update organisation name across repo

.github/CODEOWNERS

@@ -1,3 +1,3 @@
 # Catch-all rule
-/data-processed/ @covid19-forecast-hub-europe/ecdc
-/model-metadata/ @covid19-forecast-hub-europe/ecdc
+/data-processed/ @european-modelling-hubs/ecdc
+/model-metadata/ @european-modelling-hubs/ecdc

.github/workflows/ValidationV2.yml

@@ -15,7 +15,7 @@ jobs:
     steps:
     - uses: actions/checkout@v3
       with:
-        repository: 'epiforecasts/covid19-forecast-hub-europe-validations'
+        repository: 'european-modelling-hubs/covid19-forecast-hub-europe-validations'
 
     - name: Setup Python
       uses: actions/setup-python@v2

.github/workflows/reports-country.yml

@@ -59,7 +59,7 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.FORECASTHUB_TOKEN }}
         run: |
-           gh workflow run build-and-deploy.yml -R covid19-forecast-hub-europe/covid19-forecast-hub-europe-website
+           gh workflow run build-and-deploy.yml -R european-modelling-hubs/covid19-forecast-hub-europe-website
 
       - name: Create issue about failure
         if: failure() && github.event_name != 'workflow_dispatch' && github.event_name != 'pull_request'

.github/workflows/reports-model.yml

@@ -59,7 +59,7 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.FORECASTHUB_TOKEN }}
         run: |
-           gh workflow run build-and-deploy.yml -R covid19-forecast-hub-europe/covid19-forecast-hub-europe-website
+           gh workflow run build-and-deploy.yml -R european-modelling-hubs/covid19-forecast-hub-europe-website
 
       - name: Create issue about failure
         if: failure() && github.event_name != 'workflow_dispatch' && github.event_name != 'pull_request'

.gitmodules

@@ -1,4 +1,4 @@
 [submodule "validation"]
 	path = validation
-	url = https://github.com/epiforecasts/covid19-forecast-hub-europe-validations
+	url = https://github.com/european-modelling-hubs/covid19-forecast-hub-europe-validations
 	ignore = all

DESCRIPTION

@@ -3,4 +3,4 @@ Version: 0.1
 Depends:
   HubValidations
 Remotes:
-  covid19-forecast-hub-europe/HubValidations
+  european-modelling-hubs/HubValidations

README.Rmd

@@ -19,7 +19,7 @@ We are aggregating forecasts of new cases and deaths due to Covid-19 over the ne
 
 * View the [current forecasts](https://covid19forecasthub.eu/visualisation)
 * We publish a weekly [evaluation](https://covid19forecasthub.eu/reports) of current forecasts
-* Raw forecast files are in the [data-processed](https://github.com/epiforecasts/covid19-forecast-hub-europe/tree/main/data-processed) folder
+* Raw forecast files are in the [data-processed](https://github.com/european-modelling-hubs/covid19-forecast-hub-europe/tree/main/data-processed) folder
 
 ##### README contents
 

README.md

@@ -14,7 +14,7 @@ over the next four weeks in countries across Europe and the UK.
     [evaluation](https://covid19forecasthub.eu/reports) of current
     forecasts
   - Raw forecast files are in the
-    [data-processed](https://github.com/epiforecasts/covid19-forecast-hub-europe/tree/main/data-processed)
+    [data-processed](https://github.com/european-modelling-hubs/covid19-forecast-hub-europe/tree/main/data-processed)
     folder
 
 ##### README contents

code/auto_download/check_revisions.R

@@ -19,7 +19,7 @@ target_variables <-
     Deaths = "inc death",
     Hospitalizations = "inc hosp")
 
-owner <- "covid19-forecast-hub-europe"
+owner <- "european-modelling-hubs"
 repo <- "covid19-forecast-hub-europe"
 path <- vapply(names(sources), function(x) {
   paste("data-truth", sources[[x]],

code/reports/country/country-report.Rmd

@@ -6,7 +6,7 @@ params:
   plot_weeks: 4
   report_models: "EuroCOVIDhub-ensemble"
   data_weeks: 10
-  config: "https://raw.githubusercontent.com/epiforecasts/covid19-forecast-hub-europe/main/project-config.json"
+  config: "https://raw.githubusercontent.com/european-modelling-hubs/covid19-forecast-hub-europe/main/project-config.json"
 output:
   html_document:
     theme: yeti

code/reports/hub/hub-report.Rmd

@@ -127,7 +127,7 @@ models |>
 ### Complete model information
 
 ```{r table-metadata}
-github_repo <- "epiforecasts/covid19-forecast-hub-europe"
+github_repo <- "european-modelling-hubs/covid19-forecast-hub-europe"
 team_df <-
   gh::gh(
     "/repos/{github_repo}/contents/{path}", 

code/reports/models/model-report.Rmd

@@ -6,7 +6,7 @@ params:
   data_weeks: "10"
   model: "EuroCOVIDhub-ensemble"
   report_models: "EuroCOVIDhub-ensemble"
-  config: "https://raw.githubusercontent.com/epiforecasts/covid19-forecast-hub-europe/main/project-config.json"
+  config: "https://raw.githubusercontent.com/european-modelling-hubs/covid19-forecast-hub-europe/main/project-config.json"
 output:
   html_document:
     theme: yeti

code/reports/rmdchunks/evaluation-footer.Rmd

@@ -1,6 +1,6 @@
 <!--- Footer about GitHub repository and where to find data for individual 
 models --->
 If you would like to learn more about a model, you can go the the
-[`data-processed` folder](https://github.com/epiforecasts/covid19-forecast-hub-europe) of the
-[European Forecast Hub GitHub repository](https://github.com/epiforecasts/covid19-forecast-hub-europe), select a model and access the metadata file with further
+[`data-processed` folder](https://github.com/european-modelling-hubs/covid19-forecast-hub-europe) of the
+[European Forecast Hub GitHub repository](https://github.com/european-modelling-hubs/covid19-forecast-hub-europe), select a model and access the metadata file with further
 information provided by the model authors.

code/reports/rmdchunks/ranking.Rmd

@@ -48,7 +48,7 @@ if ("n_loc" %in% colnames(df)) {
 if ("rel_wis" %in% colnames(df)) {
   cat("- The [weighted interval score](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008618) (WIS) is a [proper scoring rule](https://en.wikipedia.org/wiki/Scoring_rule#Propriety) (i.e., it cannot be \"cheated\") that is suited to scoring forecasts in an interval format. It generalizes the absolute error (i.e. lower values are better) and has three components: dispersion, underprediction and overprediction. Dispersion is a weighted average of the widths of the submitted prediction intervals. Over- and underprediction (overpred/underpred) penalties are added whenever an observation falls outside of a reported central prediction interval, with the strength of the penalty depending on the nominal level of the interval and how far outside of the interval the observation fell. Note that the average WIS can refer to different sets of targets for different models and therefore _cannot always be compared across models_. Such comparisons should be done based on the relative skill.  \n")
   cat("The Relative WIS (column `rel_wis`) is a relative measure of forecast performance which takes into account that different teams may not cover the exact same set of forecast targets (i.e., weeks and locations). Loosely speaking, a relative WIS of X means that averaged over the targets a given team addressed, its WIS was X times higher/lower than the the performance of the baseline model described in [Cramer et al. (2021)](https://www.medrxiv.org/content/10.1101/2021.02.03.21250974v1). Smaller values are thus better and a value below one means that the model has above average performance. The relative WIS is computed using a 'pairwise comparison tournament' where for each pair of models a mean score ratio is computed based on the set of shared targets. The relative WIS is the geometric mean of these ratios. Details on the computation can be found in [Cramer et al. (2021)](https://www.medrxiv.org/content/10.1101/2021.02.03.21250974v1).  \n")
-  cat("This metric is calculated for all models that provide a [full set](https://github.com/epiforecasts/covid19-forecast-hub-europe/wiki/Forecast-format#quantile) of quantiles.\n")
+  cat("This metric is calculated for all models that provide a [full set](https://github.com/european-modelling-hubs/covid19-forecast-hub-europe/wiki/Forecast-format#quantile) of quantiles.\n")
 }
 if ("rel_ae" %in% colnames(df)) {
   cat("- The Relative Absolute Error (column `rel_ae`) is the relative absolute error of the predictive point forecasts, that is the predicted value that individual forecasts deem the most likely. The relative AE is computed using a 'pairwise comparison tournament' where for each pair of models a mean score ratio is computed based on the set of shared targets. The relative AE is the geometric mean of these ratios. Details on the computation can be found in [Cramer et al. (2021)](https://www.medrxiv.org/content/10.1101/2021.02.03.21250974v1).\n")

renv.lock

@@ -111,7 +111,7 @@
       "Version": "0.0.0.9000",
       "Source": "GitHub",
       "RemoteType": "github",
-      "RemoteUsername": "covid19-forecast-hub-europe",
+      "RemoteUsername": "european-modelling-hubs",
       "RemoteRepo": "EuroForecastHub",
       "RemoteRef": "main",
       "RemoteSha": "404046706b0799a002969644e6e691b564f92fd1",
@@ -140,7 +140,7 @@
       "Version": "0.0.0.9000",
       "Source": "GitHub",
       "RemoteType": "github",
-      "RemoteUsername": "covid19-forecast-hub-europe",
+      "RemoteUsername": "european-modelling-hubs",
       "RemoteRepo": "HubValidations",
       "RemoteRef": "main",
       "RemoteSha": "b8759d465e77797fca9989eb4dfd4c5bf640feac",

schema-data.yml

@@ -2,7 +2,7 @@ $schema: "http://json-schema.org/draft-07/schema"
 title: ForecastHub model data
 description: >
   This is the schema of the forecasts files, please refer to
-  https://github.com/epiforecasts/covid19-forecast-hub-europe/wiki/Forecast-format
+  https://github.com/european-modelling-hubs/covid19-forecast-hub-europe/wiki/Forecast-format
   for more info.
 type: object
 properties:

schema-metadata.yml

@@ -2,7 +2,7 @@ $schema: "http://json-schema.org/draft-07/schema"
 title: ForecastHub model metadata
 description: >
   This is the schema of the metadata file, please refer to
-  https://github.com/epiforecasts/covid19-forecast-hub-europe/wiki/Metadata for
+  https://github.com/european-modelling-hubs/covid19-forecast-hub-europe/wiki/Metadata for
   more info.
 type: object
 properties: