doc: correct the FAQ contact answer and the Preface language list

faq.qmd

@@ -4,7 +4,7 @@
   - A: Please see [this page on our website](https://a2cps.org/researchers/accessing-our-data/).
 
 - Q: After reviewing the kit, I still have questions. Who should I contact?
-  - A: Each kit is maintained by a different member of the DIRC, and their contact information is listed at the end of the kit. Please use the channels listed in the kit
+  - A: For questions about a kit itself (e.g., an error in an example, or a request for another one), please open an issue on the [starter kits repository](https://github.com/a2cps/starterkits/issues). For questions about the data, or about how to access them, please see [this page on our website](https://a2cps.org/researchers/accessing-our-data/).
 
 - Q: I am not familiar with `R`. What are a few good resources.
   - A: A great introduction to data analysis in R is the [R for Data Science](https://r4ds.hadley.nz/) book. Many of the starter kits rely on the [tidyverse](https://www.tidyverse.org/), which is covered in that book. 

index.qmd

@@ -2,4 +2,4 @@
 
 Starter kits are brief tutorials that are designed to help guide internal A2CPS projects. The kits target researchers accustomed to working with some specialized data format, but not necessarily the modality in question (e.g., someone familiar with genetics working with neuroimaging data). 
 
-Each kit has two sections, information about how to access the relevant data, and an overview of related work by the DIRC. Kits provide examples of how to explore the data and run simple analyses. These examples rely on various kinds of code, including shell commands, `R`, and `python`. These examples should be seen as only one of many ways to interact with the data. For example, the data reviewed in @sec-freesurfer is stored in `tsv` (tab-separated value) files, and that kit demonstrates working with those tables in `R`. But the tsv can be read with many programs besides `R`, including programs like Excel. The kits rely on code because the dataset is large enough that code- and scripting-based analyses provide substantial benefits.
+Each kit has two sections, information about how to access the relevant data, and an overview of related work by the DIRC. Kits provide examples of how to explore the data and run simple analyses. These examples rely on shell commands and `R`. These examples should be seen as only one of many ways to interact with the data. For example, the data reviewed in @sec-freesurfer is stored in `tsv` (tab-separated value) files, and that kit demonstrates working with those tables in `R`. But the tsv can be read with many programs besides `R`, including programs like Excel. The kits rely on code because the dataset is large enough that code- and scripting-based analyses provide substantial benefits.