@@ -7,7 +7,11 @@ They cover topics like querying IRSA, working with catalogs in Parquet format, a
77
88## Accessing IRSA archive holdings
99
10- ### Images
10+ ### Image Thumbnailes
11+
12+ These notebooks show how to query IRSA's image services, inspect the results, and download and visualize images.
13+
14+ They use the tools: PyVO, Astropy.
1115
1216``` {toctree}
1317---
@@ -21,16 +25,68 @@ tutorials/irsa-sia-examples/siav2_seip
2125
2226```
2327
28+ <!-- -
29+ ### Catalogs
30+
31+ ```{toctree}
32+ ---
33+ maxdepth: 1
34+ ---
35+
36+
37+ ```
38+
39+ ## Visualizations
40+ ```{toctree}
41+ ---
42+ maxdepth: 1
43+ ---
44+
45+ ```
46+ -->
47+
48+
2449## IRSA in the cloud
2550
51+ This notebook demonstrates basic access to the IRSA-curated datasets available in AWS S3 cloud storage buckets.
52+
53+ It uses the tools: Pandas, PyArrow, Astropy, Astroquery, PyVO, S3FS
54+
55+ ``` {toctree}
56+ ---
57+ maxdepth: 1
58+ ---
59+
60+ tutorials/cloud_access/cloud-access-intro
61+ ```
62+
63+ ### Catalogs
64+
65+ This notebook shows examples for the Parquet version of the AllWISE Source Catalog, located in AWS S3 cloud storage.
66+ It uses the tools: Pandas, PyArrow, Astropy
67+
2668
2769``` {toctree}
2870---
2971maxdepth: 1
3072---
3173
3274tutorials/parquet-catalog-demos/wise-allwise-catalog-demo
33- tutorials/cosmosims/CosmoDC2_Parquet
75+
76+ ```
77+
78+ ### Explore OpenUniverse 2024 Data Preview
79+
80+ These notebooks explore simulared Roman observation stored in AWS S3 cloud storage.
81+ They use the tools: Pandas, Astropy, S3FS, matplotlib, NumPy
82+
83+ ``` {toctree}
84+ ---
85+ maxdepth: 1
86+ ---
87+
88+ tutorials/openuniversesims/openuniverse2024_roman_simulated_timedomainsurvey
89+ tutorials/openuniversesims/openuniverse2024_roman_simulated_wideareasurvey
3490```
3591
3692## Generally useful techniques
@@ -41,4 +97,5 @@ maxdepth: 1
4197---
4298
4399tutorials/parallelize/Parallelize_Convolution
44- ```
100+
101+ ```
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