Assignment #3 guidelines (draft)

You will be asked in assignment #3 to contribute data to a "linguistic landscaping" citizen science project. It is a project-based research exercise assembling, describing, analyzing and selecting data about the "linguistic landscape" (LL) of the place of your choice: Abu Dhabi, another place you have visited or a combination of both. This can be done individually or in pairs.

You will remember from the presentation on LL research that you can take many different perspectives in carrying out your project. You will have a variety of readings (linked below) you can use to situate your project conceptually. You can use both the data you have collected and the data from the rest of the class to write up your final project.

Data collection:

You should use the Lingscape app to collect around 50 examples from the LL of the places of your choice by December 7th. Please collect these samples while you are logged on to the Abu Dhabi Fall 22 project using the app.

Check out the "tips and tricks" section of the information tab in the app.

If you collected data during fall break directly into the Lingscape app, make a list of the pictures taken and their numbers and take some screenshots identifying the ones you took.

If you collected data directly in our Fall project, please indicate your collector ID in the comment field, or make a list from the project data shared in drive for your instructor.

Tips on data collection:

If you are collecting in Abu Dhabi, you might want to look for samples which are not only of the official Arabic and English. You should collect no more than 5 of your samples from campus. Make sure you tag the samples with the languages found therein, or write in the comment field if the tags are insufficient. Data collection is an individual process, although the analysis of the LL can be in pairs.

Data selection for analysis:

As demonstrated in class, a folder and a main spreadsheet with the project metadata will be shared with you as of Dec 8th. You can use this data to put together your final project writeup, using data you have collected, in addition to the data of others. I encourage you to use the methods we have refined in class of structured data table construction, tagging and enriching metadata, as well as pivot tables, data validation, etc. to build your own subset of the data to speak about. You do not have to include all 50 data points in your analysis, but please make sure that you speak about at least 10-20 points in your analysis. If you are working in groups, please make the number of points and length of the essay analyzed commensurate with the number of team members.

Interactive map in assignment #3:

In the assignment #3, you should have at least one interactive map which shows the extent of the class data that you are analyzing. You may also have galleries of embedded images, any graphs of visualizations of your choice, as well as screenshots of maps in your site.

You have a few possibilities for creating your interactive map. Kepler will not work here for the interactive map.

(1) Google My Maps: You go to maps.google.com when you are authenticated: Your places > Maps > create a map. Use the import function to upload a csv file. Use the camera icon to upload images one by one. You will not need an iframe to embed this in Google Sites.

(2) UMap + GitHub: You need to adjust the size of your image to make them thumbnails and push them to a repository such as GitHub. Using the link for the raw image, you can adjust the popup box contents to pull from Github.

(3) ArcGIS Online + GitHub: If you would like to learn AGOL, you will need an account. I have requested them to be reactivated. If it is not, please let me know and we can follow up in data services. This will be embedded using an iframe. Instructions can be found here.

A recorded version of class on Nov 29 discusses the possible ways of putting together such a map. It can be found here.

Other requirements for the project:

1. a structured dataset in the form of a google sheet/csv file embedded or downloadable from your site detailing which images you used.

2. about 1500 words of analysis (results, process, obstacles)

3. references to critical materials about LL & citizen science

Possible questions to address in your analysis:

• What can you say about the places in which the data was collected? Can you give some context about the locations, especially if the data of interest does not come from Abu Dhabi?

• How difficult or easy was it to collect the data? How did the app facilitate or not facilitate the process? What obstacles did you encounter?

• What patterns did you find in and between languages? Are certain languages used for specific purposes? Are certain combinations of languages used for specific purposes? Can you make more general speculation about the use of language in specific contexts?

• Do combinations of languages have a spatially significant dimension? What do you think much more data on the map of the location you studied would reveal?

• What did you learn about language in the place you collected data? Did you have to do any research (or consult others) to understand the landscape?

• How does the data you have collected compare with the data of other "citizen scientists" that you can view in Lingscape's interactive map?

• What can you say about the process of participating in a large citizen science project? What kind of a contribution do you believe you are making?

• What are the most important values of citizen science for you? If you were to design a spatially inflected citizen science project similar to Lingscape what would you do?

• What can you tell about the movements of the data collectors in this exercise? why is it good that we don't know who the data collectors are?

• Do you have any suggestions for the app developers to make this experience better?

Readings for context and background in LL:

Crowdscapes. Participatory research and the collaborative (re) construction of linguistic landscapes with Lingscape (Purschke)

Citizen Humanities (Heinisch et al)

"Participatory Methods and Citizen Science" (Geoghegan, in drive)

Digital Spatial Practices and Linguistic Landscaping in Beirut (Wrisley)

Exploring the Linguistic Landscape of Cities Through Crowdsourced Data (Purschke)