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Auflistung nach Schlagwort "Citizen Science"

1 - 8 von 8
  • Konferenzbeitrag
    CareConnection – A Digital Caring Community Platform to Overcome Barriers of Asking for, Accepting and Giving Help
    (Mensch und Computer 2023 - Tagungsband, 2023) Aal, Tanja; Ruhl, Andrea; Kohler, Erich; Choudhary, Apurva; Bhandari, Pragya; Devbhankar, Namrata; Egli, Silvia; Shkumbin, Gashi; Kaspar, Heidi; Spittel, Madlen; Kirschsieper, Dennis; Müller, Claudia
    Many people would like to remain in their familiar surroundings in old age, even if they need certain forms of assistance. But what exactly does everyday life look like, where are the hurdles and where can community-based support options start? The results of a citizen-based participatory interview study of community members of a rural Living Lab near Zurich, Switzerland and full-time researchers from two universities in Switzerland and Germany explore these questions. Results of the study relate to physical limitations and potentials in old age, aspects of well-being and mental health, social engagement, relationships and networks, as well as the theme of ‘asking for help, accepting help and giving help’. Against the background of a key category, the barriers of ‘asking for, accepting and giving help’, an overarching reflection by the co-researchers and full-time researchers took place. This focus provided the basis for the participatory development of CareConnection, a digital community platform design that fosters social exchange and helps to overcome identified barriers, which can be physical, mental or social and within these categories temporal, spatial, structural and/or individual and thus enable or promote social encounters and interaction to establish a higher level of well-being and health.
  • Textdokument
    Designing an ethical technology project with the help of Data Feminism
    (SKILL 2021, 2021) Gleißner, Lea-Kathrin; Bui, Magdalena; Kühn, Fey; Nenninger, Amelie
    Algorithms and new technologies help people in several life situations, but society pays a high price for their advantages. Several scandals occurred recently, showing that algorithms are neither neutral nor fair – quite the contrary: They discriminate people as humans do. One approach to create less biased data science projects is the “Data Feminism” method, presented by Catherine D’Ignazio and Lauren F. Klein in their book of the same title. This paper evaluates how feasible the method can be implemented in student projects based on the experiences four Leipzig students made by trying to implement the method into their project ‘Questioning Street Names Leipzig’. The paper focusses on three main concepts: subjective viewpoints and context, crediting all forms of labour, and building and linking communities through public tagging events, thus opening the academic question for some citizen science help. The project utilizes open data and open data sources such as Wikidata and OpenStreetMap. The authors of “Data Feminism” want to encourage students, as well as academic professionals, to think about their bias in their data and to use the data feminism approach to reduce the impact of them and create more ethical computer science projects.
  • Konferenzbeitrag
    Digitale Innovationen von Bürgern für Bürger - Design Thinking oder Citizen Science?
    (UP 2016, 2016) Koch, Matthias; Heß, Steffen; Heß, Anne; Magin, Dominik Pascal
    Der vorliegende Beitrag beschreibt einen partizipativen Ansatz zur Entwicklung von digitalen Diensten für ländliche Regionen. Im Projekt „Digitale Dörfer“ realisiert das Projektteam gemeinsam mit den Einwohnern von drei Verbandsgemeinden in Rheinland-Pfalz verschiedene Mitmachszenarien zur Stärkung des Wir-Gefühls innerhalb der Gemeinschaft und zur Verbesserung der Nahversorgung durch örtlich ansässige Händler. In zwei Testphasen wurde ein regionaler Online-Marktplatz mit Apps zur Lieferung bestellter Waren durch Freiwillige erprobt. Hier hat sich beispielsweise gezeigt, dass Freiwillige bereit sind bis zu fünf Minuten Umweg für die Zustellung einer Lieferung in Kauf zu nehmen. In den Testphasen konnten darüber hinaus alle Lieferungen ohne Beanstandung dem Empfänger übergeben werden, was auf eine große Sorgfaltspflicht der Freiwilligen schließen lässt. Die Erprobung des so genannten Mitmachszenarios wies auf der einen Seite Erfolge auf, offenbarte zugleich aber auch die Notwendigkeit, weitergehende Konzepte in das entstehende Ökosystem einzubinden um die Attraktivität des Systems zu steigern. Auf die Frage, ob es sich bei dem gewählten Ansatz um Design Thinking, Citizen Science oder doch beides zugleich handelt wird am Ende des Beitrags eingegangen.
  • Textdokument
    Environmental Wellbeing through Guerilla Sensing
    (INFORMATIK 2021, 2021) Banse, Marvin Banse; Schmalriede, Florian; Theel, Oliver; Winter, Andreas
    All over the world, individuals, companies, and institutions are exploiting the environment to gain an advantage for themselves. The damage to the environment affects people’s health and environmental wellbeeing. By Guerilla Sensing, we provide a platform to detect, spotlight, and monitor environmental pollution, that allows citizen to trigger a closed control loop and react to this exploitation by providing data reflecting the current environmental situation. it consists of an adaptive network of low-cost sensor nodes connected to an extensible platform, enabling complex analyses and detailed notifications. Guerilla Sensing can be used by citizens without any deep knowledge in measurements or computer science. The paper introduces the approach and the components of this platform. Applied to environmental parameters such as radiation and particulate matter, Guerilla Sensing is exemplarily evaluated.
  • Workshopbeitrag
    Leveraging Digital Citizen Science for Research Problem Discovery: Insights from a Home Office Challenge Participatory
    (Mensch und Computer 2022 - Workshopband, 2022) Gau, Michael; Greif-Winzrieth, Anke; Maedche, Alexander
    Design-oriented research typically involves some kind of research problem discovery activity in order to identify and understand the problem space. Researchers can apply different methods to explore the problem space, for instance, interviews or focus groups. However, these methods are time consuming and do not scale well. Especially when it comes to discovering socially relevant realworld problems they require access to the general public to reach domain experts that is often difficult to achieve for researchers. Citizen science offers a promising approach for research problem discovery by actively involving citizens into the scientific inquiry to access knowledge on a large scale. In this paper, we report on a participatory action following a digital citizen science approach by specifically exploring the topic "home office" and corresponding challenges along four different subtopics. We report on (1) our approach and process to involve citizens in the problem discovery phase, (2) the implementation of the process in theweb-based digital citizen science application MyResearchChallenge to enable citizens to register, collect, discuss, and vote challenges, and (3) provide a summary on the collected challenges.
  • Konferenzbeitrag
    Maschinelle Bilderkennung von Phänophasen bei Pflanzen
    (INFORMATIK 2024, 2024) Seegert, Tim; Schulze, Paul; Fuchs-Kittowski, Frank
    Die Phänologie von Pflanzen steht im direkten Zusammenhang mit klimatischen Bedingungen in Ökosystemen und kann helfen, die Auswirkungen des Klimawandels zu erkennen. Es besteht ein Bedarf an der Entwicklung von automatischen Methoden zur Erkennung von Phänophasen, um diese mittels Crowdsourcing erheben zu können. Ziel dieses Beitrags ist es, ein ML-Modell zu entwickeln, das in eine mobile Anwendung integriert werden kann, um phänologische Phasen automatisch zu erkennen. Hierfür wurden Anforderungen an phänologisches Bildmaterial definiert und verschiedene Bilddatenbanken als Datengrundlage untersucht. Drei verschiedene CNN-Modelle wurden für die Pflanzen Mais und Soja erstellt, die vier verschiedene phänologische Phasen eines Feldes unterscheiden können. Die entwickelten Modelle erreichten bei den Metriken „recall“, „precision“, „accuracy“ jeweils mindestens 90 % für Soja und Mais. Ein stichprobenhafter Test mit Nahaufnahmen führte zu falschen Klassifikationen. Mittels TensorFlow Lite konnte das Modell in mobile Anwendungen integriert werden. Für eine praktische Nutzung sind weitere Bilder von phänologischen Phasen (insbesondere Nahaufnahmen) zu berücksichtigen.
  • Konferenzbeitrag
    Smart Citizen Science in pluvial flood disaster risk reduction: Building a Smart Application as one tool for local drain path identification (Work in progress)
    (EnviroInfo 2022, 2022) Haupenthal, Katharina; Fischer-Stabel, Peter
    Over the last years, flood risk has increased, and the threat of flooding has caused severe damages for economy, society and infrastructure. Hence, the project Urban Flood Resilience- Smart Tools (FloReST) was initiated by six partners from the field of civil engineering, informatics and hydrology to research on tools for high-resolution drain path identification and risk mapping. In this context, a mobile application shall be developed for crowdsourced data collection in civil society. Still being in the early stages of development, a first requirement catalogue for the application is presented and discussed, showing that especially data control is a problematic issue in Citizen Science.
  • Textdokument
    Software solutions for form-based, mobile data collection – A comparative evaluation
    (BTW 2019 – Workshopband, 2019) Steinberg, Markus; Schindler, Sirko; Klan, Friederike
    Many citizen science projects rely on their contributors going to the field and collecting data. Due to their wide availability and increasing capability, modern mobile devices have become an indispensable tool to ease the collection process. Projects can publish mobile apps, that allow contributors to easily collect data and submit their results. The requirements of individual projects oftentimes overlap to a large extent, which triggered the development of multiple generic frameworks. They allow new projects to quickly generate customized apps and reuse existing infrastructure. However, the wide landscape of tools with diverging capabilities requires projects to compare and choose. This report supports data managers in making an informed decision. We report on our experiences primarily on the whole data collection workflow starting from setting up your own instance to finally analyzing the retrieved data. We compare eight tools – both free and commercial – according to the features provided and difficulties encountered.