Kommunebarometeret - Critical Comparison of Cities

Kommunebarometeret - Critical Comparison of Cities

Organisation: Kommunal Rapport (Norway)

Publication Date: 04/02/2016

Size of team/newsroom:small

Description

Measuring the 428 municipalities of Norway across 124 different data sets, Kommunebarometeret ('Measuring Municipalities') tells readers which municipality has the best scores overall and in each different service sector, among them school, elderly care, child protection services, kindergarden, health, culture and environment - but also economy and costs. The web site makes it possible for anyone to check how each municipality actually performs. Voters sometimes use the information to decide who to vote for, and most certainly politicians use the information either to defend their record or to critizise the ones in power for their ineptitude. This is the only national measuring in Norway of municipalities on such a scale. Subscribers to the site can also read independent, editorial analysis of each municipality - highlighting shortcomings, possible explanations and analytically based suggestions as to how to improve. The whole idea is based on our duty as a newspaper: To inform the public of how the money is spent, and whether it is spent well. The web side is the core of our coverage, but we procude numerous stories based on our findings in our weekly edition of Kommunal Rapport and our daily web site www.kommunal-rapport.no. Also, the measuring project generates more and more attention nationally. Just over 24 hours after publication, around 100 stories in other news media had been generated based on 'our' data set (which uses publicly available data), including a story on the main TV news programme. The project is primarily aimed at local politicians (our newspapers' core reader group). Around 7 % of the newspaper total income comes from this subscription revenue stream, making it a very important factor in business growth. Subscribers are mostly municipalities, but also state organisations and vendors. Others who have contributed in some way (journalists and external coders): Jens Finnäs, Samuel Brynolf, Ivar Bergman, Andreas Røed, Elmira Petkova, Vegard Venli, Anders Tjernblom, Christoffer Wadensten

What makes this project innovative? What was its impact?

We have taken the massive, overwhelming amount of data on municipalities and turned into something concrete, consise and easy to understand. Using the no longer innovative traffic light signal colour scheme, everyone can immediately see if the data places the municipality at the top or at the bottom of the "league table". Do this over 124 different data sets, you both cover almost every aspect people in general would care most of. Combine these 124 data sets into one main table, and you can pinpoint which municipality seems to be running efficiently at the benefit of the public, and which to not. Instead of trying to amass loads of visualisations, we go the other way: Make it as simple and easy to understand as possible. Some data are more important than others. We tell the readers which data that is, and what they actually tell us. As opposed to the PR laden versions you will find coming from the municipalities themselves. We constantly push limits, and by being innovative in this project (which started in late 2009 and has been evolving ever since) we also contribute to improving the quality of data delivered from the municipalities. Surveys show that 2/3 municipalities use our data now in their own reporting. Though a municipliaty that ranks high in the table is more likely to quote our findings, the ones with poor scores also report our results. We take the newspapers' credibility to new grounds, by creating new, analytical journalism that was quite simply not possible ten years ago, due to data quality and computer limitations.

Technologies used for this project:

We amass the data using simple web scraper technology, compiled into an .exe-program that runs in the background as soon as the majority of data are released. No complex stuff. A few statistics are picked up from other official sources manually as not everything is published at the same time or by one source alone. Data is then refined through simple VBA macros in Excel. The correctly formatted files are then run through automatically by some other VBA code, municipalities are ranked and scores handed out based on the criteria we have set in advance. When the rankings are done, we use more VBA code to produce around 95 % of the editorial analysis. The last 5 % is added by a journalist (or rather me, the news editor), drawing the main conclusions and highlighting discrepancies and other occations where the data throws up odd pictures of how the municipality is run. The rankings are then also the basis of "regular" journalism, identifying the good and interesting stories that bring the numbers to life. The web site is then produced in good old php with java scrips.
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