Suchergebnisse

The goal of the paper is to expose the pillars of urban digital infrastructure and their role in the development of smart and data driven applications in the e2e model. Today, no one contests the need for a general-purpose infrastructure in the city that improves the quality of life with respect to various types of socio-economic activity of residents. However, the digital aspect of fostering this kind of activity is linked to a very dynamic and ubiquitous element of technology, and the quality and stability of solutions based on advanced technology is a key parameter of the quality of life and development that a city should provide to its residents. This pace of technology development means that our environment (including cities) are subject to a process of continuous digital transformation. Starting from examples of such transformation and top-trends in technology development, we focus on transformation pillars that can ensure sustainable growth of innovation supply in a city. We give three examples of platforms designed for City of Poznan. We conclude that a key factor benefiting this multidimensional transformation process is the provision of an open, data-transmission and processing infrastructure with the support of which all smart city stakeholders can pursue their social, scientific, economic, or political goals in a sustainable manner.

Digital libraries are nowadays expected to contain more than books and articles. All relevant sources of information for a scholar should be available, including research data. However, does literature retrieval work for data sets as well? In the context of a requirement analysis of a data catalogue for quantitative Social Science research data, we tried to find answers to this question. We conducted two user studies with a total of 53 participants and found similarities and important differences in the users' needs when searching for data sets in comparison to those already known in literature search. In particular, quantity and quality of metadata are far more important in data set search than in literature search, where convenience is most important. In this paper, we present the methodology of these two user studies, their results and challenges for data set retrieval system that can be derived thereof. One of our key findings is that for empirical social scientists, the choice of research data is more relevant than the choice of literature; therefore they are willing to put more effort into the retrieval process. Due to our choice of use case, our initial findings are limited to the field of Social Sciences. However, because of the similar characteristics for data sets also in other research areas, such as Economics, we assume that our results are applicable for them as well.