Citizens around the world are changing their urban environment through bottom-up projects. They are increasingly using digital platforms to come together. From the perspective of smart city research, this form of participation and interaction with city administrations has not yet been researched and defined. In our study we suggest a conceptualisation of bottomup urbanism participatory platforms and analysed 143 platforms. We identified 23 platforms as our study sample. They vary in their focus from implementation to funding or discussion. Therefor we found a broad range of participation mechanisms. A wide range of employment or voluntary work of staff members was shown. A heterogeneous picture also emerged regarding other characteristics (e.g. funding size, users or number of projects). One thing they have in common is their good cooperation with cities and regional actors.
Information extraction can support novel and effective access paths for digital libraries. Nevertheless, designing reliable extraction workflows can be cost-intensive in practice. On the one hand, suitable extraction methods rely on domain-specific training data. On the other hand, unsupervised and open extraction methods usually produce not-canonicalized extraction results. This paper is an extension of our original work and tackles the question of how digital libraries can handle such extractions and whether their quality is sufficient in practice. We focus on unsupervised extraction workflows by analyzing them in case studies in the domains of encyclopedias (Wikipedia), Pharmacy, and Political Sciences. As an extension, we analyze the extractions in more detail, verify our findings on a second extraction method, discuss another canonicalizing method, and give an outlook on how non-English texts can be handled. Therefore, we report on opportunities and limitations. Finally, we discuss best practices for unsupervised extraction workflows.
Information extraction can support novel and effective access paths for digital libraries. Nevertheless, designing reliable extraction workflows can be cost-intensive in practice. On the one hand, suitable extraction methods rely on domain-specific training data. On the other hand, unsupervised and open extraction methods usually produce not-canonicalized extraction results. This paper tackles the question how digital libraries can handle such extractions and if their quality is sufficient in practice. We focus on unsupervised extraction workflows by analyzing them in case studies in the domains of encyclopedias (Wikipedia), pharmacy and political sciences. We report on opportunities and limitations. Finally we discuss best practices for unsupervised extraction workflows.
Knowledge bases allow effective access paths in digital libraries.Here users can specify their information need as graph patterns for precise searches and structured overviews (by allowing variables in queries). But especially when considering textual sources that contain narrative information, i.e., short stories of interest, harvesting statements from them to construct knowledge bases may be a serious threat to the statements' validity. A piece of information, originally stated in a coherent line of arguments, could be used in a knowledge base query processing without considering its vital context conditions. And this can lead to invalid results. That is why we argue to move towards narrative information access by considering contexts in the query processing step. In this way digital libraries can allow users to query for narrative information and supply them with valid answers. In this paper we define narrative information access, demonstrate its benefits for Covid 19 related questions, and argue on the generalizability for other domains such as political sciences.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.