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The application of principles of good governance in brownfield regeneration, for instance through improved transparency and participation of various groups of stakeholders, varies between regions and cities. In this article, we approach good governance as a strategic response of actors in the struggle for creating development opportunities on brownfield land. Good governance has been mostly seen as a normative consideration, but it is not clear why regions with lower development prospects would employ it more than better developed regions, as it recently happened in the Czech Republic. We assume that the public administration at the regional and municipal level plays an active role in devising strategies to attract investors for brownfield redevelopment. This process brings public administrations in interaction with each other and with investors, regulators and civil society groups within a society-wide brownfield redevelopment field. This field is an arena where all these different actors struggle for redeveloping their brownfield land. Regional and municipal administrations from developed regions stand to benefit from their higher economic growth potential and hence have a dominant position within the field. We identify the latter as the incumbents or "power-holders" of the national brownfield regeneration field. Less developed regions have lower attractiveness for brownfield redevelopment, which places them in a subordinate position in the field. They are so-called challengers that are likely to favour alternative strategies for their brownfields, going beyond mere economic attractiveness. By comparing differently developed regions and regional capitals in the Czech Republic, we show how some challengers use good governance, such as responsiveness, participation and transparency, as an alternative strategy to attract investors despite their economic predicament. For regional capitals, however, good governance is practiced both by highly developed and less developed cities. We draw evidence from interviews with key stakeholders and socioeconomic data at the regional and municipal level in the Czech Republic. In the conclusion, we show some of the identified limitations in good governance, such as obstacles to participation, responsiveness or transparency, and how they can be recognized and overcome.
Purpose The purpose of this paper is to propose the platform for effective transformation of points of interests (POIs) into augmented reality (AR), specifically into the three major software tools – Junaio, Layar and Wikitude. The objective is to facilitate the creation of POIs for common users of these programs and, thus, encourage the general public to participate in the formation of a new concept of applications using AR and location-based services. Design/methodology/approach The subject of this study was analysis of methods used for POI dynamisation under the context of location-based services. This paper suggests methodology based on database format transformation. It is focused on the creation of platform for automated geotagged POI transformation into AR. Findings The research results in prototype of online platform which is capable to automatically transform geotagged POI to three major AR applications. It discusses also the model implementation of this platform in Czech national tourist authority. Research limitations/implications The paper presents a proof-of-concept of dynamisation and transformation of an unspecified number of POIs stored in a simple table database and their transformation into the AR. Practical implications Services of AR are brought for the masses to effectively dynamise tourist information. Social implications Results could make the process of multimedialising data (POIs) more suitable for masses. Originality/value This paper presents a proof-of-concept of dynamisation and transformation of an unspecified number of POIs stored in a simple table database and their transfer into the three major AR applications.
The chapter gives an account of both opportunities and challenges of human–machine collaboration in citizen science. In the age of big data, scientists are facing the overwhelming task of analysing massive amounts of data, and machine learning techniques are becoming a possible solution. Human and artificial intelligence can be recombined in citizen science in numerous ways. For example, citizen scientists can be involved in training machine learning algorithms in such a way that they perform certain tasks such as image recognition. To illustrate the possible applications in different areas, we discuss example projects of human–machine cooperation with regard to their underlying concepts of learning. The use of machine learning techniques creates lots of opportunities, such as reducing the time of classification and scaling expert decision-making to large data sets. However, algorithms often remain black boxes and data biases are not visible at first glance. Addressing the lack of transparency both in terms of machine action and in handling user-generated data, the chapter discusses how machine learning is actually compatible with the idea of active citizenship and what conditions need to be met in order to move forward – both in citizen science and beyond.
Issues related to the evolving role of citizen science and open science are reviewed and discussed in this article. We focus on the changing approaches to science, research and development related to the turn to openness and transparency, which has made science more open and inclusive, even for non-researchers. Reproducible and collaborative research, which is driven by the open access principles, involves citizens in many research fields. The article shows how international support is pushing citizen science forward, and how citizens’ involvement is becoming more important. A basic scientometric analysis (based on the Web of Science Core Collection as the source of peer reviewed articles) provides a first insight into the diffusion of the citizen science concept in the field of Geography, mapping the growth of citizen science articles over time, the spectrum of geographical journals that publish them, and their citation rate compared to other scientific disciplines. The authors also discuss future challenges of citizen science and its potential, which for the time being seems to be not fully utilized in some fields, including geographical research.
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