Critical thinking2: Open Data Now

Seminar group

Seminar days

Day 1 - 19.2. 12.30-15.30 room 4510

Book: Big data (whole book)

Presenters (students should add these here)

Day 2 - 13.3. 8.30-11.30 room 2411

Book: Open Data

  • Pages 0-110

Presenters (students should add these here)

Group Homework: We'll meet on Wednesday at 4 p.m. in front of the library. Please have a look at the other definitions before the meeting.

Day 3 - 26.3. 12.30-15.30 room 2411

Book: Open Data

  • Pages 111-



Personal homeworks

  • Create your own wiki page
  • Define big data and add links to those 3 documents you have used for defining it (before first day)
  • Ethics in/of big data (before 3rd day)

Group homeworks

  • Create groupwise definition for big data (before second day)
  • Explain relationship between big and open data (before 3rd day)

Final works

  • Provide your coursera course diploma to the lecturer
  • Create 4 exam questions representing the course contents. Explain why the question is good.
  • Grade the presentations
  • Answer to the course questionaire
  • As a group prepare the final presentation of your group to the final presentation
  • Divide x*10 points among course participant (x=number of people in the course)

Extra work for people who missed lectures

  • If you missed lectures you need to provide short reviews (1/2 page each) of all those chapters we went through that lecture time.

Extra work for those who did not get the coursera diploma

  • Critical thinking and argumentation - look for web based material into this topic (that we could possibly use in this course) and provide a summary how the critical thinking and argumentation part implemented like that could help in the discussion part of our seminar course.

Groupwise working area


Big Data is a collection of datasets which contains hidden correlations and information not obvious to identify using traditional methods.


The relation between Big and Open data is close but they are not the same. The main difference between big data and open data is that big data is defined by size and open data is defined by its free and very low cost accessibility.

Big data and open data have the potential to be monetarized. Big data monetization is usually done by the big data owner or collector. On the other hand, Open data usually monetized by a third-party.

Big and open data we could have a potent combination that will transform business, government, and society. With Big data we have the power to better understand and analyse the world around us, while Open data ensures this power will be shared and more transparent.

Group Grades

  • Eleni:10
  • Rafe:10
  • Manuel:10
  • Michal:10
  • Veli-Ensio:10
  • Masood:10
  • Vitor:10
  • Veronica:10
  • Ibrahim:10
  • Mansoureh:10
  • Marc:10
  • Isto:10
  • Martin:10
  • Karri:10
  • Ville:10

Group presentation: final-group-pres.pptx