more info text below report

Author: devhelpr

src/assets/synthetic-data.tsx

@@ -327,6 +327,11 @@ def run():
         'data': synthetic_data.head().to_json(orient="records")
     }))
 
+    setResult(json.dumps({
+        'type': 'text',
+        'key': 'syntheticData.moreInfo'
+    }))
+
     return 
     
 

src/index.css

@@ -4,7 +4,8 @@
 
 .content-list,
 .markdown {
-    p a {
+    p a,
+    li a {
         @apply text-blue-500 underline;
     }
 

src/locales/en.json

@@ -131,7 +131,8 @@
         "diagnosticsTitle": "Diagnostic Results",
         "correlationDifference": "Correlation difference: {{correlationDifference}}",
         "univariateText": "{{samples}} synthetic data points are generated using CART. The figures below display the differences in value frequency for each variable. The synthetic data is of high quality when all bars are of equal height.",
-        "bivariateText": "The figures below display the differences in value frequency for a combination of variables. For comparing two categorical variables, bar charts are plotted. For comparing a numerical and a categorical variables, a so called [violin plot](https://en.wikipedia.org/wiki/Violin_plot) is shown. For comparing two numercial variables, a [LOESS plot](https://en.wikipedia.org/wiki/Local_regression) is created. For all plots holds: the synthetic data is of high quality when the shape of the distributions in the synthetic data equal the distributions in the real data."
+        "bivariateText": "The figures below display the differences in value frequency for a combination of variables. For comparing two categorical variables, bar charts are plotted. For comparing a numerical and a categorical variables, a so called [violin plot](https://en.wikipedia.org/wiki/Violin_plot) is shown. For comparing two numercial variables, a [LOESS plot](https://en.wikipedia.org/wiki/Local_regression) is created. For all plots holds: the synthetic data is of high quality when the shape of the distributions in the synthetic data equal the distributions in the real data.",
+        "moreInfo": "  \n  \n  \n  \nDo you want to learn more about synthetic data?\n  \n  \n  \n- [python-synthpop on Github](https://github.com/NGO-Algorithm-Audit/python-synthpop)\n- [local-first web app on Github](https://github.com/NGO-Algorithm-Audit/local-first-web-tool/tree/main)\n- [Synthetic Data: what, why and how?](https://royalsociety.org/-/media/policy/projects/privacy-enhancing-technologies/Synthetic_Data_Survey-24.pdf)\n- [Knowledge Network Synthetic Data](https://online.rijksinnovatiecommunity.nl/groups/399-kennisnetwerk-synthetischedata/welcome) (for Dutch public organizations)\n- [Synthetic data portal of Dutch Executive Agency for Education](https://duo.nl/open_onderwijsdata/footer/synthetische-data.jsp) (DUO)\n- [CART: synthpop resources](https://synthpop.org.uk/resources.html)\n- [Gaussian Copula - Synthetic Data Vault](https://docs.sdv.dev/sdv)"
     },
 
     "biasAnalysis": {

src/locales/nl.json

@@ -130,7 +130,8 @@
         "evaluationOfGeneratedDataTitle": "3. Evaluatie van gegenereerde data",
         "outputDataTitle": "4. Output data",
         "diagnosticsTitle": "Diagnostische Resultaten",
-        "correlationDifference": "Correlatie verschil: {{correlationDifference}}"
+        "correlationDifference": "Correlatie verschil: {{correlationDifference}}",
+        "moreInfo": "  \n  \n  \n  \nWil je meer weten over synthetische data?\n  \n  \n  \n- [python-synthpop op Github](https://github.com/NGO-Algorithm-Audit/python-synthpop)\n- [local-first web app op Github](https://github.com/NGO-Algorithm-Audit/local-first-web-tool/tree/main)\n- [Synthetische Data: wat, waarom en hoe?](https://royalsociety.org/-/media/policy/projects/privacy-enhancing-technologies/Synthetic_Data_Survey-24.pdf)\n- [Kennis Netwerk Synthetische Data](https://online.rijksinnovatiecommunity.nl/groups/399-kennisnetwerk-synthetischedata/welcome) (for Dutch public organizations)\n- [Synthetische data portaal van DUO](https://duo.nl/open_onderwijsdata/footer/synthetische-data.jsp)\n- [CART: synthpop resources](https://synthpop.org.uk/resources.html)\n- [Gaussian Copula - Synthetic Data Vault](https://docs.sdv.dev/sdv)"
     },
     "biasAnalysis": {
         "demo": {