Spatial data old and new

Good Old Data

What is good about it?

Collected for the purpose

carefully designed

Detailed in information

rich profiles

High quality

precise methods

What is less good about it?

Massive enterprises

costly

Coarse in resolution

privacy-led aggregation

Slow

more details are less frequent

Examples

Decennial census (and census geographies)

Longitudinal surveys

Customly collected surveys, interviews, etc.

Economic indicators

New Forms of Data

Tied into the (geo-)data revolution, new sources are appearing.

Accidental

Created for different purposes but available for analysis as a side effect

Diverse

nature

resolution

quality

Detailed

Potentially, much more detailed

in both space and time

How to categorise them?

There are different ways

Lazer & Radford (2017)

Digital life (Twitter/X, Facebook, Wikipedia…)

Digital traces (record of digital actions (CDRs, metadata…))

Digitalised life (non intrinsically digital life in digital form (Government records, web…))

Arribas-Bel (2014)

Bottom up (“Citizens as sensors”)

Intermediate (Digital businesses/businesses going digital)

Top down (Open Government Data)

Opportunities

Massive, passive

Nowcasting

Data on social systems

Natural and field experiments (“always-on” observatory of human behaviour)

Making big data small

Challenges

Bias

Technical barriers

Methodological “mismatch”

Old or new?

Old and new!