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Collection of amino acids and DNA from fingerprints using hydrogels

Representation of good care in (photo)-stories

Humans use metaphors in thinking. Most metaphors are visual. In processing information stimuli the mind depends partly on visual codes. Information is processed and stored through two channels: one for non-verbal information and another for verbal information. The two different areas of information in the brain are interconnected. The information is stored in patterns that form an inner representation of how individuals perceive their reality and their self. The active processing of new information, remembering and the self-image are related phenomena, that influence each other, sometimes leading to biased interpretation or even reconstruction of contents in each of these areas. Imagination, expectations and anticipations of the future and memories are the more active manifestations of this process. In this process mimesis plays an important role. Mimesis is the imitation of reality in play, story-telling or creating images of how things should look like in the future. Through mimesis people can anticipate on roles in social life, or appropriate experiences from someone else and relate them to one’s own life story. When this happens the information is related to the self through processes of association and becomes ‘Erfahrung’.

Doing Research Online (How-to Guides)

Locative mapping with smartphones is the process of collecting geo data using mobile applications that tells something about a place, based on user input. Results are typically visualized using maps. Usually when such data is collected, the researcher is interested in more than just the location of a person. Perhaps the researcher would like to ask some questions, add a photo or make a voice recording. Questions such as what types of data you want to collect and with whom greatly influence how to design this data collection process. In this HowTo we aim to guide you through such a process and help you make the best decision what software is best for your project. We further elaborate on how such a data collection process can be paired with participatory methods to get a deeper level of understanding of the data collected.

The Urban Belonging Photo App: A toolkit for studying place attachments with digital and participatory methods

This paper introduces the open-source Urban Belonging (UB) toolkit, designed to study place attachments through a combined digital, visual and participatory methodology that foregrounds lived experience. The core of the toolkit is the photovoice UB App, which prompts participants to document urban experiences as digital data by taking pictures of the city, annotating them, and reacting to others’ photos. The toolkit also includes an API interface and a set of scripts for converting data into visualizations and elicitation devices. The paper first describes how the app’s design specifications were co-created in a process that brought in voices from different research fields, planners from Gehl Architects, six marginalized communities, and citizen engagement professionals. Their inputs shaped decisions about what data collection the app makes possible, and how it mitigates issues of privacy and visual and spatial literacy to make the app as inclusive as possible. We document how design criteria were translated into app features, and we demonstrate how this opens new empirical opportunities for community engagement through examples of its use in the Urban Belonging project in Copenhagen. While the focus on photo capture animates participants to document experiences in a personal and situated way, metadata such as location and sentiment invites for quali-quantitative analysis of both macro trends and local contexts of people’s experiences. Further, the granularity of data makes both a demographic and post-demographic analysis possible, providing empirical ground for exploring what people have in common in what they photograph and where they walk. And, by inviting participants to react to others’ photos, the app offers a heterogeneous empirical ground, showing us how people see the city differently. We end the paper by discussing remaining challenges in the tool and provide a short guide for using it.