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Critical thinking2: Open Data Now
- Lecturer: Prof. Jari Porras
- Assistant: nn
- Books:
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)
- Verónica Morales, chapter 1 chapter1.now.pptx
- Ibrahim Olanigan, chapter 2 chapter2-more.pdf
- Mansoureh Rousta , chapter 3 messy.pptx
- Marc Seidel, chapter 4 correlation_presentation.pdf
- Masood Maldar, Chapter 5 datafication.pptx
- Eleni Almpanopoulou, Chapter 6big_data_value.pptx
- Vitor Meneguetti, chapter 7 chapter7_vitor.pdf
- Martin Snizek, chapter 8 bd-ch8--risk-my-presentation.pptx
- Manuel Delgado, chapter 9 big_data_-_chapter_9_-_control.pdf
- Michal Genserek, chapter 10 gen_next.pdf
- Lilli Gunnar, Chapter 5
- Raf Ba, Chapter 6 bigdata-chapter6.value.pptx
Day 2 - 13.3. 8.30-11.30 room 2411
Book: Open Data
- Pages 0-110
Presenters (students should add these here)
- Manuel Delgado, chapter 1 - An opportunity as big as the Web. open_data_now_-_chapter_1.pdf
- Verónica Morales, chapter 2 opendatanowchapter2.pptx
- Vitor Meneguetti, chapter 3 - Consumer Websites: Choice Engines for Smart Disclosure open_data_chapter_3_consumer_websites_-_choice_engines_for_smart.pdf
- Masood Maldar, chapter 4 - New Companies to Manage the Data Deluge chapter_4-opendatanow.pptx
- Ville Liikanen, chapter 5 http://1drv.ms/19TbhvB
- Marc Seidel, chapter 6 - Green Investing: Betting on Sustainability Data open_data_green_investing.pdf
- Mansoureh Rousta, chapter 7- Savvy Marketing:How Reputational Data Defines Your Brand chapter7.pptx
- Lilli Gunnar, chapter 1 - An opportunity as big as the Web
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-
Presenters
- Almpanopoulou Eleni/Raf Ba, chapter 8 - The Marketing Science of Sentiment Analysis chapter_8.pdf
- Isto Sipilä, Chapter 9 - Tapping the Crowd for Fast Innovation open_data_now_chapter_9.pptx
- Ibrahim Olanigan, Chapter 10 - The Open Research Lab: Innovating through Open Collaboration the_open_research_lab.pptx
- Veli-Ensio Heiniluoto, chapter 11 opendata_chapter11.pdf
- Karri Väänänen, Chapter 12 ch12.pdf
Homeworks
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 DEFINITION
Big Data is a collection of datasets which contains hidden correlations and information not obvious to identify using traditional methods.
RELATION BETWEEN OPEN DATA AND BIG DATA
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