Uncertainty

Uncertainties

There can be many uncertainties identified, related to working with historical data.

• In general, good historical data (with sufficient temporal and spatial resolution) are scarce for many topics. 
• Some sources are unique, with the disadvantage of having no other independent data source to verify with. 
• Data are often only available in hard copy, not in digital format. 
• Data are sometimes only available in local libraries, or through researchers, and are not known to the public/internet. 
• Frequently missing data or strange 'jumps' in time series, sometimes as result of: 
• Differences in definitions and/or classification. 
• Old maps are often not allowed to be copied/digitized, or at very high expensives.      

Because history can not be reproduced by experiments, statistical techniques or other procedures, researchers have to rely on the historical data sources available as they are. It is important to be aware of the background of the data source itsself ('official' census data have sometimes been known to be manipulated by governments, guestimates, etc) and to look at the data in a objective, critical way. For modeling purposes and analysis it is unavoidable sometimes to manipulate the original data in order to get reasonable time series. The following solutions have been applied in order to overcome some of the problems mentioned above:

• Interpolation techniques have been applied sometimes to fill in gaps in time series. Sometimes lineair, or exponential were applicable.
• Regional growth rates have been applied to seperate countries in that region, in order to get a first order estimate. These regional totals could sometimes be compared with estimates from other authors.
• Allocation of areas of cropland and pasture have been linked to historical population densities. It is questionable whether population density is an acceptable proxy for the allocation of cropland and pasture. It seems reasonable to assume that where people are living, there always has been some sort of agricultural activity, especially in the past. With the current availability of historical population numbers, on the national scale as well as on the sub-national scale, this approach has the advantage that some migration patterns can be reproduced (e.g. with state level information USA).      

It is obvious that there is no real satisfying solution for the problems mentioned. The HYDE data base does not claim to give a complete overview of global environmental change for the past centuries, but only tries to assist researchers in providing times series of indicators of global change.

Therefore, comments are welcome about (the missing of) data(sources), as well as about the approaches followed to derive time series or maps.