diff --git a/fast-sim-and-analysis/EventProduction.md b/fast-sim-and-analysis/EventProduction.md
index db25cde9..8a3f82c4 100644
--- a/fast-sim-and-analysis/EventProduction.md
+++ b/fast-sim-and-analysis/EventProduction.md
@@ -12,7 +12,7 @@ running central production of events requires specific rights
 
 When samples produced by the [EventProducer](https://github.com/HEP-FCC/EventProducer)
 framework are ready they will appear on this
-[web-page](http://fcc-physics-events.web.cern.ch/).
+[web-page](https://fcc-physics-events.web.cern.ch/).
 :::
 
 
diff --git a/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimAnalysis/Readme.md b/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimAnalysis/Readme.md
index 7b665b60..16fc5ead 100644
--- a/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimAnalysis/Readme.md
+++ b/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimAnalysis/Readme.md
@@ -1123,13 +1123,13 @@ fccanalysis plots plots_flavor.py
 
 ## Advanced
 
-1) To evaluate the impact of detector performance, smear the neutral hadron resolution in the `ReconstructedParticlesNoMuons` collection and check the impact on the dijet invariant mass resolution. An example can be found [here] (https://github.com/HEP-FCC/FCCAnalyses/blob/master/examples/FCCee/smearing/smear_jets.py): 
+1) To evaluate the impact of detector performance, smear the neutral hadron resolution in the `ReconstructedParticlesNoMuons` collection and check the impact on the dijet invariant mass resolution. An example can be found [here] (https://github.com/HEP-FCC/FCCAnalyses/blob/master/examples/FCCee/smearing/smear_jets.py):
 
 2) Now smear the impact parameter resolution and evaluate the imapct on the efficiency of selecting two B-tagged jets or two C-tagged jets. 
 
 3) **This part can only be on lxplus and for people having the access rights to eos and the analysis dictonary**
 In order to produce plots with more statistics using centrally produced samples, we could use already processed large statistics samples.
-To do so we re-run the pre-selection over 10 percent of the total statistics [here](http://fcc-physics-events.web.cern.ch/fcc-physics-events/Delphesevents_spring2021_IDEA.php).
+To do so we re-run the pre-selection over 10 percent of the total statistics [here](https://fcc-physics-events.web.cern.ch/FCCee/spring2021/Delphesevents_IDEA.php).
 Add to your a `analysis_stage1.py` file
 
 ```python
diff --git a/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimAnalysis/finalSel.py b/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimAnalysis/finalSel.py
index 5f4eb8b6..4560be38 100644
--- a/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimAnalysis/finalSel.py
+++ b/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimAnalysis/finalSel.py
@@ -5,7 +5,7 @@
 baseDir  = ""
 
 ###Link to the dictonary that contains all the cross section informations etc...
-procDict = "https://fcc-physics-events.web.cern.ch/fcc-physics-events/data/FCCDicts/FCCee_procDict_spring2021_IDEA.json"
+procDict = "https://fcc-physics-events.web.cern.ch/data/FCCDicts/FCCee_procDict_spring2021_IDEA.json"
 process_list=['p8_ee_ZZ_ecm240','p8_ee_WW_ecm240','p8_ee_ZH_ecm240']
 
 ###Dictionnay of the list of cuts. The key is the name of the selection that will be added to the output file
diff --git a/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimVertexing/Readme.md b/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimVertexing/Readme.md
index 2329b351..dc04b249 100644
--- a/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimVertexing/Readme.md
+++ b/fast-sim-and-analysis/fccanalyses/doc/starterkit/FccFastSimVertexing/Readme.md
@@ -784,7 +784,7 @@ The files `analysis_Tau3Mu_stage1.py`, `myAnalysis.h` and `myAnalysis.cc` with a
 
 5. We now have a simple analyser that can be used to process the signal and background samples, and plot the mass of the $\tau \rightarrow 3\mu$ candidates. For that we need to process the full statistics. In order for you to have access to `/afs/cern.ch/work/f/fccsw/public/FCCDicts/`, we need to add you CERN login to an afs group. If not already provided, please do so.
 
-All samples that have been centrally produced can be found [on this web page](http://fcc-physics-events.web.cern.ch/fcc-physics-events/FCCee/index.php). We use `spring2021` samples (in `Production tags`), and the files made with `IDEA`. If you enter `TauMinus2MuMuMu` and `TauMinus2PiPiPinus` in the search field, you will see the datasets produced for the signal anf the $\tau \rightarrow 3\pi \nu$ background. The first column shows the dataset names, in this case `p8_noBES_ee_Ztautau_ecm91_EvtGen_TauMinus2MuMuMu` and `p8_noBES_ee_Ztautau_ecm91_EvtGen_TauMinus2PiPiPinu`.
+All samples that have been centrally produced can be found [on this web page](https://fcc-physics-events.web.cern.ch/FCCee/). We use `spring2021` samples (in `Production tags`), and the files made with `IDEA`. If you enter `TauMinus2MuMuMu` and `TauMinus2PiPiPinus` in the search field, you will see the datasets produced for the signal anf the $\tau \rightarrow 3\pi \nu$ background. The first column shows the dataset names, in this case `p8_noBES_ee_Ztautau_ecm91_EvtGen_TauMinus2MuMuMu` and `p8_noBES_ee_Ztautau_ecm91_EvtGen_TauMinus2PiPiPinu`.
 
 To run fccanalyses over these datasets (and not anymore over one test file), the list of datasets to be processed should be inserted in your `examples/FCCee/tutorials/vertexing/analysis_Tau3Mu_stage1.py` :