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| dcc:pdpsol:dataminimization [2026/04/29 13:36] – marlon | dcc:pdpsol:dataminimization [2026/06/11 08:47] (current) – alba | ||
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| - | ====== Data Minimization | + | ====== Data minimization |
| ===== Introduction ===== | ===== Introduction ===== | ||
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| ** | ** | ||
| - | When designing your research, | + | When designing your research, |
| ===== General data minimization practices ===== | ===== General data minimization practices ===== | ||
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| This concept is also relevant if you use certain variables as an **independent variable** in your research. For example, if you want to collect location data, it is often unnecessary to know someone’s exact address or neighbourhood to answer a research question. For example, if the goal is to compare happiness within different regions in a country, broader categories such as rural versus urban areas may be sufficient. However, in some situations, it might be necessary to collect more detailed or high-granularity data. For example, if the research is about neighbourhood connections, | This concept is also relevant if you use certain variables as an **independent variable** in your research. For example, if you want to collect location data, it is often unnecessary to know someone’s exact address or neighbourhood to answer a research question. For example, if the goal is to compare happiness within different regions in a country, broader categories such as rural versus urban areas may be sufficient. However, in some situations, it might be necessary to collect more detailed or high-granularity data. For example, if the research is about neighbourhood connections, | ||
| - | ==== Take into account the effort of research participation | + | === Take into account the effort of research participation === |
| Although it is important to consider what personal data you need for your research, it is also important to be mindful of the effort and strain participation may place on your participants. This means you should limit the collection of personal data to what you need for your research. However, you should also respect participants’ time and effort, and avoid designing studies that require participants to take part multiple times due to narrowly defined research questions. This is particularly important when working with vulnerable or hard-to-reach groups. In such cases, it is advisable to design studies that can address several relevant questions at once, thereby maximizing the value of participants’ contributions while minimizing their strain. | Although it is important to consider what personal data you need for your research, it is also important to be mindful of the effort and strain participation may place on your participants. This means you should limit the collection of personal data to what you need for your research. However, you should also respect participants’ time and effort, and avoid designing studies that require participants to take part multiple times due to narrowly defined research questions. This is particularly important when working with vulnerable or hard-to-reach groups. In such cases, it is advisable to design studies that can address several relevant questions at once, thereby maximizing the value of participants’ contributions while minimizing their strain. | ||
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| + | A research ethics committee can provide feedback on your study design. When working with participants, | ||
| ==== Use consistent file naming and version control ==== | ==== Use consistent file naming and version control ==== | ||
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| Some data can reveal more information about an individual than others. Only use an extensive or detailed data collection method if you also use this type of data to answer your research question. | Some data can reveal more information about an individual than others. Only use an extensive or detailed data collection method if you also use this type of data to answer your research question. | ||
| * **Video**: Observational research focusing on human interactions, | * **Video**: Observational research focusing on human interactions, | ||
| - | * **Audio**: | + | * **Audio**: |
| - | * **Text**: Structured qualitative research focusing on content (e.g. interviews, | + | * **Text**: Structured qualitative research focusing on content (e.g. interviews, |
| ===Contact information=== | ===Contact information=== | ||
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| ===Metadata=== | ===Metadata=== | ||
| Photo, video or audio files might contain a timestamp, date and, depending on the equipment and settings, also location. Check whether you can prevent the collection of these data or remove these metadata as soon as possible after collection. [[https:// | Photo, video or audio files might contain a timestamp, date and, depending on the equipment and settings, also location. Check whether you can prevent the collection of these data or remove these metadata as soon as possible after collection. [[https:// | ||
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| + | === Digital traces === | ||
| + | Be aware that bringing a device to an interview can, by itself, generate digital traces. If your phone is on, it may record GPS coordinates, | ||
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| + | If you plan on doing interviews with participants, | ||
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| ===Contact information=== | ===Contact information=== | ||
| - | Do not collect contact information if you do not plan to contact your participants after you have collected the data (e.g. in case of recruitment via social media, posters or third parties). The [[https:// | + | Do not collect contact information if you do not plan to contact your participants after you have collected the data (e.g. in case of recruitment via social media, posters or third parties). The [[https:// |
| === Informed Consent === | === Informed Consent === | ||
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| ==== Social media data ==== | ==== Social media data ==== | ||
| ===Data collection method=== | ===Data collection method=== | ||
| - | As a researcher, you can reduce the amount of personal data you collect when conducting social media research by carefully selecting your data collection method. Here are three common research approaches, with practical tips for each: | + | As a researcher, you can reduce the amount of personal data you collect when conducting social media research by carefully selecting your data collection method. Here are two common research approaches, with practical tips for each: |
| * **Social media data scraping** is the automated collection of user-generated content and metadata from platforms like X (Formerly Twitter) and YouTube for systematic analysis. Make sure you limit the variables you collect during scraping and define clear filters to your range (e.g. keywords and date range). Consider taking a sample and not scraping all the data that falls within this range. | * **Social media data scraping** is the automated collection of user-generated content and metadata from platforms like X (Formerly Twitter) and YouTube for systematic analysis. Make sure you limit the variables you collect during scraping and define clear filters to your range (e.g. keywords and date range). Consider taking a sample and not scraping all the data that falls within this range. | ||
| - | | + | * **Manual data collection and observation** make it possible to carefully design your data collection and easily prevent the collection of identifiable data. You can determine what data you collect and are less dependent on API. Examples of good practices: 1) Make sure not to collect any usernames or store them separately |
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