February 18, 2022

Big data challenges

To solve a big data problem, it's important to recognize where the challenge lies in terms of the 4 Vs (volume, velocity, variety, veracity). This video works through one example (predicting hail to avoid fruit damage).

January 4, 2021

Sharing information on genetic makeup for big data analysis

Imagine working at a lab that runs diagnostics on the genetic makeup of individual persons in combination with other individual information, e.g., personal habits and living conditions etc. The amount of data you collect on individuals over time is extensive, and it can be used for general big data analyses as well as for individual risk assessments. How should access to this data and to respective analyses be handled?

February 18, 2022

How big is Big Data?

May 26, 2016

Reportage: Hoe open data tourbussen helpt | 4.1 Big data, beter beleid?

Reportage: Hoe open data tourbussen helpt | 4.1 Big data, beter beleid?

May 26, 2016

Interview: Paul Suijkerbuijk | 4.2 Big data, beter beleid?

Interview: Paul Suijkerbuijk | 4.2 Big data, beter beleid?

May 26, 2016

Basics en classics: Hugo Verheul | 4.3 Big data, beter beleid?

Basics en classics: Hugo Verheul | 4.3 Big data, beter beleid?

February 18, 2022

Immutability is great

The video explains why immutibility of data is such an important requirement for big data.

August 23, 2023

Lecture: Data Preparation and Exploration

To be able to chose the most suited data preparation method based on the case prepare data in practice (handle missing values, create new derived features) Data enrichment Ethical: anonymisation and problems with this (identification possible in indirect ways) - again, there should be some examples out there Imputation – mention that it can introduce bias and that this needs to be kept in mind New feature creation – loss of proper semantics Ethical: remove bias from the dataset Parallels and differences between sampling of data in statistics and acquisition of data (including big data) for ML and AI

March 12, 2018

3.8 Digital challenges 2

One of the buzzwords of our time is big data. It's hard to define the term but one often used definition states that big data is characterized by its volume, the amount of data, its velocity, the speed with which new data arrive, and its variety. by using social media a lot of this data is generated. What ethical issues can arise here?

October 14, 2017

Amsterdam: Smart Citizens in Smart Cities

Big Data and new appliances (such as advanced apps showing local air pollution) may make elements of city life more sustainable. But there is ongoing debate on the Smart City. Which stakeholders have an interest in ‘smart cities’? And what does it mean to live in one? In this video on air quality in Amsterdam, prof. at Erasmus University in Rotterdam Liesbet van Zoonen will reflect on these topics and address what Smart Cities and Big Data entail for citizens’ everyday life. You will see that there is a major debate surrounding the accelerating use of ICT in the urban setting. LEARNING OBJECTIVES: Design policies; governance arrangements and coordination structures for resilience planning and response addressing policy-making; public private partnerships and civic engagement. DURATION: 1 short video (~10 min video)