Skip to Content
Last modified by Hyunji Cho on 2022/05/26 12:10
From version 3.1
edited by Hyunji Cho
on 2022/05/24 14:51
Change comment: There is no comment for this version
To version 2.1
edited by Hyunji Cho
on 2022/05/24 14:49
Change comment: There is no comment for this version

Summary

Details

Page properties
Title
... ... @@ -1,1 +1,1 @@
1 -6.1. Defining cities’ targets and objectives
1 +6.1. Data management process
Content
... ... @@ -1,12 +1,14 @@
1 -**What do you wish to measure/include/improve in your City?**
1 +Large scale urban data acquisition and processing would typically need the collaboration of various stakeholders in the data life cycle. As mentioned in Chapter 2.2., Data governance in cities will operate the following data process.
2 2  
3 -The first step of the process for cities is to define the overall objectives they have and find related indicators to monitor changes in these action areas. This includes all the city’s targets, including both those related to air pollution and those related to air pollution and climate change. These initial aims can be broad and unspecific, for example, “I want to improve my city’s air quality”, “I want to take steps towards decarbonizing my city” or “I want to improve inclusion of less vocalized individuals and groups in decision-making processes for making my city more sustainable”.
3 +Alongside this data lifecycle is the data quality management which is the process of assessing the data in relation to whether it serves the purpose of the research (Lebied, 2018). This should take place at each stage of the data lifecycle (UK government Data Quality Hub, 2020). The rules for determining this will vary at each stage of data management and will be defined based on the project data requirements (Lebied, 2018).
4 4  
5 -Indicators can then be found for these objectives by filtering them by keywords.
5 +Importantly, the data being handled must be understood by all of its users at every stage of the process. The stages of this process are outlined below and can be summarised by Figure 15. It should be noted, however, that whilst this figure represents a generic data lifecycle process, each specific step will be unique according to the organisation carrying out the process and the datasets that need processing.
6 6  
7 -The framework provides:
7 +In line with the UK Government Data Quality Hub, there are 6 key stages within the lifecycle of data. (UK Government Data Quality Hub, 2020).
8 8  
9 -* A tool for filtering the indicators related to the objectives/ intended impacts of the project.
10 -* T3.1 has a framework for the co-creation process, from which we can filter the data management related actions, and phase and sequence them.
11 11  
12 -
10 +[[image:image-20220524154942-1.png]]
11 +
12 +Figure 16: Generic stages of a data lifecycle. Taken from UK Government Data Quality Hub, 2020.
13 +
14 +The stages of this process are outlined in greater detail throughout the remainder of this section.