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Big data

Big data is a massive volume of data that is so large that it's difficult to process using traditional database and software techniques. Technologies made to process these large data sets are aiming to obtain new information for enhanced insight, decision making and process control.

Ethics in big data

Companies and government agencies are collecting information about you everywhere they can and in many cases without telling it to you. If they tell it they still don't usually tell you what exactly is collected and what they are exactly doing with it. Probably in many cases they don't even know it themselves because of the nature of the big data. They assume it will be useful in the future in the some way or the another.

Cheap storage space enables the possibility of storing all collected data virtually forever. Data processing techniques are constantly developing and in the future sensitive information about you can be extracted from the data in the ways now impossible. In untrustworthy hands collected information can be used against you especially if you are in the position of influence.

Data collection should be done in transparent ways and if possible the subject of it should have some power about it. In many cases data collection shouldn't be done at all if it doesn't benefit the subject. There are many ethical issues concerning big data but because of the great benefits of it those are often ignored.

References

Demchenko, Y., Membrey, P., Defining Architecture Components of the Big Data Ecosystem, 2014, 2014 IEEE International Conference on Collaboration Technologies and Systems (CTS)

Zheng, Z., Zhu, J., Lyu, M., Service-generated Big Data and Big Data-as-a-Service: An Overview, 2013, 2013 IEEE International Congress on Big Data

Zhang, D., Inconsistencies in Big Data, 2013, 2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

Exam questions

1. What makes an good argument?

For starters the question which makes students to think some of the key factors of critical thinking.

2. Compare big data and open data. Explain possible differences and similarities.

This question makes students to think and explain the meaning of these terms needed later.

3. How and why big data can change lives of ordinary people? Give three examples.

After the exploration of the key terms follows two critical thinking exercise. In this one students have to think how big data might affect society.

4. How opening data benefits governments?

This question covers open data topic widely and forces students to think relationships between open data providers and companies using it.

Coursera diploma

sipila_coursera_2015.pdf