal maken.
Digitalization: processen en andere onderdelen van ons leven om digitale technologie en
informatie structureren.
Digitale technologie heft een grote invloed op de samenleving.
Digital society: effect op hoe we: communiceren, socialize, werken, leren, gezond blijven,
politiek.
Data (raw) → information (organized and structured) →
knowledge (analyzing, interpreting and analyzing) → wisdom
The map is not the territory; the representation might not be valid/ accurate
Real world = sum of all facts data = representation of all these facts
What does the data capture and what doesn’t it capture.
Types of data analytics: descriptive (what happened), diagnostic (why/ how did it happen),
predictive (what/ when will happen), prescriptive (how should we react).
Garbage in, garbage out: bad data in, bad behavior out.
Data wordt verzameld met sensors. Mensen zijn ook sensors.
Type of data sources: ad hoc, spontaneous, crowdsourcing
Data to understand design problem, data for inspiration, data as part of product, data for
testing.
Interacting with data, data for technology, data creating value for business.
3
