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dc.contributor.authorSteinberg, Markus
dc.contributor.authorSchindler, Sirko
dc.contributor.authorKlan, Friederike
dc.contributor.editorMeyer, Holger
dc.contributor.editorRitter, Norbert
dc.contributor.editorThor, Andreas
dc.contributor.editorNicklas, Daniela
dc.contributor.editorHeuer, Andreas
dc.contributor.editorKlettke, Meike
dc.date.accessioned2019-04-15T11:40:30Z
dc.date.available2019-04-15T11:40:30Z
dc.date.issued2019
dc.identifier.isbn978-3-88579-684-8
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/21800
dc.description.abstractMany 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.en
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofBTW 2019 – Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) – Proceedings, Volume P-290
dc.subjectData collection
dc.subjectCitizen Science
dc.subjectMobile Software
dc.subjectWeb Applications
dc.titleSoftware solutions for form-based, mobile data collection – A comparative evaluationen
mci.reference.pages135-144
mci.conference.sessiontitleWorkshop on Big (and Small) Data in Science and Humanities (BigDS 2019)
mci.conference.locationRostock
mci.conference.date4.-8. März 2019
dc.identifier.doi10.18420/btw2019-ws-14


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