Wiki source code of 2. Guideline for building inclusive data
Version 1.1 by Hyunji Cho on 2022/07/04 14:29
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1.1 | 1 | An important aim of the DivAirCity project is its acknowledgement and attempt to address data gaps where marginalised groups of people are concerned. It impacts the capacity of data to address equal participation and accessibility at which the DivAirCity project aims. |
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| 3 | Apart from the operation of the data framework in a general manner, the DivAirCity project needs to pay particular attention to building inclusive data. Inclusive data is to ensure that everyone is counted in evidence, and no one is forgotten. This is key to eliminating discrimination on the basis of personal characteristics such as disability, ethnicity, or gender and to accelerating global efforts towards inclusive programming. | ||
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| 5 | Greater concerns regarding biased data and the lack of visibility of diverse groups in data (or big data) started to be raised in recent years (Hand, 2020; Perez, 2019). Still, not many data processing practices include this aspect. This section specifically addresses the key points to consider in order to provide the methods for inclusive data processing. |
