key: cord-0071088-cgapqjum
authors: Pánek, Jiří; Barvíř, Radek; Koníček, Jakub; Brlík, Milan
title: The emotional map of Prague – data on what locals think about the Czech capital?
date: 2021-11-27
journal: Data Brief
DOI: 10.1016/j.dib.2021.107649
sha: a206b8d91c1646e8b285625ce29fdb64d44cacaa
doc_id: 71088
cord_uid: cgapqjum

The paper presents the data from the participatory emotional mapping in Prague, Czech Republic. It contains 98,364 points complemented with 30,941 comments from 5,973 respondents across the city of Prague (1,335,084 inhabitants according to [1]). There were eight questions/statements common for all of Prague, furthermore each Prague district (n = 27) could add up to seven questions/statements. The data were collected via our own participatory mapping platform EmotionalMaps.eu from April to September 2021.

• Our dataset provides the largest sample of participatory emotional mapping in the Czech Republic so far, and possibly also in Europe. It allows further analysis of the urban sense of place and perceptions across various topics. • The data can be analysed by researchers focusing on crime geography, transport geography, as well as environmental psychologists and urban planners. The variety of topics is complemented with 30,941 comments about specific points. • The data provide insights into a broad variety of the citizens´experiences and perceptions in diverse, areas of interest (free time, places for visitors, neglected places, safety, transport, parking issues, urban green areas, and waste management) with information about the respondents' age and gender.

Data about urban perceptions and sense of place are valued amongst researchers from various disciplines, not just geospatial, but also from social sciences and environmental studies. Within our research we created a robust participatory mapping webpage, which included 27 separate emotional maps for each Prague district ( Fig. 1 ) , which are the basis for an overall city synthesis of mapped topics. The respondents were first asked to fill in the map for the district where they live, and then they could continue with other districts if needed.

As is visible from Table 1 , the sample is not representative regarding the age groups nor the gender balance, but as the data collection method can be defined as open and snowball-like, it was not the aim of this study to have a sociologically representative sample. Nevertheless, we believe it is sizeable enough to provide a complete overview.

The presented data were collected during the end of the third Covid-19 wave in the Czech Republic, so the preferred data collection method was the online approach. Physical meetings were originally planned in order to enrich the data collection strategy, nevertheless we were forced to abandon this plan. The dataset contains the raw, unprocessed data, with the exception that the labels and comments were translated into English. 

The data were collected via online participatory mapping platform EmotionalMaps.eu (in Czech) from April to September 2021. The platform was created in 2014 [2] (well described in [3 , 4] and since then it was used in over 200 various emotional mapping projects in several European countries. The data were collected for each of the Prague city districts separately and then merged. Eight questions/statements were common for all respondents (see Table 2 ) and then some districts decided to add further questions related to their specific neighbourhood (see Table 3 ). The eight questions/statements common for all of Prague were decided centrally There is a traffic hazard here (for walking, cycling, motor vehicle, lack of pedestrian crossing etc.) 6

There are parking problems (not enough parking spaces, cars parked inappropriately, etc.) 7 I would like more green space here 8

There is often an overflowing waste bin or collection point for municipal/sorted waste There is a lack of cycle links here Prague Dolní Po černice 36

There is a lack of a playground here Prague 18 37

There is a lack of a bench here Prague 18 38

There is a lack of a large-capacity car park Prague 18 39

There is a lack of a multi-purpose playground for the public Prague Dolní Po černice 40

Here is the centre of our neighbourhood Prague 11 41

Here there is often a mess Prague 11, Prague 18, Prague Dolní M ěcholupy 42

There is frequent clutter here Prague B řezin ěves 43

There is a missing pedestrian crossing Prague 12 44

This place is alive (good atmosphere) Prague 11 45

Here is a dangerous place on the cycle path Prague 18 46

Here is a problematic place to access (barrier) Prague 10 47

Here is a space where I want to educate myself Prague B řezin ěves 48

Here is too much noise 49

Here The environment here has deteriorated in the last year Prague 12 64

The environment here has improved in the last year Prague 12 65

The air here is bad to breathe and/ or polluted Prague 12 66

This is where we have our reunions Prague 11 ) . Furthermore, the option to add questions relevant to respective Municipal districts, was offered. We are not aware of the reason(s) why some districts did (not) use the opportunity. Some Prague districts used similar questions (we were not able to monitor or adjust the questions suggested by the districts' representatives), so the suggested broader categories are presented in Table 4 . We do not claim that data from these categories are mutually fully complemented, but we believe they can be used for cross district comparisons if needed. The categories are just suggestions and we are sure users can also find their own categories. The data were collected as point features, mainly based on the argument of [5] , who states that "The use of points for mapping PPGIS attributes and aggregating areas through density mapping constitutes a conservative approach to spatial inferences about a places significance, but the data demands for point collection are considerably higher than for polygon features." In our visualisations we expected users' inaccuracy in point placement and we used hexagons to aggregate the points into a regular grid for further visualisations. The hexagonal grid nevertheless is not part of the raw data provided in the dataset. Table 5 presents basics statistics for eight common questions for all of Prague, including the number of comments for each question. The most commented on (in relative numbers) is the question about traffic hazards, while the least commented on (again in relative numbers) is the statement "I would show this place to a visitor". The number of points represents how many locations were marked in each question. Each respondent had the opportunity to mark more points in each question and it was possible to skip questions, where the respondent did not want to mark any location. The dataset is saved and shared as a GeoJSON file, an open format for encoding and representing a variety of geographic data structures and features, including their non-spatial attributes (in our case, gender, age, and comments). GeoJSON is an extension of JSON format and can be easily read by any GIS software (we worked with open source QGIS) and any text editors such as Notepad. In the file, each line represents one feature (point), while columns represent the attributes. Coordinates and geometry type are directly written in the structure of the feature, while attribute values are written as "properties" -see below.

One feature would be written as this example: {"type": "Feature", "properties": {"ID": 1, "question": 1, "user_id": "d9w9tu8me", "comment_CZ": null, "comment_EN": null, "gender": "male", "age": "30-39 }, "geometry": {"type": "Point", "coordinates": [14.395566, 50 .090879]}}, Columns used in the GeoJSON file of our data are reported below:

• ID -unique Id of each feature • question -a number that represents the question/statement asked (see Tables 2 and 3 for explanations) • user_id -unique Id assigned to every user, so one can track answers from a specific user • comment_CZ -original comments attached to the specific point in the Czech language • comment_EN -translated comments (we used service DeepL for the translations) • gender -binary variable -male/female (or empty) • age -variable that can contain one of these age groups (0-19, 20-29, 30-39, 40-49, 50-59, 60-69, 70 + , empty)

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 

Ethical approval was not required for this study based on the following considerations: The study did not include medical aspects, person-identifiable data or sensitive or confidential data. The respondents also had the option not to fill in the data (age, gender).

Emotional maps

Emotional maps: participatory crowdsourcing of citizens' perceptions of their urban environment

Mapping citizens' emotions: participatory planning support system in Olomouc

An evaluation of the use of points versus polygons in public participation geographic information systems using quasi-experimental design and Monte Carlo simulation

The output has been financially supported by the Czech Science Foundation (GACR) as part of the grant project no. 19-14506S -Geoparticipatory spatial tools in the decision making processes of local administrations.

Supplementary material associated with this article can be found in the online version at doi: 10.1016/j.dib.2021.107649 .