diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
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--- /dev/null
+++ b/.github/workflows/main.yml
@@ -0,0 +1,29 @@
+name: Static Demo Site
+
+# Controls when the action will run. Triggers the workflow on push
+on:
+ push:
+ branches:
+ - 'scale-7'
+ pull_request:
+ branches:
+ - 'scale-7'
+
+# A workflow run is made up of one or more jobs that can run sequentially or in parallel
+jobs:
+ # This workflow contains a single job called "build"
+ build:
+ # The type of runner that the job will run on
+ runs-on: ubuntu-latest
+
+ # Steps represent a sequence of tasks that will be executed as part of the job
+ steps:
+ # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it
+ - uses: actions/checkout@v2
+ - uses: tibor19/static-website-deploy@v1
+ with:
+ enabled-static-website: 'true'
+ blob-container-name: '$web'
+ folder: '.'
+ connection-string: ${{ secrets.CONNECTION_STRING }}
+ remove-existing-files: 'false'
diff --git a/demos/README.md b/demos/README.md
new file mode 100644
index 0000000..be7fa2e
--- /dev/null
+++ b/demos/README.md
@@ -0,0 +1,24 @@
+# Ohio Demo Site
+
+This site is used to display demo's of AIS developed software for clients, job fairs, etc.
+
+## Demos
+
+The Current Demos included are
+
+* Eris
+* Scale 5
+* Scale 7
+* Sigma
+* Flock
+
+The Scale 7 Demo uses a mock API which can be found [here](https://scale-7-demo-api.azurewebsites.net/).
+
+## Azure Setup
+
+To make changes to the [existing Azure Demo Site](https://demositestatic.z13.web.core.windows.net/demos) all that is required is a successful pull request to the **scale-7** branch. A Github action will update the site automatically.
+
+To create the site, first a storage account in Azure must be made. After the Storage Account is made, go to Static Website and enable it. A blob named `$web` will be created. At this point there are a couple options.
+
+The first is to use the Azure Storage Explorer and simply dump the repository into the static site blob. Another option is to use Github Actions to upload the reposiory. The benefit of this approach being continuous deployment. [This Page](https://github.com/tibor19/static-website-deploy) to activate it, push to the Github repository.
+
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diff --git a/demos/assets/scale-screenshot.jpg b/demos/assets/scale-5-screenshot.jpg
similarity index 100%
rename from demos/assets/scale-screenshot.jpg
rename to demos/assets/scale-5-screenshot.jpg
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diff --git a/demos/eris/index.html b/demos/eris/index.html
index 8b45941..4d5a886 100755
--- a/demos/eris/index.html
+++ b/demos/eris/index.html
@@ -8,7 +8,7 @@
-
- Eris visualizes the comparison of extracted event output produced by different systems. Analysts can view events correlated
- by temporal and geospatial characteristics and then vote on whether the extraction is useful. This data is then used to provide
- machine-learning feedback data to the source algorithm.
-
- Scale enables on-demand, near real-time, automated processing of large, file-based datasets using a dynamic bank of
- algorithms. Users can monitor cluster health and manage processing pipelines using an interactive Recipe Editor.
-
Eris visualizes the comparison of extracted event output produced by different systems. Analysts can view events correlated by temporal and geospatial characteristics and then vote on whether the extraction is useful. This data is then used to provide machine-learning feedback data to the source algorithm.
-
- Sigma enables interactive analysis of large, geospatial datasets. The app utilizes WebGL for high
- performance visualizations.
-
- The demo include a sample Landsat data set covering the Great Lakes from 01/01/2015 to 11/01/2015.
- You can use this
-
- prepopulated query to view the data set.
+
+
+
+
Scale 5
+
+
+
Scale enables on-demand, near real-time, automated processing of large, file-based datasets using a dynamic bank of algorithms. Users can monitor cluster health and manage processing pipelines using an interactive Recipe Editor.
Scale enables on-demand, near real-time, automated processing of large, file-based datasets using a dynamic bank of algorithms. Users can monitor cluster health and manage processing pipelines using an interactive Recipe Editor.
Sigma enables interactive analysis of large, geospatial datasets. The app utilizes WebGL for high performance visualizations.
+
The demo include a sample Landsat data set covering the Great Lakes from 01/01/2015 to 11/01/2015. You can use this
+
+ prepopulated query to view the data set.
-
- Flock is a clustering and classification engine for processing x/y-based signatures, giving intelligence analysts a head start by providing typing information and context around a given event.
+
+
+
+
Flock
+
+
+
+
+
+ Flock is a clustering and classification engine for processing x/y-based signatures, giving intelligence analysts a head start by providing typing information and context around a given event.
+