The Future of Cities

This report is an initiative of the Joint Research Centre (JRC), the science and knowledge service of the European Commission (EC), and supported by the Commission's Directorate-General for Regional and Urban Policy (DG REGIO). It highlights drivers shaping the urban future, identifying both the key challenges cities will have to address and the strengths they can capitalise on to proactively build their desired futures. The main aim of this report is to raise open questions and steer discussions on what the future of cities can, and should be, both within the science and policymaker communities. While addressing mainly European cities, examples from other world regions are also given since many challenges and solutions have a global relevance. The report is particularly novel in two ways. First, it was developed in an inclusive manner – close collaboration with the EC’s Community of Practice on Cities (CoP-CITIES) provided insights from the broader research community and city networks, including individual municipalities, as well as Commission services and international organisations. It was also extensively reviewed by an Editorial Board. Secondly, the report is supported by an online ‘living’ platform which will host future updates, including additional analyses, discussions, case studies, comments and interactive maps that go beyond the scope of the current version of the report. Steered by the JRC, the platform will offer a permanent virtual space to the research, practice and policymaking community for sharing and accumulating knowledge on the future of cities. This report is produced in the framework of the EC Knowledge Centre for Territorial Policies and is part of a wider series of flagship Science for Policy reports by the JRC, investigating future perspectives concerning Artificial Intelligence, the Future of Road Transport, Resilience, Cybersecurity and Fairness Interactive online platform : https://urban.jrc.ec.europa.eu/thefutureofcitiesJRC.B.3-Territorial Developmen

Spatial information in European agricultural data management. Requirements and interoperability supported by a domain model

Data compatibility and system interoperability are fundamental for crosswalks and collaboration between domains. The most frequently used references for information sharing are time and location. In order to understand the requirements, fundamental processes, and core information concepts of a domain, a comprehensive, but standardised documentation is needed. In spatial data infrastructures models presented in Unified Modelling Language (UML) are widely used to facilitate the uptake of standards and valorise best practices of various communities. The European agricultural decision makers must deal with many components described in the Common Agricultural Policy (CAP) in order to optimize data integration and achieve transparency. Geospatial information plays a key role in the implementation of this policy, which comprises the establishment and maintenance of the Integrated Administration and Control System (IACS). In the past the IACS of the MS has principally served a single high level business case: to run a correct administration of the CAP. However, the recent reform and the synergies with environmental and societal policies create increasing expectations for IACS, which impact upon system interoperability and data usability. These objectives can be achieved by establishing a framework that is standard based, allows flexible extensions, and that supports efficient implementation and information exchange between the stakeholders. This paper presents the development process and describes the structure of a domain model we propose for IACS. This standard driven model was designed to translate requirements into technical elements, ensuring interoperability, and providing flexible extensions at the same time. For this purpose we set-up a formal requirement model, formalized use cases, and integrated ISO/TC 211 and INSPIRE UML based class diagrams. As such, this paper proposes a methodology to help guide how the policy can be implemented. The importance of traceability from IACS and third party business rules to the information concepts was proven by simulation runs. The developed modelling approach yielded a reference for conformance testing, indicated critical points of potential errors, and highlighted the impact of eventual changes. Storing all concepts and implementation options of IACS in a unique framework helps to eliminate redundant efforts, provides a strong basis for developing various applications, underpins interoperability with other domains and enhances transparency of the CAP.JRC.H.4-Monitoring Agricultural Resource

Conformance testing of geographic information. A case study on the Land Parcel Identification System

According to ISO 19105 “Geographic information – Conformance and testing” standard, conformance assessment is based on abstract and executable test cases that are hierarchically organised into test modules and test suites. This standard specifies a conformance testing framework and criteria to be used when claiming conformance to the family of ISO geographic information standards. In this paper we explain the conformance and testing challenges for Land Parcel Identification System (LPIS), which has to meet not only the technical, but also legal requirements of the Common Agricultural Policy (CAP). Recognising the benefits of formal models in terms of efficiency of design, enforcements of standards and consistency of implementation, we used Geography Markup language (GML) profile of Unified Modeling Language (UML) for developing a conformance testing framework both for implementation model and data testing. The simultaneous development of the LPIS core design model with the testing model and the tracing relationships helped us to arrive to a compact, yet detailed model, where workflows and users’ interactions with the information system became unambiguous. This is an asset that enables the repeatability of test verdicts, transparency of procedures and thus, trustworthiness of testing. The model based approach is also efficient for deriving documentation targeted at different users, such as quality inspectors or IT developers. The UML model also allows exporting machine-readable Extensible Markup Language Schema Definition (XSD) application schemas that we used for developing a tool for schema matching between the System Under Test (SUT) and the reference schema, the LPIS core model. With the model and standard driven approach we clarified how abstract and executable test should be applied in the LPIS testing framework and described the role of data quality measures as indicator-metrics for conformance.JRC.D.5-Food Securit

Living cost gap in the European Union member states

The living cost gap refers to the differential amongst income, expenditures, and poverty lines. It is important since it addresses a number of aspects that point towards historic and continued living standards. The purpose of this study is to identify, measure, and compare the living cost gap in the Europe Union member states. Twenty-nine indicators/criteria from Eurostat and World Bank, covering the period 2008–2017, are employed. In order to rank and compare living cost gap by countries, objective functions for each criterion are defined and applied. The importance of each criterion is assessed independently. The composite living cost gap indicator for each MS is calculated using multiple criteria decision support methods. The relationship between the compound annual growth rates of this indicator and each single criterion is estimated and evaluated. The findings of the study suggest that living cost gap is higher where unemployment rates and households’ expenditure on basic needs (housing, food etc.), are larger, while living cost gap is lower where households’ income and expenditure on optional needs are higher. The living cost gap in the majority of countries tends to narrow/decrease, along with the increase in the household income and expenditures. Our research highlights the need to mitigate unemployment and households’ low net income in order to alleviate living cost gap. The analysis and assessment of living cost gap might help identifying the most vulnerable social profiles and groups, and hence might contribute to the adequate formulation and implementation of targeted policy responses and interventions at European Union, national, and regional level.JRC.B.3-Territorial Developmen

Ageing in regions and cities: high resolution projections for Europe in 2030

This report presents an experimental exercise in which the LUISA population distribution method has been extended to break down its local population distribution outcomes by broad age class. To do so, elaborate methods have been set up to disaggregate observed age class distribution data to fine spatial resolution raster data; to account for age-class specific demographic expectations; and to model changes in population composition while constrained by LUISA’s local population results and expected age class sizes at the regional level. This report describes the developed methodology and summarizes the obtained results.JRC.B.3-Territorial Developmen

A Drive Time-Based Definition of Cross-Border Regions and Analysis of Population Trends

This study aims to add technical insights to the debate about overcoming the cross-border obstacles to growth and jobs in the EU internal border regions. It proposes new border geography by defining distinct drive time zones (30, 30-60, 60-90, 90+ minutes) to terrestrial paved border crossing points. The drive time zones are delineated by applying network analysis algorithms to the TomTom Multinet (2017) road network data, based on governing speed limits for passenger cars and assuming free-flow i.e. without congestions and/or border crossing delays. Paved bridges and river ferries are also included. At the next stage, the study looks at the population changes during the period 2001-2011 in the adjacent to the borders "30 minutes" drive time zones and compares these changes with the respective country population trends . The analysis encompasses thirty one couples of EU border areas and three complex border regions, where more than two EU border areas are included. The analysis is executed in the context of the Knowledge Centre for Territorial Policies (KCTP) of the European Commission.JRC.B.3-Territorial Developmen