ESA, in collaboration with European Space Imaging, has collected this WorldView-2 dataset covering the most populated areas in Europe at 40 cm resolution. The products have been acquired between July 2010 and July 2015. Spatial coverage: Check the spatial coverage of the collection on a map available on the Third Party Missions Dissemination Service.

World Cities provides a basemap layer for the cities of the world. The cities include national capitals, provincial capitals, major population centers, and landmark cities. Population estimates are provided for those cities listed in open source data from the United Nations Statistics Division, United Nations Human Settlements Programme, and U.S. Census Bureau.

Cities are major drivers of environmental change at all scales and are especially at risk from the ensuing effects, which include poor air quality, flooding and heat waves. Typically, these issues are studied on a city-by-city basis owing to the spatial complexity of built landscapes, local topography and emission patterns. However, to ensure knowledge sharing and to integrate local-scale processes with regional and global scale modelling initiatives, there is a pressing need for a world-wide database on cities that is suited for environmental studies. In this paper we present a European database that has a particular focus on characterising urbanised landscapes. It has been derived using tools and techniques developed as part of the World Urban Database and Access Portal Tools (WUDAPT) project, which has the goal of acquiring and disseminating climate-relevant information on cities worldwide. The European map is the first major step toward creating a global database on cities that can be integrated with existing topographic and natural land-cover databases to support modelling initiatives.

Context

This dataset has been obtained by scraping TA (the famous tourism website) for information about restaurants for a given city. The scraper goes through the restaurants listing pages and fulfills a raw dataset. The raw datasets for the main cities in Europe have been then curated for futher analysis purposes, and aggregated to obtain this dataset.

The scraper is a Python script, available on the GitHub repository here.

It uses principally pandas and BeautifulSoup libraries.

IMPORTANT: the restaurants list contains the restaurants that are registrered in the TA database only. All the restaurants of a city may not be resgistered in this database.

Content

The dataset contain restaurants information for 31 cities in Europe: Amsterdam (NL), Athens (GR) , Barcelona (ES) , Berlin (DE), Bratislava (SK), Bruxelles (BE), Budapest (HU), Copenhagen (DK), Dublin (IE), Edinburgh (UK), Geneva (CH), Helsinki (FI), Hamburg (DE), Krakow (PL), Lisbon (PT), Ljubljana (SI), London (UK), Luxembourg (LU), Madrid (ES), Lyon (FR), Milan (IT), Munich (DE), Oporto (PT), Oslo (NO), Paris (FR), Prague (CZ), Rome (IT), Stockholm (SE), Vienna (AT), Warsaw (PL), Zurich (CH).

The data is a .csv file comma-separated that contains 125 433 entries (restaurants). It is structured as follow: - Name: name of the restaurant

• City: city location of the restaurant

• Cuisine Style: cuisine style(s) of the restaurant, in a Python list object (94 046 non-null)

• Ranking: rank of the restaurant among the total number of restaurants in the city as a float object (115 645 non-null)

• Rating: rate of the restaurant on a scale from 1 to 5, as a float object (115 658 non-null)

• Price Range: price range of the restaurant among 3 categories , as a categorical type (77 555 non-null)

• Number of Reviews: number of reviews that customers have let to the restaurant, as a float object (108 020 non-null)

• Reviews: 2 reviews that are displayed on the restaurants scrolling page of the city, as a list of list object where the first list contains the 2 reviews, and the second le dates when these reviews were written (115 673 non-null)

• URL_TA: part of the URL of the detailed restaurant page that comes after 'www.tripadvisor.com' as a string object (124 995 non-null)

• ID_TA: identification of the restaurant in the TA database constructed a one letter and a number (124 995 non-null)

Missing information for restaurants (for example unrated or unreviewed restaurants) are in the dataset as NaN (numpy.nan).

Acknowledgements

This work has been done as a personal interest but also as a training of the skills I got from the DataCamp data science bootcamp I have followed.

I hope you will find this dataset inspiring and will make great stories out of it that I will be pleased to read :)

Costs of coastal flooding and protection are essential information for risk assessment and natural hazards research, but there are few systematic attempts to quantify cost curves beyond the case study level. Here, we present a set of systematically derived damage and protection cost curves for the 600 largest (by area) European coastal cities. The city clusters were identified by an automated cluster algorithm from CORINE land cover 2012 data, following the Urban Morphological Zone (UMZ) definition.The data provides detailed cost curves for direct flood damages at flood heights between 0 and 12 m on a 0.5 m increment. Costs estimates are based on depth damage functions for different land use obtained from the European Joint Research Center. The necessary mapping between land use and land cover is based on Land Use/Cover Area frame Survey (LUCAS) 2015 primary data. The underlying inundation maps were derived from the European Digital Elevation Model (EU-DEM).Furthermore, the data contain curves for the cost of protection at the same heights and increments as the damage curves, assuming no previously installed protection. These curves are available both for a low and high cost scenario and are based on hypothetical protection courses derived from cluster data and inundation maps.All cost estimates are given in Euro and were inflation-adjusted to 2016 price levels. For spatial reference, we include the individual raster tiles depicting the extent of each city cluster.The research leading to these results has received funding from the European Community's Seventh Framework Programme under Grant Agreement No. 308497 (Project RAMSES). Supplement to: Prahl, Boris F; Boettle, Markus; Costa, Luis; Kropp, Jürgen P; Rybski, Diego (2018): Damage and protection cost curves for coastal floods within the 600 largest European cities. Scientific Data, 5(1), 180034

This dataset contains the data displayed in the figures or the article "High-resolution projections of ambient heat for major European cities using different heat metrics".

The different files contain:

Data_Fig1_DeltaTXx_EURO-CORDEX_1981-2010_to_3K-European-warming_RCP85.nc: Change of yearly maximum temperature in Europe between 1981-2010 and 3 °C European warming relative to 1981-2010.

Data_Fig2_timeseries-GSAT-ESAT_EURO-CORDEX_CMIP5_CMIP6_1971-2100_RCP85_SSP585.xlsx: Time series of global mean surface air temperature (GSAT) for CMIP5 and CMIP6 models, and for European mean surface air temperature (ESAT) for EURO-CORDEX, CMIP5, and CMIP6 models for the period 1971-2100.

Data_Fig3_TX-distribution_distance-from-city-centre_E-OBS_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for E-OBS for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.

Data_Fig3_TX-distribution_distance-from-city-centre_ERA5-Land_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for ERA5-Land for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.

Data_Fig3_TX-distribution_distance-from-city-centre_EURO-CORDEX_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for the EURO-CORDEX models for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.

Data_Fig3_TX-distribution_distance-from-city-centre_weather-stations_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for GSOD and ECA&D stations for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.

Data_Fig4_TX-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models.

Data_Fig5_Contribution-of-explanatory-variables-to-total-explained-variance.xlsx: Contribution of different explanatory variables (climate and location factors) to the total explained variance of spatial patterns of heat metrics.

Data_Fig6_TN-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx: Nighttime heat metrics for the investigated cities: HWMId-TN at 3 °C European warming relative to 1981-2010, TN exceedances above 20 °C at 3 °C European warming relative to 1981-2010, and TNx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models.

Data_Fig7_TX-ambient-heat_CMIP5_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP5 models.

Data_Fig7_TX-ambient-heat_CMIP6_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP6 models.

Data_Fig8_GCM-RCM-matrix_ambient-heat_3K-European-warming.xlsx: GCM-RCM matrices for the three heat metrics.

The empirical dataset is derived from a survey carried out on 25 estates in 14 cities in nine different European countries: France (Lyon), Germany (Berlin), Hungary (Budapest and Nyiregyha´za), Italy (Milan), the Netherlands (Amsterdam and Utrecht), Poland (Warsaw), Slovenia (Ljubljana and Koper), Spain (Barcelona and Madrid), and Sweden (Jo¨nko¨ping and Stockholm). The survey was part of the EU RESTATE project (Musterd & Van Kempen, 2005). A similar survey was constructed for all 25 estates.

The survey was carried out between February and June 2004. In each case, a random sample was drawn, usually from the whole estate. For some estates, address lists were used as the basis for the sample; in other cases, the researchers first had to take a complete inventory of addresses themselves (for some deviations from this general trend and for an overview of response rates, see Musterd & Van Kempen, 2005). In most cities, survey teams were hired to carry out the survey. They worked under the supervision of the RESTATE partners. Briefings were organised to instruct the survey teams. In some cases (for example, in Amsterdam and Utrecht), interviewers were recruited from specific ethnic groups in order to increase the response rate among, for example, the Turkish and Moroccan residents on the estates. In other cases, family members translated questions during a face-to-face interview. The interviewers with an immigrant background were hired in those estates where this made sense. In some estates it was not necessary to do this because the number of immigrants was (close to) zero (as in most cases in CE Europe).

The questionnaire could be completed by the respondents themselves, but also by the interviewers in a face-to-face interview.

Data and Representativeness

The data file contains 4756 respondents. Nearly all respondents indicated their satisfaction with the dwelling and the estate. Originally, the data file also contained cases from the UK.

However, UK respondents were excluded from the analyses because of doubts about the reliability of the answers to the ethnic minority questions. This left 25 estates in nine countries. In general, older people and original populations are somewhat over-represented, while younger people and immigrant populations are relatively under-represented, despite the fact that in estates with a large minority population surveyors were also employed from minority ethnic groups. For younger people, this discrepancy probably derives from the extent of their activities outside the home, making them more difficult to reach. The under-representation of the immigrant population is presumably related to language and cultural differences. For more detailed information on the representation of population in each case, reference is made to the reports of the researchers in the different countries which can be downloaded from the programme website. All country reports indicate that despite these over- and under-representations, the survey results are valuable for the analyses of their own individual situation.

This dataset is the result of a team effort lead by Professor Ronald van Kempen, Utrecht University with funding from the EU Fifth Framework.

This dataset contains information on the characteristics of Local Climate Adaptation Plans in Europe. A sample of 328 medium- to large-sized cities across the formerly EU-28 was investigated for the availability of Local Climate Plans and strategies on climate change adaptation. A set of 168 cities out of the 328 were identified to have at least one, if not more Local Climate Adaptation Plans. The contents of these plans were documented, using an elaborated framework combining indicators of state-of-the -art plan quality principles with indicators of justice/ equity theory. Used common plan quality principles are 1) Fact base - Climate change impact, risk and vulnerability assessment (related to risk, sectors, justice), 2) Adaptation goals (related to risk, quantitative); 3) Adaptation measures (distributed across 12 sectors, justice); 4) Implementation process (prioritization, responsibility, timeframe) & tools (budget); 5) Monitoring & evaluation (responsibility, timeframe, justice). Additionally to the information on these 5 plan quality principles information on the (potential) participation process, a communication strategy, the national and regional context, as well as with access information, access data, access type, and other meta data were retrieved and documented. The publication dates of the plans range from 2005 - 2020. The collection period ranges from March 2019 to June 2021, depending on the country and city, with the majority collected between May 2019 and June 2020. Content analysis of EU Local Climate Adaptation Plans and Strategies Date: Data collection: March 2019 to June 2021, depending on the country and city. (Publication) Date of local adaptation plans: 2020.

Abstract copyright UK Data Service and data collection copyright owner. The aim of this research was a comparative study of the development of and globalisation of real estate markets in three capital cities of Budapest, Prague and Warsaw. The specific objectives of the research are: to identify the form and inter-relationship between administrative structures/agencies and the operation of the planning and development process at the metropolitan and borough levels; to identify the means of financing real estate development in central Europe, particularly the role of international institutional and emerging local investors; to identify the supply side constraints, regional demand-side prospects and national investment processes; to identify the structure and working processes of the real estate investment market; to ascertain the changing trend of economic activities, particularly commercial and business, and their spatial and property impacts. Main Topics: The data set comprises three different categories of data and 15 different data files. Category 1 relates to the results of a postal survey of international real estate investors and developers. One data file is dedicated to this category. Category 2 relates to the results of semi-structured interviews carried out in the three cities of Budapest, Prague and Warsaw. In each city respondents were chosen according to the three main categories of a) private actors directly involved in the markets, i.e., real estate developers, financiers/banks, investors, agents and consultants, b) public city officials impacting on real estate activity and c) real estate occupiers. Altogether, therefore, nine data files are dedicated to the results of the interviews covering three main categories of respondents in each of the three cities. Category 3 consists of six maps showing the location of major office and retail projects in the three cities. Purposive selection/case studies Face-to-face interview Postal survey Compilation or synthesis of existing material

Table of Content: 1. General context of the data set "lsUDPs" ; 2. Background and aims of the study using the data set lsUDPs; 3. The data set lsUDPs: 3.1 Selection of cases and data collection; 3.2 Data management and operationalisation 1. General context of the data set "lsUDPs" The data set "lsUDPs" has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2020. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, strategic spatial plans) into quantitative land-change modelling approaches at the urban regional level. The first stage (2016-2017) of the CONCUR project focussed on 21 urban regions in Western Europe. The urban regions were selected through a multi-stage strategy for empirical research (see Hersperger, A. M., Grădinaru, S., Oliveira, E., Pagliarin, S., & Palka, G. (2019). Understanding strategic spatial planning to effectively guide development of urban regions. Cities, 94, 96–105. https://doi.org/10.1016/j.cities.2019.05.032 ). 2. Background and aims of the study using the data set lsUDPs As part of the CONCUR project, a specific task was to examine the relationship between strategic spatial plans and the formulation and implementation (i.e. urban land change) of large-scale urban development projects in Western Europe. Strategic urban projects are typically large-scale, prominent urban transformations implemented locally with the aim to stimulate urban growth, for instance in the form of urban renewals of deprived neighborhoods, waterfront renewals and transport infrastructures. While strategic urban projects are referred to in the literature with multiple terms, in the CONCOR project we call them large-scale urban development projects (lsUDPs). Previous studies acknowledged both local and supra-local (or structural) factors impacting the context-specific implementation of lsUDPs. Local governance factors, such as institutional capacity, coordination among public and private actors and political leadership, intertwine with supra-local conditions, such as state re-scaling processes and devolution of state competencies in spatial planning, de-industrialisation and increasing social inequality. Hence, in implementing lsUDPs, multi-scalar factors act in combination. Because the formulation and implementation of lsUDPs require multi-scalar coordination among coalitions of public and private actors over an extended period of time, they are generally linked to strategic spatial plans (SSPs). Strategic spatial plans convey collective visions and horizons of action negotiated among public and private actors at the local and/or regional level to steer future urban development, and can contain legally binding dispositions, but also indicative guidelines. The key question remains as to what extent large-scale urban development projects and strategic spatial plans can be regarded as aligned. By alignment, or “concordance”, we mean that strategic projects are formulated and implemented as part of the strategic planning process (“high concordance”), or that the strategic role of projects is reconfirmed in (subsequent) strategic plans (“moderate concordance”). Lack of concordance is found when lsUDPs have been limitedly (or not at all) acknowledged in strategic spatial plans. We assume that certain local and supra-local factors, characterising the development of the projects, foster (but not strictly “cause”) the degree of alignment between lsUPDs and SSPs. In this study, we empirically examine how, and to what extent, the concordance between 38 European large-scale urban development projects and strategic plans (outcome: CONCOR) has been enabled by five multi-scalar factors (or conditions): (i) the role of the national state (STATE), (ii) the role of (inter)national private actors (PRIVATE), (iii) the occurrence of supra-regional external events (EVENTS), (iv) the degree of transport connectivity (TRANSP), and (v) local resistance from civil society (RESIST). We adopted a (multi-data) case-based qualitative strategy for empirical research and applied the formalised procedure of within- and cross-case comparison offered by fuzzy-set Qualitative Comparative Analysis appropriate for the goal of this study. Based on set theory, QCA formally integrates contextual sensitivity to case specificities (within-case knowledge) with systematic comparative analysis (across-case knowledge). The research question the data set has been created to reply to is the following: which conditions, and combinations of conditions, enable the concordance between large-scale urban development projects and strategic spatial plans? The conditions (“independent variables”) considered are. STATE: the set of large-scale urban projects characterized by a high degree of state intervention and support in their formulation and implementation, PRIVATE: the set of large-scale urban projects characterized by a high degree of involvement of (inter)national private actors in their formulation and implementation, EVENTS: the set of large-scale strategic projects whose formulation and implementation have been strongly affected by unforeseen international events and/or global trends, TRANSP: the set of large-scale strategic projects with a high degree of road and/or transit connectivity, and RESIST: set of large-scale strategic projects whose realization has been characterized by resistances that have substantially delayed or modified the project implementation. The outcome (“dependent variable”) under analysis is CONCOR: the set of large-scale urban projects having a high degree of concordance/alignment/integration with strategic spatial plans 3. The data set lsUDPs 3.1 Selection of cases and data collection To generate the current data set on large-scale urban development projects in European urban regions (data set "lsUDPs"), we identified 35 large-scale urban development projects in a sample of the 21 Western urban regions considered in the CONCUR project (see supra, Hersperger et al. 2019): Amsterdam, Barcelona, Copenhagen, Hamburg, Lyon, Manchester, Milan, Stockholm, Stuttgart. The criteria we followed to identify the 35 large-scale urban development projects are: geographical location, size (large-scale), site (located either in the city core or in the larger urban region) and urban function (e.g. housing, transportation infrastructures, service and knowledge economic functions). Employing these criteria facilitated the selection of diverse large-scale urban development projects while still ensuring sufficient comparability. In 2016, we performed 47 in-depth interviews with experts in urban and regional planning and large-scale strategic projects and infrastructure (i.e. academics and practitioners) about the formulation, implementation and development (1990s–2010s) of each project in each of the 9 selected urban regions. On average, each interviewee answered questions on 3.1 large-scale urban development projects. Three cases were subdivided into two cases because a clear differentiation between specific implementation stages was identified by the interviewees (expansion of the Barcelona airport, cases “bcn_airport80-90” and “bcn_airport00-16”; realisation of Lyon Part-Dieu, cases “lyo_partdieu70-90” and “lyo_partdieu00-16”; MediaCityUK, cases “man_salfordquays80-00” and “man_mediacityuk00-16”). Therefore, from the initial 35 cases, the final number of analysed cases in the lsUDPs dataset is 38. 3.2 The data set lsUDPs: Data management and operationalisation Interviews were fully transcribed and analysed through MAXQDA (version 12.3, VERBI GmbH, Berlin, Germany), and intercoder agreement was evaluated on a sample of nine interviews. We also compiled “synthetic case descriptions” (SCD) for each case (totalling more than 160 SCDs) to spot potential inconsistencies among interviewees’ accounts and to facilitate completion of the “calibration table” for each case (see below). An online expert survey distributed to the interviewees (response rate 78%) helped systematise the information collected during the interviews. We also consulted both academic and gray literature on the case studies to check for possible ambiguity and inconsistencies in the interview data, and to solve discrepancies between our assigned set membership scores and questionnaire values. Site visits were also carried out to retrieve additional information on the selected cases. For each case (i.e. each of the 38 selected large-scale urban development projects), we operationalised each condition (i.e. STATE, PRIVATE, EVENTS, TRANSP, RESIST) and the outcome (CONCOR) in terms of sets, for subsequent application of Qualitative Comparative Analysis. This process is called “calibration”; we used a number of indicators for each condition to qualitatively assess each large-scale project across the conditions. The case-based qualitative assessment was then transformed into fuzzy-set membership values. Fuzzy-set membership values range from 0 to 1, and should be conceived as “fundamentally interpretative tools” that “operationalize theoretical concepts in a way that enhances the dialogue between ideas and evidence” (Ragin 2000:162, in “Fuzzy-set Social Science”. Chicago: University Press). We employed a four-value fuzzy-set scale (0, 0.33, 0.67, 1) to “quantify” into set membership scores the individual histories of cases retrieved from interview data. Only the condition TRANSP was calibrated as a crisp-set (0, 1). The translation of qualitative case-based information into numerical fuzzy-set membership values was iteratively performed by populating a calibration table following standard practices recently emerged in

The European cities experimented, during the 20th century, industrialization processes and agricultural changes that triggered the rural-urban exodus. A mostly young population left their rural territories work in cities. These massive migratory movements were the catalyst for the situation of depopulation and aging that currently suffer many rural regions of Europe. Spain is one of the European countries most affected by depopulation. The region of Castilla y León, in the northwest of the country, due to its orographic characteristics and the dispersion of its population in a large number of small municipalities, has been and still is especially vulnerable to the loss of inhabitants in favour of large cities, converting a large part of its territory in a good example of demographic desert. Many municipalities suffer physical isolation due to their orographic environment and, additionally, they present also technological isolation resulting from coverage issues in both land lines and mobile networks. The main objective of this study is to priority areas where the improvement of technological infrastructures and services can lead to reverse or stop the current depopulation trend, at a time when teleworking can be an important lifeline for many rural municipalities.

Abstract copyright UK Data Service and data collection copyright owner. The theoretical aim of this research is to examine and understand why innovative and competitive firms tend to cluster in a limited number of particular cities. The project is also seeking to understand the observed variety of supplier and customer arrangements among firms and the interactions between these and the firms' home city regions. These concerns raise questions about the characteristics of different stages of the innovation process and why firms' activities have been seen to vary from flexibly specialised local production networks, in mainly craft-based older industries, in new industrial districts; to individually produced innovations linked primarily in the context of competitive secrecy to major international customers. Research on the London region (further London data are also held separately in the companion study to this one, SN:4360 'Innovation in the London Region, 1999-2000') was informed by the comparative perspective of innovation studies in the four European cities of Amsterdam, Milan, Paris and Stuttgart. A common questionnaire was administered in the five cities to a common sample frame of innovative companies who had won awards for basic research in industrial technologies for Europe (BRITE). In addition to this common sample frame, innovative firms drawn from local databases were also interviewed. The lessons from this first stage of the research were taken forward into a more in-depth research study of innovative and external support systems in the London metropolitan region where the sampling frame was identified using a variety of innovation awards. The purpose of gathering data for the five European cities in one study was to implement a common methodology for five of the most innovative regions in Europe. The regions were selected from a group of ten cities identified by the European Union as the ten most significant islands of innovation within the EU. Data were collected from 160 telephone interviews with industrial firms who were asked about specific innovative projects - an average of 32 firms from each city.

This dataset contains the responses of 292 academic experts asked to review the state of city leadership in 202 cities internationally, addressing a series of queries as to the shape, performance and pressing challenges city leadership confronts in countries around the world.What does ‘city leadership’ entail in an increasingly networked global scenario? How do city leaders respond to global challenges and contribute to global governance? How are they influenced by city- to-city networking? How does city leadership translate into strategic responses to global challenges? Urban Gateways is designed to improve our understanding of how city leadership translates into long-term strategic visions, how it relates and contributes to global governance and how this global action is perceived ‘on the ground’ in cities. Urban Gateways will provide a global overview of the city leadership and strategic plans in both developing and developed countries, highlighting leadership approaches, strategic trends, foresight drivers and major hindrances in the development of strategic urban plans addressing global challenges. The project focuses both on major global cities and second-tier cities to offer not only international comparative assessments but also multi- tiered considerations that de-centre globalist models of international and urban research. The team began by selecting a target group of 200 cities. The ethos behind these selection criteria was that comparative urban research should aim to incorporate the experiences of a diverse array of cities across both the global North and South. In particular we wished to gather viewpoints that might serve as alternatives to the well-known perspectives of heavily researched so-called ‘global’ and ‘mega’ cities. The team developed an initial list of 200 cities with a roughly equal distribution among regions of the world and city size. The team grouped cities into six regions, based on the regions used by the World Bank. These were East Asia and the Pacific (including Oceania), Latin America and the Caribbean, the Middle East and North Africa, South and Central Asia and Sub-Saharan Africa. One deviation from the World Bank approach was our grouping of North America and Europe. The team also included several ‘outlier’ cities, that were geographically isolated, such as island cities (such as Male in the Maldives) and cities in remote regions of the world (Nuuk in Greenland). The research team then sought to identify at least one expert per city to address a series of questions as to the current shape, challenges and performance of city leadership in each city. Experts were selected on the basis of their academic track record (several recognisable publications) of expertise on a specific city in the pool of 200 (finally at 202 in total) cities surveyed.

The Global Monthly and Seasonal Urban and Land Backscatter Time Series, 1993-2020, is a multi-sensor, multi-decadal, data set of global microwave backscatter, for 1993 to 2020. It assembles data from C-band sensors onboard the European Remote Sensing Satellites (ERS-1 and ERS-2) covering 1993-2000, Advanced Scatterometer (ASCAT) onboard EUMETSAT satellites for 2007-2020, and the Ku-band sensor onboard the QuikSCAT satellite for 1999-2009, onto a common spatial grid (0.05 degree latitude /longitude resolution) and time step (both monthly and seasonal). Data are provided for all land (except high latitudes and islands), and for urban grid cells, based on a specific masking that removes grid cells with > 50% open water or < 20% built land. The all-land data allows users to choose and evaluate other urban masks. There is an offset between C-band and Ku-band backscatter from both vegetated and urban surfaces that is not spatially constant. There is a strong linear correlation (overall R-squared value = 0.69) between 2015 ASCAT urban backscatter and a continental-scale gridded product of building volume, across 8,450 urban grid cells (0.05 degree resolution) from large cities in Europe, China, and the United States.

This dataset is a research outcome of a European Research Council, Starting Grant funded (Grant Number 679097, Industrialisation and Urban Growth from the mid-nineteenth century Ottoman Empire to Contemporary Turkey in a Comparative Perspective, 1850-2000, UrbanOccupationsOETR) project. It contains a mid-nineteenth-century urban Ottoman population micro dataset for the city of Bursa.

In recent decades, a "big microdata revolution" has revolutionized access to transcribed historical census data for social science research. Despite this, the population records of the Ottoman Empire, spanning Southeastern Europe, Western Asia, and Northern Africa, remained absent from the big microdata ecosystem due to their prolonged inaccessibility. In fact, like other modernizing states in the nineteenth century, the Ottoman Empire started to enumerate its population in population registers (nüfus defterleri) in 1830, which recorded only males of all ages for conscription and taxation purposes. These registers were completed and updated in two waves, one in 1830-1838 and the other in the 1839-1865 period. Following this experience, the Empire implemented its first modern census, which included females, in 1881/1882 for more comprehensive statistical and governance reasons to converge with European census-taking practices and account for the increasing participation of females in economic and social spheres.

The pre-census population registers were opened to researchers in 2011. There are around 11.000 registers today. The microdata of the late Ottoman censuses is still not available. Still, unfortunately, the majority of the existing literature using the population registers superficially utilized and failed to tabulate the microdata. Most works using these valuable sources contented with transcribing the microdata from Ottoman to Latin script and presenting their data in raw and unstyled fashion without publishing them in a separate repository.

Our dataset marks the inaugural release of complete population data for an Ottoman urban center, the city of Bursa, derived from the 1839 population registers. It presents originally non-tabulated register data in a tabular format integrated into a relational Microsoft Access database. To ensure that our dataset is more accessible, we are also releasing the dataset in Microsoft Excel format.

The city of Bursa, a major cosmopolitan commercial hub in modern northwestern Turkey, is selected from the larger UrbanOccupationsOETR project database as an exemplary case to represent the volume, value, variety, and veracity of the population data. Furthermore, since urban areas are usually the most densely populated locations that attract the most migration in any country, they are attractive locations for multifold reasons in historical demography. Bursa is not the only urban location in the UrbanOccupationsOETR database. As it focused on urbanization and occupational structural change, it collected the population microdata on major urban centers (chosen as primary locations) and towns (denoted as secondary locations), which pioneered the economic development of post-Ottoman nation-states. What makes the city of Bursa’s data more advantageous than other cities is that it has been cleaned and validated multiple times and used elsewhere for demographic and economic analyses.

The Ottoman population registers of 1830 and 1839 classified the population under the commonly and officially recognized ethnoreligious identities- Muslim, Orthodox Christian, Armenian, Catholic, Jewish, and (Muslim and non-Muslim) Roma. Muslim and non-Muslim populations were counted in separate registers. The registers were organized along spatial and temporal lines. The standard unit of the register was the quarter (mahalle) in urban and village (karye) in rural settings. Within these register units, populated public and non-household spaces such as inns, dervish lodges, monasteries, madrasas, coffeehouses, bakeries, mills, pastures (of nomads), and large private farms (çiftlik) were recorded separately.

The household (menzil/hane) was the unit of entry, which sometimes took different forms depending on the context, such as the room for inns and the tent for nomads. Each household recorded its members on a horizontal line. The variables of male individuals inhabiting them were self-reported biographical information (names, titles/family names, ages, and occupations), physical description (height and facial hair), relationships with other household members (kinship, tenancy, and employment ties), infirmities, and military and poll tax status, including the reasons for exemption, military post, and poll tax category (high-ala, medium-evsat, and small-edna). Households with no inhabitants were differentiated. At the same time, if a resident was known to be absent during registration due to reasons such as military service or migration, he was recorded in his household with a note stating that reason. If he was missing and appeared later, he was added to the household during updates with a note like “not recorded previously” (e.g., hin-i tahrirde taşrada olub) or “newly recorded” (tahrir-mande).

In addition to the permanent residents of a given location, migrant/temporary non-local (yabancı) residents such as laborers, inn-stayers, and unskilled bachelors (bî-kâr) were recorded along with their place of origin and for how long they had been in the migrated place. Non-Muslim migrants were registered with information regarding the last location where they got their poll tax certificate and if they would make their next poll tax payment in the migrated location.

Updates were made mainly to births, deaths, migrations, and military and poll tax status. No other variables, such as age, were renewed except for occupations in a limited number of cases. Updates are easily identifiable since they were written in siyakat, a special Ottoman chancery shorthand script, and occasionally in red ink. Births were specified with newborns’ names added next to the father’s entry. Deaths were updated by crossing out the deceased person’s record. Migrations were added with a description of the migrated place (including the military branch if the person was conscripted). Military and poll tax status was updated by crossing out the old category and adding the new one next to it. Updates were usually expressed in hijri years, sometimes in month-year, and rarely in day-month-year fashion. It is important to note that since updates were made once every few months, these dates may reflect their registration date rather than giving the exact time of the events. Equally crucial is that many events, especially births, were not reported, so their quality is limited.

Modeled after the way information was contained in the population registers, this relational database has two tables, “tblHouse” and “tblIndividual.” Each table categorizes and standardizes the register variables. To make the data easier to use, the dataset also includes a query “Query_InnerJoin” that combines all the variables from each table in a separate sheet.

Given Bursa’s important place in Ottoman history, our dataset serves as a large and crucial resource for comprehending historical societal, economic, and demographic trends within the Empire in the early stages of globalization. The dataset has 8391 household entries (HouseID) and 19,186 individual (IndivID) entries. This data includes the population registered in all of Bursa’s quarters and other location categories in 1839 and the updates until and including 1843 (Figure 2). The ethno-religious breakdown of the total population is 12462 Muslims (65%), 3315 Armenians (17%), 2466 Orthodox Christians (13%), 749 Jews (4%), and 194 Catholics (1%).

To broaden access and use of our data and bring it more in line with findability, accessibility, interoperability, and reusability (FAIR) data guidelines, the variables of “tblHouse” and “tblIndividual” are sorted into general categories and described in detail in the following tables. As the variables indicate, the dataset and population registers, in general, could serve to formulate unprecedented, hitherto impossible research questions related to major demographic dynamics, i.e., household size and composition, ethnoreligious differences, population density, occupational structure, intergenerational mobility and status transfer, mortality, fertility, migration, age-heaping/human capital, conscription, settlement patterns within and across urban locations, onomastics, toponymy, etc.

Table 1: Categories and descriptions of the variables of tblHouse

The Global Monthly and Seasonal Urban and Land Backscatter Time Series, 1993-2020, is a multi-sensor, multi-decadal, data set of global microwave backscatter, for 1993 to 2020. It assembles data from C-band sensors onboard the European Remote Sensing Satellites (ERS-1 and ERS-2) covering 1993-2000, Advanced Scatterometer (ASCAT) onboard EUMETSAT satellites for 2007-2020, and the Ku-band sensor onboard the QuikSCAT satellite for 1999-2009, onto a common spatial grid (0.05 degree latitude /longitude resolution) and time step (both monthly and seasonal). Data are provided for all land (except high latitudes and islands), and for urban grid cells, based on a specific masking that removes grid cells with > 50% open water or < 20% built land. The all-land data allows users to choose and evaluate other urban masks. There is an offset between C-band and Ku-band backscatter from both vegetated and urban surfaces that is not spatially constant. There is a strong linear correlation (overall R-squared value = 0.69) between 2015 ASCAT urban backscatter and a continental-scale gridded product of building volume, across 8,450 urban grid cells (0.05 degree resolution) from large cities in Europe, China, and the United States.

This dataset provides values for INFLATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Habitat loss and fragmentation globally threat biodiversity and ecosystem services. However, major research biases and knowledge gaps in biogeographical regions, taxonomic groups, landscape metrics and species’ biological responses studied, are recurrent in fragmentation studies. Detecting these biases and associated gaps is crucial to steer future research efforts and to guide applicable conservation policies. We conducted a systematic literature review and extracted data from 107 articles to evaluate biogeographic, taxonomic and ecological biases in fragmentation research on the highly-diverse terrestrial fauna in peninsular Spain. We observed that research was biased towards mountain ranges, southeastern drylands and nearly largest cities. Specifically, the Cantabrian Range comprised the highest density of studies, while open dehesas in western Spain and Atlantic coastal forests in the northwest were overlooked. We also found an overrepresentation of studies (77%) on vertebrates and a high positive relative bias for birds, while several invertebrate taxa were neglected in the literature. Fragmentation was more frequently considered than habitat loss. Habitat degradation and patch size reduction were the most studied metrics, while patch isolation, edge effect and matrix contrast were underrepresented. Assemblage-level species responses (abundance and richness) comprised 86% of studies, while interspecific interactions, genetics and individual conditions were largely underrepresented. Our findings indicate major gaps in the studies focused on the effects of habitat loss and fragmentation on the Spanish fauna. We recommend that fragmentation research in this diverse region from southern Europe needs to consider undersampled taxa, further fragmentation metrics and biological responses to avoid inappropriate inferences for conservation actions.

Attitudes to the EC, 2. Problems of environmental protection. Topics: 1. Attitudes to the EC: citizenship and eligibility to vote at place of residence; contentment with life; satisfaction with democracy; opinion leadership and frequency of political discussions; postmaterialism; frequency of obtaining news from television, radio and newspapers; preference for a dictatorship under certain conditions; major reasons for one´s own election participation; associations with the terms European Community and European Union; judgment on personal level of information about the EC; attitude to European unification and membership of one´s own country in the EC; advantages or disadvantages for the country from EC membership; regret of a possible failure of the EC; knowledge about the location of selected EC institutions; future significance of EC membership of the country for the country and the people; most important personal interests that will be achieved through the EC; satisfaction with the attitude of selected institutions and persons to Europe; self-perception as European or member of a nation-state (split: in the second case the key word ´citizen´ was introduced in the formulation of the question); judgment on current and desired speed of unification for Europe; knowledge about the European flag; cities, media and events, at which the European flag was seen; attitude to the European flag; attitude to the European Commission; preference for a national or European decision-making authority in selected political areas; attitude to reform of EC agricultural policy; knowledge about the European domestic market; expectations of the domestic market and reasons for hopes or fears; general attitude to the domestic market and a European social policy; expected effects from the domestic market; attitude to a European Government and the European Parliament; general significance of the European Parliament in selected political areas; attitude to an increasing significance of this parliament; agreement with expanded transfer of authority to the EC in an economic and currency union as well as in a political unification; knowledge about the Maastricht conference, the treaty and contents; evaluation of the significance of the Maastricht Treaty for the EC; expected effects of the Maastricht Treaty for the EC, for one´s own country and personal life; agreement with admission of selected countries into the EC and positive or negative effects originating from this for the old member countries; willingness to pay increased taxes to support Eastern Europe; knowledge about the most powerful EC institution; attitude to an eligibility to vote for EC foreigners at local and EC level; attitude to admission of Southern European job-seekers, emigrants from Eastern Europe as well as political applicants for political asylum; judgment on the proportion of foreigners from non-EC countries in one´s country and an extension of their rights; perceived disturbance from presence of people of foreign nationality, race and religion.2. Problems of environmental protection: urgency of environmental protection; personal concern about selected environmental problems(scale); preference for economic growth or environmental protection; concern about the effects of selected economic areas on the environment; most important economic areas polluting the environment; classification of the extent of various types of environmental pollution in one´s residential surroundings (scale); concern about individual areas of environmental pollution in one´s country (scale); perceived seriousness of dangers to the environment and most important effects of these dangers; actual commitment and general readiness for active environmental protection (scale); assessment of the efficiency of local, regional, national, European as well as world-wide environmental protection institutions; need for information about environmental protection; most trustworthy sources of information; preferred topics for the environmental protection conference in Rio de Janeiro; interest in information on the year of ´civil defense´. Demography: self-classification on a left-right continuum; party allegiance; party preference (Sunday question); behavior at the polls in the last election; union membership; marital status; age at end of education; resumption of school training after an interruption and length of school training; length of further education; sex; age; size of household; number of children in household; possession of durable economic goods; occupational position; weekly number of working hours; supervisor status; employment in the civil service or private enterprise (company sector); person managing household; head of household; age of head of household at end of education; occupation of head of household; supervisor status of head of household; self-assessment of social class; residential status; degree of urbanization; religious denomination; frequency of church attendance; religiousness; monthly household income; city size; region. Also encoded was: date of interview; length of interview; presence of third persons during interview; willingness of respondent to cooperate. Indices: opinion leadership (cognitive mobility); postmaterialism; attitude to Europe; status in profession; party preference on European level; EC support; support for the EC domestic market; media usage. The following questions were posed only in Norway: highest school degree; further education and college attendance. The following additional questions were posed only in the new states: use of selected sources of information about the EC; perceived EC topics; most important sources of information about occurrences in the state, in the Federal Republic and in Europe; classification of credibility of selected sources of information; interest in further information about the EC; preference for brief or detailed information on political questions; assessment of the EC role in the achievement of equivalent standard of living between East and West Germany; knowledge about individual EC organs and their tasks; knowledge about EC member countries. The following questions were posed only in Portugal: knowledge and significance of the Portuguese EC presidency. The following questions were posed only in Ireland: agreement with Irish participation in a common European defense policy.

A survey was carried out in 2016 among households in Amsterdam who suffered from rainfall damage in the past years. This database contains the survey response data. A paper that discusses the background, survey design and first results is published in Natural Hazards and Earth System Sciences, and also available in this dataset.Take note that additional conditions of use apply, which can be found in the file 'Creative Commons Attribution-NonCommercial 4.0 International CC BY-NC 4.pdf'.Abstract.Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Münster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Münster and Amsterdam in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people’s awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people’s experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend to include cell-phones in a CATI survey to avoid biased sampling towards certain age groups.