The scanners can devide between children and grown ups by size. We guess that small grown ups are categorized as children by the algorithm. In the dataset we downloaded, the distinction is not made, but all pedestrians higher than 90cm are counted as a +1.
It remains unclear, wether people in a wheelchair, carried children, buggies etc. are categorized.
The hours under observation start at X:00 and end at X:59:59. The data from the scanners come in every few minutes and are then commulated for the whole hour.
the unit of observation is defined as person/h. it is defined in absolute numbers. it does not decide between different categories of people (even though technically it could decide between 'adults' and 'children')
There is very little information on the definitions. Two points I stumbled over: In the sheet, there is a mention of a discrepancy of data coming from a different department - without any further explanations. So it would be interesting how this discrepancy happended and how there are different measurment logics involved. And the second point: on the website the data source is provided with the add-on: based on estimated quantity. So it remains very unclear how the measuring process is happening and how the data are generated.
It also only provides the average of water use for one year. In another graphic provided at the website, it shows the change of proportion of different clients between 1990 and 2021. The water use of households and small companies increased dramatically, but it does not state if the overall amount has increased or only the proportions have changed.
The document doesn't give information on the definitions of the seven categories that are represented in the table. It might be interesting to find out, how the broad bundles of practices have been made -- why is the toilet flush not subsumed under body care, why is car cleaning in the same category as garden watering? The categorizations made might come from the urge to find broad enough categories to make graphics and tables readable (opposed to a fine-grained detailed table with hundreds of different practices that use water). But they might also emerge from contraints in measurment, if the spended water is measured with counters intstalled at different water valves in the house. That would fit very plausible to the categorizations as for example watering a garden and cleaning a car is most probably both done with a water valve outside, if existing and accessible. It would be interesting, wether queries have been made to configure the list of practices that are mentioned and how they are clustered or wether they result from mere considerations of what valve is most propably used for what.
The category that evades my ways of making sense of the data and imagining their crafting-process is that of "small business" in the last row. If it would be different water valves, this would not make sense, unless this number just points to workshop-watervalves which would not include tea-cooking in the kitchen of creative workers in home office for example.
The laser scans all pedestrians above 90cm that cross an imagined line within one hour. Because the line is produced in more-dimensionally, it can measure the walking direction, different zones on the street, and the pedestrians' height. However, it does not discriminate between individual pedestrians - so, crossing the laser repeatedly in a counting interval means the pedestrian is counted multiple times.
In the documentation, the definition is actually that it is not necessarily a delivery, but instead as a "different form of involvement". This seems misleading with regard to the table heading.
Text based / String type data for the name of the place or the service ; a category or type of service (For ex. fast food) ;
A scale / range of wheelchair accesibility rating from 1 (not accessible) to 3 (accessible) ;
Optional picture upload ;
Address information from openstreetmap.org
Data seems to be taken from open access streetmap.
companies involved in arms exports to war zones and warring states
"global overview of companies that are involved in arms exports to war zones and warring states. It currently covers almost 600 companies, including parent companies, subsidiaries and joint ventures. It is not a general look at defence companies, but specifically at companies that are involved in various ways in arms deliveries to war zones."
"The starting point for the database is the selection of conflict actors/conflict states based on the Heidelberg Conflict Barometer. It has been published by the renowned Heidelberg Institute for Conflict Research since 1992. Compared to its peers in empirical conflict research, this institute integrates qualitative criteria more strongly in its research in order to categorize states as crisis or war zones. This makes it possible to identify conflict dynamics at an early stage.
Only conflicts that reached conflict intensity 4 (limited war) or 5 (war) at least once in the period from 2016 to 2021 were included in the current version of ExitArms.org. Intensity levels one and two include non-violent conflicts. Level three describes conflicts in which violence is used without the use of military weapons. The conflict intensity definition by the Heidelberg Conflict Barometer is based on an assessment of the conflict consequences in terms of victims, refugees, militarization, degree of organization of violence, and destruction of infrastructure. Additionally: ExitArms.org does not include conflicts for which the United Nations Security Council has issued a mandate under Chapter VII of the United Nations Charter that includes the use of force."