Garage48 Visualising Data

Overview

Agenda

Get Ready

Challenges

Have you ever stared at a massive spreadsheet of data and thought how much prettier it would look when visualised? Does your mind instantly wanders to diagrams, charts and graphs or do you prefer to bring data alive through animation and movement?

The art of making data beautiful and sexy is taking the world by storm. Data and data analysis have taken on a new quality and what used to be simple charts are now complex and creative pieces of data art. A good visualisation tells a narrative, removing the noise from data and highlighting the useful information - it’s a storytelling with a purpose.

HOW DOES IT ALL WORK?

We start on Thursday, 9th of May at 15:30 with registration. At 16:00 we kick off with the event, lead by Karin Sarv - our wonderful host from Mooncascade! Friday, 10th of May at 17:00 is the time to show your work and win some amazing prizes. Check the AGENDA tab on our website for more thorough plan for the 24 hours.

Statistics Estonia has prepared a selection of tasks and data which you can open here: https://gitlab.com/statistics-estonia/hackaton-2019-visualising-data/hackaton-info

All different approaches and visualisations are welcomed and even expected (front-end code, for example static javascript files, animated codes, videos). Let the most colourful idea win! You will have 90 seconds to present your idea to the crowd. Teams will be formed on the spot around the best and brightest solutions.

After the event Statistics Estonia would like to access the codes of the solutions, so they expect the
teams to publish the codes in a public repository, which is accessible for everyone. They are also providing a public GitLab account in case you don’t have an option to upload your work yourself. All the visualisations will be added to a public library for everyone to see by Statistics Estonia.

WHO’S INVITED TO JOIN?

Garage48 and Statistics Estonia are inviting:

- designers,

- front end developers,

- data scientists/enthusiasts,

- business masterminds/project managers (to coordinate the work of the teams),

- movie makers and artists to tell a story through a good visualisation. Come and help to transform the boring rows in Excel into a beautiful and eye-catching visualisations that will help the Statistics Estonia to carry out the future projects that will change Estonia and the way we look at data.

VENUE, FOOD AND DRINKS

Visualising Data Hackathon will be held in one the most vibrant blocks in Tallinn - Palo Alto Club in Telliskivi Creative City. We don’t want you to worry about food and drinks and snacks. We got you covered. You just focus on making data sexy!

Join us and let’s make data great again!

Join the event in Facebook!

Get your tickets HERE!

Thursday, 9th of May
15:30 Registration, coffee and snacks
16:00 Opening remarks by G48 host and Statistics Estonia
16:30 Presenting / pitching the ideas and challenges
18:00 Team formation
18:30 Team work begins
21:00 Pitch training

Friday, 10th of May
09:00 Breakfast
10:00 Checkpoint #1
11:15 Team work continues
13:00 Lunch
13:30 Team work continues
15:00 Pitch drill with the demo
17:00 Light snacks and coffee
17:30 Final presentations
19:00 Award ceremony and networking

WHAT TO BRING WITH YOU?

Positive attitude, an open mind and lots of energy! Be open, get to know new people, share your ideas and give ideas/feedback to other teams. MOST IMPORTANT - have fun!

Please take your:
1) Laptop
2) 3-5m power extension cord (as power might be at a distance)
3) All chargers
4) Water bottle and thermos (help us reduce the use of plastic in this event)

PITCHING IDEAS

Statistics Estonia will present their challenges and database to all the participants.

If participants have their own ideas, they should present their ideas based on "elevator-pitch" method within 90 seconds. You can prepare 1 PDF slide to support your pitch. You should send the slide by Wednesday, 8th of May 19.00, to merit@garage48.org.

TEAM FORMATION
The average team will have 4 to 6 people. The team should be balanced which means that all required roles should be covered - designer, front end developer, data scientist/data analyst/ data enthusiast, project manager. This is essential in order to get the product/service ready in 24 hours.

After Statistics Estonia has presented their challenges and participants with their own ideas have pitched, the teams will be formed and work starts.

Datasets can be found in Statistics Estonia database in English and Estonian, here:
http://andmebaas.stat.ee/?lang=et
http://andmebaas.stat.ee/?lang=en
Just copy-paste the table numbers (indicated near the challenges) and you’ll find the data.

NB! Data that is connected to challenges nr.5 and nr.6 can be found here: https://gitlab.com/statistics-estonia/hackaton-2019-visualising-data/hackaton-info (MFA data.xlsx and Youth_in_Estonia.xlsx)

We suggest the solutions to be built around the personalised approach of an individual or an enterprise – how I’m personally related to the dataset, or how is my enterprise doing?

1. POPULATION

1.1 Population pyramids by local municipalities and counties, by years
(Source: dotStat database table RV0241 (years 2012-2017 – place of recidence before 2017 administrative reform) and RV0240 (years 2015-2019 - place of recidence after 2017 administrative reform))

1.2 Population projections – a tool for user to forecast Estonian population by year x.
• User could input some values to see what happens with the forecast: total fertility rate, mortality, net migration, etc.
(Source: dotStat database: RV0212 – population by sex and age beginning of the year or RV021 – population by sex and age groups)

1.3 Migration count and distribution by local municipalities and counties – Where do people
settle and where do they leave from? (Source: dotStat databases: RVR02)

1.4 Population clock – animated increase/decrease of Estonian population by
minutes/days/months/years (Source: dotStat database tables RV0213 ja RV0213U)

1.5 How long do I live? (Source: dotStat databases RV045 – life expectancy by sex and age,
RV0451, RV0452, RV0453, RV0454 – life expectancy in different breakdowns)

1.6 Statistics about date (day, month, year) – a tool for user to see information about inserted
date:
• How many people (boys and girls) celebrate their birthday on this day in Estonia?
(Source: Data in Excel: Birthdays 2019.xlsx)

• How many people born in this month/year? (Source: dotStat database RV10)
• How many people born in this year by county? (Source: dotStat database RV11, RV112,
RV112U)
• What is the life expectancy for this date? (Source: dotStat database RV045)

2. LABOUR MARKET

2.1 Labour force analysis – labour tree or other tool to describe distribution of population aged
15-74 by labour status (number of people and rates), or by years with the possibility to
change age groups.
Source: Yearly data: TT331, TT220, TT217, TT43, TT451. Quarterly data: TT461, TT478,
TT477, TT441, TT452
Supporting schemas: https://www.stat.ee/dokumendid/1518883 and
https://www.stat.ee/dokumendid/37136

2.2 Which profession to choose: employed persons by age group, sex, economic activity, major
group of occupations (Source data tables: TT0201, TT0202, TT2129 or any other section in
Employed persons’ annual statistics)

3. SALARIES IN ESTONIA

3.1 Average gross wages (salaries) based on monthly quarterly and annual data Source: PA006,
PA001
• Where do I stand in salaries pyramid?

3.2 Average gross wages (salaries) Source: PA001, PA003, PA005, PA22, PA5335
• Where to get more salary? – by economic activity, economic activity section, type of
owner of an economic unit, county, gender

3.3 Gender pay gap (GPG) by economic activity PA5335
• How big is the GPG in the field I work at?

4. ESTONIAN ENTERPRISES AND ENTERPRISE DEMOGRAPHY

4.1 Active Estonian enterprises:
• by administrative units (whether by local municipalities or counties) and
• by economic activity
• How has the distribution changed over the years?
• How an administrative reform in 2017 affected distribution by counties?
NB! Due to administrative reform the time series presented in two tables.
Source: dotStat database tables: 2000-2017y table RE031, 2017-2018y table RE0309. Please note
that 2017y data is doubled for both database table.

4.2 Active Estonian enterprises:
• by administrative units (whether by local municipalities or counties) and
• by number of employees
• How has the distribution changed over the years?
• How an administrative reform in 2017 affected distribution by counties?
NB! Due to administrative reform the time series presented in two tables.
Source dotStat database tables: 2000-2017y table RE32, 2017-2018y table RE032. 2017y is doubled
for both database table.

4.3 Active Estonian enterprises:
• by economic activity and
• by legal form
• How has the distribution changed over the years?
Source dotStat database table: RE029

4.4 Active Estonian enterprises:
• by economic activity and
• by type of owner
• How has the distribution changed over the years?
Source dotStat database table: RE026

4.5 Active Estonian enterprises:
• by economic activity and
• by number of employees
• How has the distribution changed over the years?
Source dotStat database table: RE025

4.6 Active, born and dead enterprises:
• by counties and
• by economic activity and
• by number of employees
• How has the distribution changed over the years?
• How has the survival rate (proportion of the born enterprises in active enterprises) changed
over the years?
• How has the deaths rate (proportion of the death enterprises in active enterprises) changed
over the years?
Source dotStat database tables: RE051, RE052, RE053

4.7 Survived enterprises:
• by year of birth
• by number of employees
• by economic activity
• by counties
• Which enterprises are more viable during 5 first years of their life?
Source dotStat database table: RE060

5. ECONOMY-WIDE MATERIAL FLOW ACCOUNTS (EW-MFA)

Economy-wide material flow accounts (EW-MFA) are a statistical accounting framework describing
the physical interaction of the economy with the natural environment and the rest of the world economy
in terms of flows of material.

How to visualize the data on the flows of material resource? How Estonia pops up among other
countries of EU?

5.1. Material Flow Accounts is providing important information and statistical indicators on
material use: how much and what kind of materials are extracted, are these materials used by
national economy itself or are mostly exported?
Main datasets : Statistics Estonia database tables EN91, EN957. In case you use attached
“MFA_data.xlsx”, Estonian data are on sheet: “Domestic extraction” and “Exports - physical
units”, for other countries data, international data for EU Member Countries are available
in Eurostat database: https://ec.europa.eu/eurostat/data/database under the following category:
Environment and energy -> Environment -> Material flows and resource productivity->
Material flow accounts. (env_ac_mfa)

5.2. What kinds of materials are imported, what is the balance between export and import of
materials?
Dataset: Statistics Estonia database tables EN956, EN957, EN958. In case you use attached
“MFA_data.xlsx”, Estonia’s data are on a sheet:” Imports - physical units”. For trade balance
there is also sheet “Exports - physical units”, data for EU Member Countries are available
in Eurostat: https://ec.europa.eu/eurostat/data/database under the following category:
Environment and energy -> Environment -> Material flows and resource productivity->
Material flow accounts. (env_ac_mfa)

5.3. How efficiently materials are used? What is resource productivity (how much of GDP is
generated per one ton used material)? How Estonian economy is doing compared to other EU
members from point of view of material use or generation of residues?
Dataset: Statistics Estonia database table EN99. In case you use attached “MFA_data.xlsx”,
Estonia’s calculated indicators are on a sheet named ”Indicators publ-d by STAT EE”. Data
for EU Member Countries are available in Eurostat:
https://ec.europa.eu/eurostat/data/database under the following category: Environment and
energy -> Environment -> Material flows and resource productivity-> Resource
productivity:(env_ac_rp)

Supporting datasets:
Population figures: Statistics Estonia database tables PO0211 (population data). Data for EU
Member Countries are available in Eurostat database:
https://ec.europa.eu/eurostat/data/database under the following category: >Population and
social condition ->Demography and migration -> Population change - Demographic balance
and crude rates at national level ->average population total (demo_gind)

GDP - NAA0061: Gross domestic product by expenditure approach (ESA 2010) - gross
domestic product at market prices and chain-linked volumes (2010), million euros
International data for EU Member Countries are available in Eurostat database:
https://ec.europa.eu/eurostat/data/database under the following category: >Economy and
finance->National accounts (ESA 2010)-> Annual national accounts-> main GDP aggregates-
> GDP and main components (output, expenditure and income) (nama_10_gdp)-> gross
domestic product at market prices and chain-linked volumes (2010), million euros

The attached Excel sheets (MFA_data.xlsx) contain material flow accounts data tables
which Estonian Statistics provide to Eurostat. The sheet Estonian indicators contain calculated
material flow main indicators (published), population figures and gross domestic products
(which have been used for indicator calculation). Attached word file contains data description
and definitions. International data for EU Member Countries are available in Eurostat
database: https://ec.europa.eu/eurostat/data/database under the following cathegory:
Environment and energy -> Environment -> Material flows and resource productivity.

6. YOUTH CONDITIONS IN ESTONIA

(Source: Data in Excel: Youth_in_Estonia.xlsx)
6.1 How to present youth data in a playful way – from youth to youth? How can statistics draw
young people’s attention?

6.2 How can young people compare themselves to one another? Which parameters could be
used for comparing regional differences (e.g. my municipality against the whole country/my
county/other municipalities in Estonia or in our neighbourhood)?

6.3 How can young people check their knowledge about youth statistics? Which municipalities
have the largest proportion of young people, most young entrepreneurs, most hobby
schools, etc?

6.4 How to present regional youth data to show the diversity? Map is always a good way. What
other methods do we have to express data localisation?

Garage48 Visualising Data

1. POPULATION

2. LABOUR MARKET

3. SALARIES IN ESTONIA

4. ESTONIAN ENTERPRISES AND ENTERPRISE DEMOGRAPHY

5. ECONOMY-WIDE MATERIAL FLOW ACCOUNTS (EW-MFA)

6. YOUTH CONDITIONS IN ESTONIA

#G48TALLINN #G48VISUALISINGDATA

THE SUPERSTARS
The Mentors

Organizers

The Programme is brought to you by:

1. POPULATION

2. LABOUR MARKET

3. SALARIES IN ESTONIA

4. ESTONIAN ENTERPRISES AND ENTERPRISE DEMOGRAPHY

5. ECONOMY-WIDE MATERIAL FLOW ACCOUNTS (EW-MFA)

6. YOUTH CONDITIONS IN ESTONIA

#G48TALLINN #G48VISUALISINGDATA

THE SUPERSTARSThe Mentors

Organizers

The Programme is brought to you by:

THE SUPERSTARS
The Mentors