Merge pull request #36 from ARTIST-Association/Markus-Goetz-webpage-f…

…ixes

Update papers.html

html/templates/base.html

@@ -39,6 +39,15 @@
                         <a href="/data" class="nav-link text-black p-3 active" aria-current="page">
                         {% else %}
                         <a href="/data" class="nav-link text-black p-3">
+                        {% endif %}
+                            <i class="bi bi-clipboard-data-fill me-2"></i> Overview
+                        </a>
+                    </li>
+                    <li class="nav-item">
+                        {% if active == "repository" %}
+                        <a href="/WRI1030197" class="nav-link text-black p-3 active" aria-current="page">
+                        {% else %}
+                        <a href="/WRI1030197" class="nav-link text-black p-3">
                         {% endif %}
                             <i class="bi bi-database-fill me-2"></i> Data
                         </a>

html/templates/data.html

@@ -5,11 +5,15 @@
 <div class="position-relative text-white">
     <img class="img-fluid w-100" src="static/img/quartz.png">
     <div class="position-absolute top-50 start-5 translate-middle-y">
-        <h1 class="px-4 py-2 fs-large border-start border-2 border-white">Data</h1>
+        <h1 class="px-4 py-2 fs-large border-start border-2 border-white">Database Overview</h1>
         <p class="my-3 fs-3">Calibration images, deflectometry measurements, kinematic information</p>
     </div>
 </div>
 
+<h4 class="my-4 py-2 text-primary">Data Repository</h4>
+
+Our web page offers an <a href="/WRI1030197">HTML-browsable version</a> of the data from the concentrating solar power plant in Jülich, Germany, with the global power plant id (GPPD) WRI1030197. A programmatic API is provided in our <a href="https://github.com/ARTIST-Association/PAINT">repository</a> as a PyTorch dataset and STAC client.
+
 <h4 class="my-4 py-2 text-primary">Data Types</h4>
 
 <dl class="row">

html/templates/home.html

@@ -14,7 +14,7 @@ <h4 class="my-4 py-2 text-primary">Introduction</h4>
 
 The PAINT database makes operational data of concentrating solar power plants available in accordance with the <a href="https://www.nature.com/articles/sdata201618">FAIR data principles</a>, i.e., making them findable, accessible, interoperable, and reusable.
 
-Currently, the data encompasses calibration images, deflectometry measurements, kinematic settings, and weather information of the concentrating solar power plant in Jülich, Germany, with the global power plant id (GPPD) WRI1030197. Metadata for all database entries follow the <a href="https://stacspec.org/en">spatio-temporal asset catalog (STAC) standard</a>.
+Currently, the <a href="/WRI1030197">data</a> encompasses calibration images, deflectometry measurements, kinematic settings, and weather information of the concentrating solar power plant in Jülich, Germany, with the global power plant id (GPPD) WRI1030197. Metadata for all database entries follow the <a href="https://stacspec.org/en">spatio-temporal asset catalog (STAC) standard</a>.
 
 PAINT closely follows open science guidelines and makes all software to (pre-)process data publicly available in the <a href="https://github.com/ARTIST-Association/PAINT/">project's source code repository</a>.
 

html/templates/papers.html

@@ -10,16 +10,11 @@ <h1 class="px-4 py-2 fs-large border-start border-2 border-white">Papers</h1>
     </div>
 </div>
 
-<h4 class="my-4 py-2 text-primary">PAINT Release Paper</h4>
-
-<ul>
-    <li>M. Pargmann, K. Phipps, M. Kuhl, M. Weiel, M. Busch, N. Blumröhr, D.M. Quinto, C. Debus, F. Göhring, A. Streit, R. Pitz-Paal, M. Götz "A FAIR database for concentrating solar power plant data".</li>
-</ul>
-
 <h4 class="my-4 py-2 text-primary">Papers based on PAINT</h4>
 
 <ul>
-    <li>M. Pargmann, J. Ebert, M. Götz, D.M. Quinto, R. Pitz-Paal, S. Kesselheim "Automatic Heliostat Learning for In-situ Concentrating Solar Power Plant Metrology with Differentiable Ray Tracing" <i>Nature Communications</i> (accepted).</li>
+    <li>M. Pargmann, J. Ebert, M. Götz, D.M. Quinto, R. Pitz-Paal, S. Kesselheim "Automatic Heliostat Learning for In-situ Concentrating Solar Power Plant Metrology with Differentiable Ray Tracing" <i>Nature Communications</i> 15(1) (2024): 6997, doi: <a href="https://doi.org/10.1038/s41467-024-51019-z">10.1038/s41467-024-51019-z</a>.</li>
+    <li>M. Kuhl, M. Pargmann, M. Cherti, J. Jitsev, D.M. Quinto, R. Pitz-Paal "Flux density distribution forecasting in concentrated solar tower plants: A data-driven approach" <i>Solar Energy</i> 282 (2024): 112894, doi: <a href="https://doi.org/10.1016/j.solener.2024.112894">10.1016/j.solener.2024.112894</a>.</li>
     <li>M. Pargmann, D.M. Quinto, P. Schwarzbözl, R. Pitz-Paal "High accuracy data-driven heliostat calibration and state prediction with pretrained deep neural networks." <i>Solar Energy</i> 218 (2021): 48-56, doi: <a href="https://doi.org/10.1016/j.solener.2021.01.046">10.1016/j.solener.2021.01.046</a>.</li>
 </ul>