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Exploring the Transforming City by Digital Methods. Case: Lä
Transcript of Exploring the Transforming City by Digital Methods. Case: Lä
Non-machine-readable, incomplete, imprecise or highly subjective data means we had to imagine and build our data sets
Map data and tools lack standardisation
Privacy concerns limit access to data on health, wellbeing and mental life of residents
Identification, collection, classification and analysis of old photographs
We wanted to make sense of the freely usable museum collections on
related to our area and period of study, mainly consisting of
records of photographs with a digitized image
. The photos included
some descriptive metadata
; a year and keywords f.ex., but
no real location information
The contents of the index were not available as a single dump but through queries via
. To create a collection of relevant records we used a
list of historical and current street names
automated queries to api.finna.fi
. This provided us with a list of records that contained
hundreds of unique, relevant images
with very few false positives.
Social Sciences' Methodology
Grounded Theory is a systematic methodology in the social sciences
involving the construction of theory through the analysis of data.
A study using grounded theory is likely to begin with a question, or even just with the collection of
. As researchers review the data collected, repeated
become apparent, and are tagged with
, which have been extracted from the data.
As more data are collected, and as data are re-reviewed, codes can be grouped into concepts, and then into categories.
These categories may become the basis for new theory
. Thus, grounded theory is quite different from the traditional model of research, where the researcher chooses an existing theoretical framework, and only then collects data to show how the theory does or does not apply to the phenomenon under study.
As we were interested in impressions, we had to produce a
way for the computer to understand the impressions
in the photographs. We manually divided the keywords in two categories representing the
“old”, “soft”, “spontaneous” and “free” wooden Länsi-Pasila
“new”, “hard”, “rational” district
that replaced it. We have used the categorization to
calculate a value for each image
This trial was highly experimental and not scientific at all, while with more meaningful distinctions the method could be useful. The added location data gives one potentially interesting dimension to the data and simplifies the re-use of pictures in further research.
YLE Data Word Cloud
district, located within today’s Länsi-Pasila, was a diverse residential area constructed from the 1890s onwards and inhabited by working class families, originally mainly railroad workers of the near-by railyards. The early development of was driven by Helsinki's industrialization and rapid population growth. The houses were built on City-owned rented plots, there were no city plans nor building regulations and the neighborhood grew organically. Houses were built in close proximity to each other and no two houses were alike.
The City of Helsinki
threatened not to renew the land plot leases for the first time already in the 1940s and uncertainty about the future led slowly to dereliction of the buildings as nobody was willing to invest in renovations. The housing and sanitary conditions were poor and Wooden Pasila became eventually area of cheap rental housing described as ‘an emergency landing’ place for the poorest.
In the early 1970s the City of Helsinki started actively buying and even confiscating buildings and terminating plot leases in the area.
show how young people and families were the first to move out, typically to suburban housing estates and eventually only the old people remained by late 1970s.
The number of people living in area, which had been according to un-verified sources close to 3000 at the best, started decreasing to 181 in 1980.
The trouble of making alive collections of historical images
Emerging Research Question(s)
The relationship between the radically transforming built-environment and the social change of the neighborhood:
* The gradual disappearance of the original urban community over time, eventual displacement of old/older poor residents, emerging of the new community with new residents.
* The change reflected againts wider societal development of the period. Social policies, modernist ideals in material production of housing, City of Helsinki land-use policy and housing policy.
Urban renovation projects are alike, which means we should be able to learn from past projects and avoid their errors
A New Town Plan for Länsi-Pasila
in 1979, and the old wooden buildings were quickly demolished. A modern city district was constructed with mostly younger new residents started moving in.
By 1989 when the main phase of the construction of today's Länsi-Pasila was finished, there were approx. 5000 residents. Länsi-Pasila has relatively large share of municipal social housing (21.5% of the housing stock) as well as a considerable amount dedicated student housing.
The impressions and experiences of people living in and visiting the transformed areas are a good source of information to measure the success of these projects
GROUP 3: EXPLORING HELSINKI
Jussi Kulonpalo (Univ. Helsinki, Social Research/Urban Studies)
Timo Laine (Univ. Helsinki, Moral and Social Philosophy)
Kari Laine (Aalto University, Computer Networks)
Antti Härkönen (Univ. Eastern Finland, General History)
Susanna Ånäs (Aalto University, MediaLab)
Kaisa Sarén (Univ. Helsinki, Bioinformatics)
Maija Paavolainen (Univ. Helsinki, Library Sciences)
Rauli Laitinen (Aalto University,
Built Environment/ Urban Academy)
There are several ways the situation can be improved and
will likely improve
quality of data
is making progress and
new tools and algorithms
are becoming available inside and outside universities
Urban Exploration ->
Starting Point // The Data
The hard evidence”
City of Helsinki (HRI.fi) population, housing etc.
statistical data of the area and various official City documents. Maps and GIS data.
”The soft evidence”
Historical FINNA photos of Helsinki, their #keywords and other metadata.
The objective media”
Different media data (the YLE dataset).