AnneLaure - Potato Families

Network of potatoes.
From the database scraped *..( 5600 potatos + pedigree (their parents)
plotting the communities of potatoes. mapping the mother-daughter relation
every name = potato, all arrows pointing to mother
5700 pairs of mother-daughter relationship.. selected then the groups around one mother but not the links between groups (some potatoes have two mothers)..
selected only the potato names with readable names ( not the L451-F )
community plot (in R), igraph library

if mother is not in db, doesn't mean she has one
most are doploid, some are mutants!

--> R manual: you don't understand how fucntion works, you just use it
it's apparently unknown the name of the ultimate foremother of the potatoes..

Hans - Potatent-scraping

Big battle with the server of the EU patent database.. Lots of request rejections!
Actually they developed an open patent services, as written in the request pages.. In the mean time we found another website to scrape texts of patents...
The mapping of the owner of patents could be added to the potato families..
Most intense patenters are Lays, Smitsol for Mcdonald's fries and McCain..

Next steps:
use list of varieties, do text searches on patents -> see which varieties are named
gives a matrix that maps varieties & second that maps the property rights of these varieties
you could also make timeline -> show how cancer of patenting is devleoping over the varieties
-> corpus for week 2 -> patent (de)generator for potatos

APP - Average Potato Project

Some parts of datafetish, some part reflecting on what data to collect, what to keep hidden..
creation of the Average Potato.
Bought 3 sets of potatoes from Delhaize (B, NL, F), named them, dealt with them in a scientifical manner. Measured them, weight them
Cooked them in the end for the average mesh!
Average potatoes made out of the mashed, which weight the average potato.

hybrid species: one represents average weight/size of 3 different species
bpp.cvs: data of original potatos
app.cvs: data of average potatos

you can always add data to datasets, endless
measured average shape (represented in their logo)

did first graphical representations of datasets
closest relation with the potato.. modelling the mash.
very rational creatures, data, you need a lot of messiness to extract something interesting.. measuring the potato, encounter with the scientifical model.
messiness = 'mashiness'

Point of view of potato: lends itself very well to process of messiness and meshiness, was more resistant to adapt itself to measurable data again (precise size and weight)
resistent to take the shape of an average potato..

Correlations scatterplots

correlations, finally.
correlatinf data from the scraped database of all potato data.
difficult to get something out of the raw data.. so visualization.. plotting the correlations color coded..
with visualzation of how much data contributes to create a correlations..
visualizing images of the potato in question, selecting different correlations, exploring the names, the images, the links to the website

Look into measurements 'medium', 'littel'
-> gave values in numbers for all these, mapping all the terms into numbers, so that they could be plotted..
"how much bigger is medium than small?" :)
appears that the hollow heart tendency relates to dormancy period..
Data < The European Cultivated Potato Database (Scotland)

From the same dataset, Michael made visaulisation with different parameters & values
'it quickly becomes a big mess'
'kind of a mash': mashes the text low/medium/low as mash of 3 numbers

Kate, Nicolas, An - Feral Tradilations

amiguities in the database. 
the choices of the structure and of the use of the database influence its readability..
The informations should NOT be extremely precise.. make it possible to understand what's happening, but not on a full transparency agenda. also because of datamining.
degree of precision.. layering of shipments and hops.
send name of location to 'geonames' database to for gps coordinates - sometimes it works, sometimes not (0)
changing fields & spaces, we offer more potential to datanaming
'it made a decision there, which is wrong'
results for railway stations are extremely precise -> keyword helps the geolocation

An, Database is very personal, subjective..
In this case, datamining really becomes storytelling. Some datamining of the feral trade database was made, and the questions were kind of disturbing.
Invasion of the private space.
Palm reading has grown a lot lately - according to undisclosed sources on the internet - comparison between the hand lines and the growing and changing of databases..
The lines reveal somehow a genealogy more than a state of being.. What about databases?
Palm reading is ideological. 1. if you are a woman, the structure of your birth is on your left hand, the experiences on the right hand. for man can be the opposite. also older than 30. different opinions.

Courier line, showing the people near..
Life line, major life changes, healts..
Invoices line, in 2007 a peak and then goes down till 2010.. Kate had an accident.
Life line coincides with the faith line. Must be 2010..
There is a second faith line even. seems to coincide with the peaks of summer trades..

Famous Last Words

M: difficult to get into it, to find a way to go to a practise 
G: really like 2/3 days on lectures - interesting theoretical context set; but also with M's practical example with 3D, to see something being done with given information
-> what works better? filter theory throughout the week (with the coffee)
P: difficult, you need to be fed in the beignning; sensed a discrepency which is inevitable between presentation of people outside/inside the group
beginning was steep, has to do with the subject, large & impenetrable - look at your personal scale works very well
takes a lot of time to find your way in
G: Thursday was first day to really start
H: brainstorm was on Wednesday, we could have preminaliry ideas the first day
G: after avalanche of information, it would be difficult to do a brainstorm --- (needs reorganising, equilibruim)

R: interesting, a lot of ideas raised, curious to know what happens next week with stuff done this week
fille din Ricardo's scraber, Michael built upon my work
think what it means to appropriate language & technique one is critizing, to what extend it is necessary to deeply understand in order to critizise
did straight forward mathematical visualisation, without explicit social commentary - hope someone can use it for something and make something that engages with larger conversation here
has no seen resolution to that question of relation between techniques & sociality we're critiquing
-> interesting to make a claim of a correlation, gives a sense of consequence

Do we want to make claims like that at all?
and can we use mathematical correlation for that?

Did we fell in the digital trap? Using frameworks and accepting their way of being/working without questioning it?
R: 'you start believing it'
the more I developed, the less I understood'

K: AL datamined Feral Trade, I could see difference between datamined data & data of db; interrogation techniques
the data duel, we both thought we 'won': she found interesting phenomenons, I thought she didn't; both were valid
-> any correlation could be meaningful/less; without my knowledge you don't know
data alone = dead, has to be animated by story; can support ideology, feedback loop between data & design
potato db I find really meaningless

G: by imitating the process, you start understanding the data
ask continuously: what have I really done? discovered?
APP: making numbers out of action / raw & cooked data

how deal with bureaucratical data without having access to databases/raw data?

Karin: correlation in politics are made all the time, put forward, replicated in studies....
seeing this is playful, shows the limitations... in week you create average potato, in EU this would take 7 years
illustrative on how you can use data/imitate

7/8 brands dominate the market vs 5700 existing species
potential to look into social relations & way you're working

Scottish database & scatterplot: making claim that has some sense, sell that to someone, contrast your claimed correlation to existing one in the market
needs closer collaboration to identify what this kind of playful claims can have as an effect
'no one makes the claim that data are only looked at in excel sheet'
potential avenues in using some of the ways you're working for other people than you
'playfulness' is opening up to a lot of new ideas
-> denying causal link that 'we' (EUpeople) would claim

Julie: arrived on Tuesday, terms that were not familiar; nothing in my practise that relates to what we're looking at
frustrating, looked at reason why some items are absent in dbses:
    not valid on the market, not allowed to sell species, looked into policies that decide upon this
    not productive, but interesting
Barbara: interesting, cannot come next week
thesis on potatos,; full research in 1 day
got to know a lot of people, inside activism, art...
photogrpahy/video... no knowledge about computer programming, saw interesting estaetic practises (like Roberts)

Leo: good overview of possibilities around data, tools/representations/images...
loved the talks, very wide, and some very practical

Stamatia: felt like the potato
resistant towards rational aspects of programming/writing with numbers
tried to start to learn something
good combination of theory & practise, different points of view
made me more 'malleable' 

Anita: not used to time schedule, very nice talks also during the breaks

hot potato
patati patata
mashed potato 'dance'