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Author: ipopovaite

Jul 27 2018

Exploring spacewalk patterns: work done so far

Posted on July 27, 2018 by ipopovaite

As you might recall from my previous post, I have been working on a prototype tool to visualize spacewalk patterns that occur in short term Mars habitat simulations. 

My work so far

I used R packages shiny, visnetwork, and plotly to create an interactive web application for data exploration. Here is how it looks now: 

 The main drop down menu selects a crew to display. A network graph shows who worked with whom on extravehicular activities (EVAs). Each node is a crew member, and the size of a tie represents how many times these people worked together on an EVA. A bar chart in the bottom right corner shows the total number of EVAs that a crew member participated in.

A user can also select a single EVA to see which crew members worked together.


Future steps

This simple app functions well, but I want to tweak its appearance: put role abbreviations to the bottom left corner, make sure that the interface is displayed properly both on computers’ and phones’ screens, have a unified theme for different elements of the app. Also, I want to connect the network plot with the bar chart: when a user clicks on a node, a bar that corresponds to that node also gets selected.

I want to add more socio-demographic data, such as level of education, previous participation in such simulations, and experience in space industry. I want to enable user to visualize interaction networks by other demographics, not just by gender and role in a crew.

I also plan to add regression models that test whether women are less likely to be central figures than men, controlling for their role in a crew and other demographics.

Things I have learned

It has been a short journey in the Studio, but a fulfilling one. Summer funding allowed me to take a breath, work on my project, and think about my professional and academic future.

I have learned that I like building things and enjoy solving problems. I have used R Shiny for the very first time, and its familiar syntax was painless introduction to the world of interactive visuals.

I come from an interdisciplinary background (journalism-nationalism studies-sociology). As a journalist, I tell stories; and as a researcher, I want to do the same. A well done web application or a well done web page is a more efficient way to communicate one’s scholarship than an academic article. Yes, in academia it is still seen as a supplement rather than a substitute to a peer reviewed publication. And it’s a pity – it takes a lot of time, skills, and effort to create even the simplest visuals. On the other hand, it still is time well spent: by creating a visual story, one gets to know their data very intimately. And the world does not end with academia – it is helpful to leave the ivory tower and engage with the audiences outside of it. Who knows, maybe it will land me a job in this world of scarce tenure track positions.

Inga Popovaite, sociology PhD student

Posted in Digital Scholarship & Publishing, Studio FellowsTagged networks, r shiny, sociology, studio fellowship, visualization
Jun 28 2018

Mapping gender and status in simulated Mars missions

Posted on June 28, 2018June 28, 2018 by ipopovaite

NASA has scheduled the first manned mission to Mars by 2030s. Millions of miles away, this group of astronauts will constitute a micro society. Women and men, most likely from different cultures, will have to live and work together in claustrophobic chambers for a long time.

Stereotypes in task groups

To prepare for this experience, psychologists have long been studying groups in similar conditions – for example wintering crews in Antarctica, or volunteers participating in Mars habitat simulations. Existing research on mixed gender crews in isolated confined extreme (ICE) conditions shows that males and females have different experiences – for example, they report different stressors, different relations between crew members; females report more  unwanted sexual attention and harassment. Gender differences are usually explained by personality and situational factors; and social structure is left out of the equation.

But sociologists have shown that structural inequality and stereotyping, that shape societies at large, are imported into small group settings every time we interact. For example, in work groups we subconsciously stereotype others, and judge about their abilities based on their gender, race, ethnicity and other observable status characteristics. This happens both in newly formed, and in long term task groups – in latter, stereotypes keep influencing our decisions even if we are aware how well or poorly our teammates have performed in the past.

It is a self-fulfilling prophesy: we know who should be better at a task based on our stereotypical knowledge, and then we let them lead our group and contribute more to the task. But even if we know their actual abilities, stereotypical knowledge will continue to influence the formation of the status hierarchy in the group.

Simulated spacewalks, status hierarchy, and network analysis

 My first step in understanding how gender impacts informal status hierarchy formation in small isolated crews is secondary data analysis from the Mars Desert Research Station (MDRS) archives that are freely available online.

MDRS is a space analog facility in Utah owned and operated by a non-profit Mars Society. Each year, MDRS hosts an eight month field season for professional scientists and engineers as well as college students of all levels, in training for human operations specifically on Mars. Most missions are 2 weeks in duration. To this day, over 190 crews have conducted their research on the site over the course of 16 field seasons.

Most of the crews consist of six members, each of them are assigned the following roles: Commander, Executive Officer, Health and Safety Officer, Crew Biologist or Astrophysicist, Crew Geologist or Chief Engineer. These roles are consistent to most part across different crews. Each crew member has to file daily logs and reports; most reports from previous crews have been archived and available online through the MDRS website. In addition to logs, members of each crew post a short biography of themselves, usually including their education, occupation and other information relevant to their participation in a simulation.

Extravehicular activities (EVAs), or simulated spacewalks, are a crucial part of Mars habitat simulation. Thus it is likely that crew members who are seen as more important to the mission, will go on more simulated spacewalks. If we know who went on spacewalks with whom and who did it more often, then we can have a glimpse (albeit imperfect) to this crew’s status hierarchy.

To get there, I will analyze daily logs and biographic entries from a random sample of crews to see whether males or females are more central to the mission success.

I will use social network analysis to map status hierarchy in crews. Each node will represent a crew member, and ties between them will show how often they have worked together. I will use centrality measures to determine the most central person (or the person who has the highest in-group status). Later, I will use logistic regression models to determine whether males or females are more likely to be the most central, controlling for their role in the crew and other sociodemographic variables.

Summer at the Studio

A picture is worth a thousand words. When I started thinking about this project, I instantly knew that I need attractive visuals to accompany it.

There is a simple way to do it. Two graphs that show the same crew, one coded by gender, and the other by different crew roles. In both, thicker lines indicate that these individuals have worked together more often. In the left, black color marks males. It shows that the most central person is a male. In the right, the same crew is coded by their roles. The central node is the engineer. 

It is possible to detect some interaction patterns looking at these graphs side by side. But I want to visually summarize the data better. As one of the Studio fellows, this summer I will design and create a prototype of an animated interactive network graph (using simulated data) for the future use. This graph will:

  • Be evolving. It will show how the final networks (e.g. the ones above) came to be. I will add data from one EVA at a time.
  • Allow to see the formation of the network by gender, by role in the crew, or other sociodemographic characteristic.
  • Show who is the most central person in this crew.
  • Allow to compare crews side-by-side.

I think I can do all of it in R/ R Shiny, with some help of Java-based ndtv-d3 network animation player. Another route would be to use d3.js library, but I am not as comfortable in Java as I am in R. But I will keep an open mind and give you updates as I go, either here or on my blog. 

-Inga Popovaite

Posted in Digital Scholarship & Publishing, Publishing, Studio Fellows

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