Pre-arrival

The Summer Institute will bring together people from many fields and backgrounds. In order to use our time together efficiently, there are a number of things that you should do before participating in SICSS-ODISSEI 2022.

• Complete the pre-institute readings
• Complete coding bootcamp (if needed)
• Prepare your computing environment

TAs will host office hours through Slack to support you as you work through these pre-arrival materials.

Reading

For the summer school, SICSS-ODISSEI requires the participants to prepare in advance, both in terms of training and reading material. Below you will find the list of required (and optional) materials. However, please note that in addition to the provided list below, more reading material will be provided in the coming months. In total, the preparatory reading will be no more than 5-6 articles or chapters.

In order to prepare for SICSS-ODISSEI 2022, you should read Matt Salganik’s book, Bit by Bit: Social Research in the Digital Age (Read online or purchase from IndieBound, Princeton University Press), or Amazon, Barnes & Noble. Parts of this book, which is a broad introduction to computational social science, will be review for most of you, but if we all read this book ahead of time, then we can use our time together for more advanced topics.

Obligatory reading material:

• Hofman, Jake M., et al. “Integrating explanation and prediction in computational social science.” Nature 595.7866 (2021): 181-188.
• Liu, David M., and Matthew J. Salganik. “Successes and struggles with computational reproducibility: lessons from the fragile families challenge.” Socius 5 (2019): 2378023119849803.
• Salganik, Matthew J., Ian Lundberg, Alexander T. Kindel, Caitlin E. Ahearn, Khaled Al-Ghoneim, Abdullah Almaatouq, Drew M. Altschul et al. “Measuring the predictability of life outcomes with a scientific mass collaboration.” Proceedings of the National Academy of Sciences 117, no. 15 (2020): 8398-8403.
• Breznau, Nate, Eike Mark Rinke, Alexander Wuttke, Muna Adem, Jule Adriaans, Amalia Alvarez-Benjumea, Henrik Kenneth Andersen et al. “Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty.” (2021).
• van der Laan, Jan, Marjolijn Das, Saskia te Riele, Edwin de Jonge, and Tom Emery. “Using a network of the whole population of the Netherlands to measure exposure to differing educational backgrounds.” (2021).
• Lugtig, Peter. “Panel attrition: separating stayers, fast attriters, gradual attriters, and lurkers.” Sociological Methods & Research 43, no. 4 (2014): 699-723.

Recommended material:

• Introduction to Data Science for Social Scientists
• Machine learning versus Statistics
• Statistics versus Machine learning

If you have any further questions or comments, please do not hesitate to contact us at sicss@odissei-data.nl.

Training

We strongly recommend that participants follow the course Data Science & Society Introduction course which is provided by Chris Bail. In the course the emphasis is more on text and unstructured data than the content covered in the SICSS-ODISSEI summer school which will be more oriented towards complex, structured administrative and linked data. However, many of the principles are the same and it will provide excellent preparation for our two weeks in Rotterdam.

Participants are expected to be familiar with both R and Python before the start of the summer school. It is expected that you will arrive at the summer school ready to use both R and Python. We would encourage participants to bring their own laptops with R and Python installed and ready to use. If bringing your own laptop is not possible or is impractical for any reason, please let us know and we will make alternative arrangements for you.

For what concerns Python, to support your preparation we have arranged for participants to follow a virtual workshop called ‘Data Carpentry for Social Sciences with Python’, provided by the Netherlands eScience Center. The workshop will take place online, from 30 May to 2 June. The workshop will ensure that the participants have the necessary knowledge and experience with Python to participate in sessions during the summer school. If you are not able to attend or do not feel like it is necessary for you, please email sicss@odissei-data.nl. before April 25. Please register via the eScience website. To register follow the steps below:

• Select Register
• Select Enter Promo Code
• Put in escience-odissei
• Click apply
• Select SICSS-ODISSEI ticket
• In the registration form under the Affiliation information section check the check box next to “I am not affiliated with a Dutch research organization, but I am a project partner with the eScience Center. (….)” .

In addition to the Data Science & Society Introductory Course, there are a large number of resources for learning R that are available:

The SICSS Boot Camp is an online training program created by Chris Bail to provide you with beginner level skills in coding so that you can follow the more advanced curriculum we teach at SICSS. The videos and materials are designed for complete beginners and are best viewed as a sequence since each video builds upon content introduced in previous tutorials. If you are already familiar with the topics in these videos, you do not need to complete them. Other recommendations include:

• RStudio Primers, which can be supplemented by the open access book R for Data Science by Garrett Grolemund and Hadley Wickham
• R for Social Science, Data Carpentry.
• Introduction to R for Social Scientists, Taught by Charles Lanfear at University of Washington. This course includes videos of lectures, slides, and assignments.
• Learn R, Code Academy.

If you are already (highly) experienced in any of the above-mentioned necessary training, please contact us at sicss@odissei-data.nl.

Computing environment

R

Some of the activities will require coding, and we will support R. You are welcome to use other languages, but we cannot guarantee that we can support them. Before SICSS you should install a modern, stable-release version of R and RStudio.

Slack

Before participating at SICSS-ODISSEI 2022, you should have an account in the SICSS 2022 Slack workspace. If you have not used Slack before, you should review these getting started materials. Slack can be hard to use at first, but we’ve found that it is the best way to enable everyone to collaborate.

GitHub

Many participants at SICSS use GitHub to collaborate. If you do not yet have one, you should create a GitHub account. If you are a student, we recommend that you apply for a GitHub Student Developer Pack.

Office hours

The SICSS-Duke TAs will host weekly office hours in the SICSS 2022 Slack. You can find information about the office hours in the SICSS 2022 Slack channel #pre-office-hours. If you are not able to attend during the regularly scheduled office hours or have any questions about office hours, please contact one of the TAs.