From the course: Data Rights Foundations

Data elements

From the course: Data Rights Foundations

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Data elements

- [Instructor] When we talk about data, exactly what are we talking about? So there may be personalized fields, such as name and address, as well as personal financial information, such as bank or credit card details. In the age of big data, there may be recorded phone conversations, recorded videos, and due to smart devices, biometric, behavioral, and physical data elements may be tracked and used for purposes outside of an individual's control. All of these elements may be recorded and stored either on the device or stored in a cloud service. In addition to these types of personal data, there may also be metadata, which is extracted non-personal information that can give an indication of different behaviors. So what this actually means is sort of a layer above personal data. So it describes what's been happening. So instead of a specific phone call, it may be information about the time and the duration of a phone call. It could be information regarding a combination of purchased products. So not the specific list, but a general category about what was purchased. It may be the number of different locations that have been visited while traveling. It may be the average usage of a product over a period of time. It could be generalized spend information from online websites. As mentioned previously with the government health example, the data may appear to be anonymous, but there's a number of instances where it can be used to map directly back to an individual's identity. When it comes to personal data as well, a large amount of it can be picked up in a second hand manner, meaning a second or third party may record and store data on their services. And this might make it quite difficult for an individual to actually, well, first of all, know that our data's being stored by another party and actually access it or change that data. One example might be if your face has ever been tagged in a Facebook photo. Although the tags can be removed, the tagging metadata is still available to Facebook and it can be used for image recognition and other training purposes. Once that data's been incorporated into predictive models, it might be difficult to actually extract that contribution from that system. In addition, data can also be stored from public sources. So if private sources are personal, web accounts or mobile phone usage, public sources might be if you've been recorded in a public area. So a number of different cities have CCTV cameras and then they may use these cameras to record how many people walk past different areas to provide traffic statistics, or information on how to improve the city or town planning. Although this data is aggregated and not provided at a personal level, these numbers have been generated by using a combination of a number of individuals. So it may be possible to get trends or understand individual behavior based on these aggregates.

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