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- W3048475618 abstract "Drawing on an engaged research project (Milan & Milan, 2016) the presentation discusses a case of civic data hacking in Colombia—The Data Week—through the framework of data activism (Milan & Gutiarrez, 2015; Shrock, 2016) and critical (digital) citizenship (Isin & Ruppert, 2015). The Data Week is a periodic event organized by citizens that functions as both a hackathon and a workshop, as it is oriented mainly towards learning (open to non-technical expert publics). On one hand, the Data Week is an interesting case of experimentation with the hackathon form since its scope goes beyond the short-term goals of the traditional hackathon—producing a prototype or technical solution for a single problem in a short time. The Data Week in its different iterations has aimed mainly at fostering a community of people interested in the civic possibilities of data that works around multiple issues and emphasizes processes over solutions (D'Ignazio et al., 2016)—though coding is also a goal in itself, it is mainly a means. On the other hand, it represents an instance of critical citizenship as it adopts a set of politically motivated technical principles aiming at citizen empowerment: the adoption of moldable tools, pocket infrastructures and frictionless data, that is, small-scale technology that can adapt to people's needs and capacities in the Global South in order to overcome infrastructural limitations to civic engagement through data and the Big Data divide (Andrejevic, 2014). We will present one of their works concerning the opening up and visualization of public budget and spending data and describe how participants communicated with and questioned public institutions repurposing the hackathon form as an advocacy platform." @default.
- W3048475618 created "2020-08-18" @default.
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- W3048475618 date "2017-01-01" @default.
- W3048475618 modified "2023-09-23" @default.
- W3048475618 title "Making small talk about small data: A case study of civic data hacking in Colombia" @default.
- W3048475618 doi "https://doi.org/10.22215/datapower.v2017i0.127" @default.
- W3048475618 hasPublicationYear "2017" @default.
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