Developing an Internet Measurements training course

Which skills and knowledge should be included in an Internet Measurements training course? Let us know what you think!

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I would suggest first basic statistics (I’m always surprised by the number of people who use the average when they should use the median).
Then (unless it is obvious and assumed by default) Internet behavior basics (such as the fact that issues are not random, problems gather together, etc).
Then the tools (Python, R, etc).

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This is a great start! I wonder if you can maybe point me to a list of Internet behavior basics I can use as a reference? As a technical trainer I don’t work directly with networks, except in theory, so I need some guidance here. :saluting_face:
What do you think of focusing on using RIPE NCC tools (RIPEstat, RIPE Atlas) for the measurements?

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I’d think concepts like bandwidth, delay and throughput should be explained in some detail.

Capacity, not bandwidth, which is an old concept from analog times. But yes, basic things such as the fact that a network path can be bounded in p/s or in b/s are important.

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Well, the RIPE-NCC tools are fine for a start but I think that users will soon need more, requiring some programming.

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I think that the concepts of “ethics in measurements” should be included; see my previous work on that: Ethics in Network Measurements | RIPE Labs & more links here: (e.g. #27, Human Right Considerations) Ethics of Internet Measurements – Example of RIPE Atlas - JCSA 18 — RIPE Network Coordination Centre
& one of the sources : OII | Ethics in Networked Systems Research: ACM SigComm Workshop Report

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Even further, I’d like it if we also mention Data Justice - because Internet Measurements are about collecting data, and then using / visualising it to make decisions… Data Feminism: From Data Ethics to Data Justice | RIPE Labs

Data science has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind?

Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice."

From Data Feminism, by Catherine D’Ignazio and Lauren F. Klein

That’s a possibility, though we cannot dedicate too much time to teaching a programming or scripting language. Maybe some guidance and practical examples could be enough? Learners can then develop their programming/scripting skills on their own.

I agree! We will see how we can include this as part of the learning goals.

So maybe starting the training course with general definitions? This way the learners can all be brought up to the same level of understanding of these concepts.

Excellent initiative, I think there should be a theoretical part and a more hands-on part:
Theoretical:

  1. Internet protocols (looking at the different layers) and provide a general understanding of what can be measured for different
  2. Statistical analysis
  3. RIPE Atlas, RIPE RIS, RIPE Stat and other toolsets
  4. Other available systems (CAIDA Ark, routeviews, etc)

Hands-on part:

  1. Practical measurement exercises with RIPE Atlas
  2. Data collection and analysis using RIPE Atlas API/toolsets
  3. Statistical analysis and data visualization using python
  4. Storytelling from measurement data

You can have a look at this:

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Thank you, Amreesh! This is really helpful input. Our idea is to make the course a “learn by doing” experience. There will be a mix of theory and hands-on activities designed to meet the learning goals of the training course.

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Does anybody have a suggestion of what the pre-requisites to attend this training course should be? Who would be the main target audience for such a training course?