Differences

This shows you the differences between two versions of the page.

--- rdms:workflows:archiving [2025/02/28 11:27] – [Prerequisites] removed red jelte
+++ rdms:workflows:archiving [2025/03/06 09:19] (current) – unstructured to unbundled jelte
@@ Line 1: / Line 1: @@
 {{indexmenu_n>2}}
 ====== Archiving Workflow ======
+{{ :rdms:workflows:rdms_archiving_workflow_wiki.svg |}}
-{{ :rdms:workflows:rdms_archiving_workflow.png?direct&800 |}}
+The archiving workflow in the RDMS allows the owner of a [[rdms:solution:projects|RDMS Project]] to archive the data contained in the project folder by following a step-by-step process in the web interface. An archive in the RDMS is **a bundled dataset**, called //data package//, that contains both data and related metadata, and has been **frozen by making it read-only** in the system. The archive is by default **labelled with a creation date** to inform the user of when the data was frozen. The archived dataset (data package) can then be pushed to the publication workflow (**still in development**), which will allow the publishing of the dataset metadata to the outside world, in compliance with the Open Science framework.
-The archiving workflow is the process of creating a bundled dataset, called //data package// in the RDMS, from a [[rdms:solution:projects|RDMS Project]] in a structured way. The archived dataset (data package) is then ready for the publication workflow (which is the process of publishing the metadata to the outside world to comply with the Open Science framework). **Currently, the publication workflow is under development.**
+During the archiving process, there are **three different roles** that will be active at different times.
-During the archiving process, there will be **three different roles** that will be active at different times.
 **Owner/Admin:**
@@ Line 17: / Line 16: @@
 This role is responsible for verifying and completing the metadata information related to the archive. Best practice is to assign this role to the person(s) who know the origin and scope of the data.
-A single user can have any number of these roles assigned to them, and/or multiple users can have different roles and work at different stages of the archiving process.
+A single user can have any number of these roles assigned to them, and/or multiple users can have the same or different role(s) and work at different stages of the archiving process. The important part is that each role is assigned to at least one user, otherwise the workflow cannot be completed.
-This section will furthermore explains, the workflow starting from an already existing RDMS project including its different steps and the active roles. It will also elaborate more on the content of the created datapackage.
+===== Steps of the Archiving Workflow =====
-===== Steps of the Archiving Workflow =====
+This section will explain the workflow starting from an already existing RDMS example project and walk you through the requirements to start the workflow, the different steps, and the roles active at each step. It will also elaborate more on the content of the created //data package//.
-This section explains in details the different steps of the archiving workflow, including the requirements that need to be fulfilled to start it. An example project will be used to guide step-wise through the whole workflow.
 ==== Prerequisites ====
 === Existing Project ===
-To start an archiving workflow, the first prerequisite is that there is an already existing RDMS Project which also contains some data from which the workflow can be started.
+To start an archiving workflow, the first prerequisite is that the RDMS Project you want to archive **must** already exist. The project also needs to **contain data**. An empty project will result in an error after the first step of the workflow.
 === Using the Web Interface ===
-Using the archiving workflow requires using the [[rdms:webapp:|RDMS web interface]]. It is not possible to execute the workflow via CLI, e.g. iCommands.
+The archiving workflow requires using the [[rdms:webapp:|RDMS web interface]]. It is not possible to execute the workflow via CLI, e.g. iCommands.
 === Correct User Privileges ===
-The RDMS account of the project admin needs the correct, elevated permissions to be able to assign user roles and start the archiving workflow. If you lack these privileges, please contact [[rdms-support@rug.nl|rdms-support@rug.nl]].
+If you want to start an archiving workflow as a project admin, you need the correct, elevated permissions to start the workflow and be able to assign user roles (data manager and metadata manager). If you lack these permissions, please contact [[rdms-support@rug.nl|rdms-support@rug.nl]]. The easiest way to check if you have the correct permissions is to check if you can assign roles to users in the project management tab.
-For the other involved roles, metadata and data manager, no special privileges are needed, but the respective role should have read/write permission in the project.
+For the other involved roles, metadata and data manager, no special permissions are needed, but they should have at least read/write permission in the project. If this is not the case, the workflow does not allow them to modify or approve the data (metadata).
 === Assigning Roles ===
-Before starting an archiving workflow, it is is recommended to assign the desired workflow roles for the RDMS Project. The can be done by the owner of the project via the data management tab.
+If you know that you have the right permissions, then we recommend that you assign the desired workflow roles for the RDMS Project before starting an archiving workflow. You can do this, as the owner of the project, via the data management tab.
 {{ :rdms:workflows:rdms_workflow_adding_roles.png?direct&800 |}}
-By clicking on pencil symbol next to the name of an existing project member, their project [[rdms:data:permissions|permissions]] as well as project roles can be adjusted (see best practices below).
+By clicking on the pencil symbol next to the name of an existing project member, their project [[rdms:data:permissions|permissions]] as well as project roles can be adjusted (see below for best practices).
 {{ :rdms:workflows:rdms_workflow_adding_roles_2.png?direct&600 |}}
-After the roles are assigned, the archiving workflow can continue, starting with the initialization of a new workflow by the project admin.
+After the roles are assigned, the archiving workflow can either start with the initialization of a new workflow by the project admin or continue from where it left off before the required roles were assigned.
 **Notes:**
-  * To assign a user as project admin, select 'own' permission. Please note that the user needs elevated privileges to be able to act as project admin. In cases where this is needed, please contact [[rdms-support@rug.nl|rdms-supprt@rug.nl]].
+  * To assign a user as project admin, select the 'own' permission. Please note that the user needs elevated privileges (having 'own' is not enough) to be able to act as project admin. In cases where this is needed, please contact [[rdms-support@rug.nl|rdms-supprt@rug.nl]].
-  * To assign a user role, the user need to have at least 'read' permission in the project.
+  * To assign a user role, the user needs to have at least 'read' permission in the project.
-  * Also see the section about best practices with some info about how these roles could be assigned in a smart way.
+  * The section about best practices gives useful information on how these roles could be assigned in a smart way.
@@ Line 57: / Line 55: @@
 <hidden>
 **Active role**: Project Admin\\
-**Via sidebar item**: [[rdms:webapp:datamanagement|Data Management tab]] or [[rdms:workflows:start|Workflows tab]].
+**Prerequisites**: Project to be archived exists, Project folder contains data.\\
-The first step after all prerequisites are fulfilled  is the initialization of the workflow.
+This first step is the initialization of the archiving workflow. The project admin can start it from two places in the RDMS, either via the [[rdms:webapp:datamanagement|Data Management tab]] or the [[rdms:workflows:start|Workflows tab]].
-The project admin can do this via two places in the RDMS, either via the data management or via the workflows tab.
+----
-To initialize via the data management tab, open the respective project in the tab, then open the menu in the top-right corner (cogwheel symbol) and select //Archive data//.
+To initialize the workflow via the data management tab, open the respective project in the tab, then open the menu in the top-right corner (cogwheel symbol) and select //Archive data//, as shown below.
 {{ :rdms:workflows:rdms_workflow_init_2.png?direct&600 |}}
-A new pop-up window  will open where the project data from which the project should be initialized can be selected.
+In the new pop-up window that will open, select the project data that you wish to archive. When you are done selecting the data you wish to archive, click the arrow at the bottom of the window to move to the next step.
 {{ :rdms:workflows:rdms_workflow_init_1.png?direct&600 |}}
-After the data was selected, the arrow button in the top-left corner will redirect to another page that shows an overview of the selected data. Moreover, it allows to specify a version tag for the created archiving workflow. The default tag is of the format ''archive<Timestamp>'' with the timestamp being the [[https://en.wikipedia.org/wiki/Unix_time|Unix time]] when the archiving workflow was initialized, but it can be customized by the user.
+You will be redirected to another window that shows an overview of the selected data. The window also allows to specify a version tag for the created archiving workflow. The default tag is of the format ''archive<Timestamp>'' with the timestamp being the [[https://en.wikipedia.org/wiki/Unix_time|Unix time]] when the archiving workflow was initialized, but it can be customized by the user.
 {{ :rdms:workflows:rdms_workflow_init_4.png?direct&600 |}}
+After clicking //Archive data//, you have completed this part of the workflow. Look to "Step 2" in this page for the next part.
+----
-To initialize via the workflows page, open the than, then select "Archiving" from the menu. Using the cogwheel button in the top-right corner, the "Archive new data" option can be used to initialize a new archiving workflow. This will open a new pop-up where you can specify the project from which you want to initialize and let's you select the data an assign a version tag.
+If you want to initialize the workflow directly in the workflows tab, open the tab in the sidebar menu and select "Archiving". Using the cogwheel button in the top-right corner, you can click on the "Archive new data" option to initialize a new archiving workflow. This will open a new pop-up window where you can specify the data that you wish to archive from a selected project. As described above, you will be able to assign a version tag to the data you wish to archive (see screenshots above).
 {{ :rdms:workflows:rdms_workflow_init_5.png?direct&600 |}}
+----
 **Notes:**
   * The version tag can't be adjusted by the user afterwards. Please take this into account when adjusting this value.
+  * If you adjust the archive name, it is still recommended to keep a timestamp of some sorts ([[rdms:bestpractices|usual naming recommendations]] apply).
   * While the project admin can already select data during initialization, more data can be added or removed in the next step. This can be done by the data manager.
 **Special considerations**:
-When you start the archiving process, you will be prompted to select the folders or files you want to archive. In this step, you can decide if you want to archive the entire project folder or just a part of it. Most of the time, you will select the entire folder. However, there are cases where part of the archive needs to be deleted before the customary retention period (10 years), due to privacy regulations. In such cases, we advise you to create two archives: one containing normal data that should be stored for 10 years, the other containing the sensitive data that needs to be deleted earlier. A good practice would be to label both archives in a way that makes it clear that they are interlinked and which one contains the sensitive data. This is best done in the project folder before the archiving starts. Please contact [[rdms-support@rug.nl|rdms-support@rug.nl]] if your data belongs to these special cases and you are unsure how to use the archiving workflow in such cases.
+When you start the archiving process, you will be prompted to select the folders or files you want to archive. In this step, you can decide if you want to archive the entire project folder or just a part of it. Most of the time, you will select the entire folder. However, there are cases where part of the archive needs to be deleted before the customary retention period (10 years), due to privacy regulations.\\
+In such cases, we advise you to create **two archives**: **one containing normal data** that should be stored for 10 years, the **other containing the sensitive data** that needs to be deleted earlier. A good practice would be to label both archives in a way that makes it clear that they are interlinked and which one contains the sensitive data. This is best done in the project folder before the archiving starts. Please contact [[rdms-support@rug.nl|rdms-support@rug.nl]] if your data fits what we just described and you are unsure how to use the archiving workflow in such cases.
 </hidden>
@@ Line 92: / Line 96: @@
 <hidden>
 **Active role**: Data Manager\\
-**Via sidebar item**: [[rdms:workflows:start|Workflows tab]].
+**Prerequisites**: Step 1 has finished, project folder is not empty.\\
-In this step, the data manager checks if the data,  that is contained in the project folder and that is sent to the archiving stage, is complete and uncorrupted. If the data manager confirms that all is good, the data is copied to a separate folder in the projects's archive located at ''/rug/home/DataArchive/Projects/<projectname>/''.
+In this step, the data manager checks if the data sent to be archived is complete and uncorrupted. If the data manager confirms that all is good, the data is copied to a separate folder in the projects archive, located at ''/rug/home/DataArchive/Projects/<projectname>/''.
-The data manager can do this steps via the workflows tab in the web interface where the available archiving workflows are listed.
+----
-As the workflow was just started by the project admin, the newly created workflow is found on the first stage called "Prepare data". The respective workflow can be identified by the version tag that was assigned by the project admin.
+As data manager, you can do this step via the workflows tab in the web interface, where the available archive drafts are listed in the archiving workflow page. After the project admin initializes the workflow, you can find the newly created archive draft in the first column, labelled "Prepare data". The drafts are organized into cards and you can identify the respective archive draft by the version tag that was assigned by the project admin in the previous step. At the top of each card, you can find a button with three vertical dots which you can use to execute different tasks on the selected workflow. See the screenshot below for the location of the button and the options available to you.
 {{ :rdms:workflows:rdms_workflow_dataprep_1.png?direct&600 |}}
-At the top of the cards of the respective workflow, the button with the three vertical dots can be used to reveal the menu that allows the data manager to execute different tasks on the selected workflow.
+If you select the //Append data// option, you will be able to add data to the archive. Selecting this option will also open a new window, where you will be guided through adding data. Use this option if the project admin did not add all the data necessary to the archive at the previous step.\\
+After all data was added, you can click on the //Prepare data// option to get a view of the currently selected data in a new window. In this window, you can verify that the data that needs to be archived is correct and complete, but you can also remove data again. Additionally, you can select an option that will allow you to add [[rdms:metadata:|RDMS metadata]] to the archive. What we mean here is that you will be adding metadata that was added to files and folders included in the archive, not that you are adding metadata **about** the archive. This will happen in a later step.
 {{ :rdms:workflows:rdms_workflow_dataprep_2.png?direct&600 |}}
-The "Prepare data" function opens a view of the currently selected data. It also allows to select if [[rdms:metadata:|RDMS metadata]], meaning metadata that was added to files/folders that are included in the archive, should be included in the final archive (<color #ed1c24>see below for a description of the final archived package</color>).
+\\
+\\
-The "Append data" option allows the data manager to add more data that was not included by the project admin during initialization.
+Finally, once you are ready, click on the //Copy data to archive// option to move the archive draft to the next step. A window will open, where you can verify the data sent to archive once again. If you decide to approve the data in this window, then the archiving workflow will start copying your data from the project space to the projects' data archive.
 {{ :rdms:workflows:rdms_workflow_dataprep_3.png?direct&600 |}}
+During the copying of the data, the archiving workflow is blocked. You can see that the workflow is still busy by checking if the yellow frame around a card is still blinking. After the copying is finished and the yellow frame disappears, you can continue the workflow with the following step, the creation of the data package. If the workflow runs into an error, it will display a red frame around the card once it stops.
-If all was checked and missing data was added, the "Copy data to archive" function can be used to get once more an overview of all the selected data, and then to copy the data from the project space to the projects' data archive.
 {{ :rdms:workflows:rdms_workflow_dataprep_4.png?direct&600 |}}
-During the copying of the data, the archiving workflow is blocked which can be clearly seen by visual indicator. After the copying is finished, the workflow can continue with the following step, the creation of the data package.
 </hidden>
-==== Step 4: Creation of the Data Package ====
+==== Step 3: Creation of the Data Package ====
 <hidden>
 **Active role**: Data Manager\\
-**Via sidebar item**: [[rdms:workflows:start|Workflows tab]].
+**Prerequisites**: Step 2 has finished.
-In this step, the previously unstructured data that was moved to the project's archive space in the RDMS is bundles to a so called data package. This data package is a tar file containing the selected data as well as RDMS metadata that was available if the option to export metadata was selected (color #ed1c24>see below for a description of the final archived package</color>)
+In this step, the previously unbundled data that was moved to the project's archive space in the RDMS is bundled to a so called **data package**. This data package is a tar file containing the selected data, as well as RDMS file and folder metadata if the option to export it was selected in the previous step.
+----
+This step should be a short one if the data is in order. It is mostly implemented to make sure that if there are more than one data manager, they have the ability to check what the other data managers did. If you did implement our suggestion of having one data manager with final say, then this step is where they get to do a last check. In this step, you have the option to //Preview data//, to //Create data package//, and to //Prepare data// (see screenshot below).
 {{ :rdms:workflows:rdms_workflow_dp_2.png?direct&600 |}}
-This is again done via the workflows tab by the data manager. The options on this step of the workflow are previewing of the data if an additional check is needed and creation of the data package.
+If you select //Preview data//, a window will show you the data contained in the archive draft. At this stage, the data package has not been created yet and data can still be freely added to the archive. If you wish to add more data, select //Prepare data// to move the card back a step. Add the necessary data to the archive draft, then move the card back to the //Data package// column.
 {{ :rdms:workflows:rdms_workflow_dp_1.png?direct&600 |}}
-If the creation of the data package is selected, the system will automatically bundle the previously unstructured data into a tar archive. Afterwards, the next step (adding metadata to data package) can follow.
+If you select the //Create data package// option in the menu, the RDMS system will automatically bundle the previously unbundled data into a tar archive. Afterwards, the next step (adding metadata to data package) can follow.
 {{ :rdms:workflows:rdms_workflow_dp_4.png?direct&600 |}}
-**Notes**: It is not possible to add more data via the workflows page in this step. If the data manager sees that wrong data was selected, the "Prepare data" function can be used which puts the workflow to the previous step, preparation of the data, where the content can be adjusted.
+**Notes**: As mentioned above, you cannot directly add more data via the workflows page in this step. If you or another data manager sees that wrong data was selected or that data is missing, then you have to select the //Prepare data// option, which will move the workflow back to the previous step. There, you can adjust the content of the archive draft before moving it back to the current step.
 </hidden>
-==== Step 5: Add/Approve Metadata ====
+==== Step 4: Add/Approve Metadata ====
 <hidden>
-**Active role**: (Meta)data Manager
+**Active role**: Metadata Manager and Data Manager\\
+**Prerequisites**: Step 3 is finished, (a DOI for the data set exists).
-After the data package was successfully created, metadata can be added to the data package. Also, if it exists, a [[https://en.wikipedia.org/wiki/Digital_object_identifier|DOI]] of an existing, related publications can be added to the data package.
+In this step, metadata about the archive can be added to the data package, after the data package was successfully created. Also, **if it already exists**, a [[https://en.wikipedia.org/wiki/Digital_object_identifier|DOI]] of a related publications can be added to the data package.
-While the RDMS in general allows to add metadata with or without a metadata template, the archiving workflow only allows do add metadata via templates. This is done to help standardizing the metadata for archives projects and therefore make it better findable. Templates can be created by users and also shared with others. If there is no suitable metadata template present, you will therefore have to create one as described in the [[rdms:metadata:metadatatemplates|Metadata Template section of the wiki]].
+----
+While the RDMS in general allows the user to add metadata with or without a metadata template, the archiving workflow only allows to add metadata via templates. This is done to help standardize the metadata for archived projects and therefore make them better findable. Templates can be created by users and also shared with others. If there is no suitable metadata template present, you will therefore have to create one, as described in the [[rdms:metadata:metadatatemplates|Metadata Template section of the wiki]]. Nevertheless, please remember that you are adding metadata about the archive during this step, not about the single files and folders within it. As such, you might not need too much complexity when it come to the metadata template you want to use.\\
+\\
+As in previous steps, the three dots menu holds all the actions you can perform at this stage. They are, in order, //Add DOI//, //Add metadata template//, //Approve metadata//, and //Data package//. If you are data manager, you can move the archive draft back to the previous step. We do not expect you to have to do it, but last minutes changes to a data set could still happen. This is why you still have the option to edit the data.
 {{ :rdms:workflows:rdms_workflow_meta_3.png?direct&600 |}}
-In this step, a metadata template can be selected and metadata can be added. This can be done by either the data manager or the metadata manager.
+If you select //Add metadata template//, you will see a new window open. At the very top of the window, you can choose which template you want to fill in. Then you can select or type in the different metadata entries the template requires you to add. This step allows for both metadata, as well as data, managers to add metadata.
 {{ :rdms:workflows:rdms_workflow_meta_2.png?direct&600 |}}
-Also, a DOI can be added if there exists a publication to which the data is related. The DOI will be verified to be valid in this step. Please note the correct format of the DOI to be specified (DOI format: ''prefix/suffix'', **not** URL).
+If you already have generated a DOI for the dataset, then you can use the //Add DOI// menu button to insert the existing DOI into the metadata of the archive. You can also add a DOI linked to a related publication in this stage of the archiving workflow. The RDMS will check the DOI and will verify its validity. Please note that the correct format of the DOI to be specified is ''prefix/suffix'', **not** URL.
 {{ :rdms:workflows:rdms_workflow_meta_1.png?direct&600 |}}
-Now, the metadata role becomes active and the metadata manager has to check and approve the metadata. Note that a link was automatically added as metadata entry for the DOI.
+The last option in the menu we have not yet addressed is //Approve metadata//. This action is **available only to the metadata manager**. If you or other metadata managers have checked that the metadata has been filled in properly, then you can press the button //Approve metadata// to move the archive draft to the final stage of the archiving workflow. Note that a DOI link was automatically added as metadata entry, if a DOI was specified.
 {{ :rdms:workflows:rdms_workflow_meta_4.png?direct&600 |}}
-If all looks good, the last step of the workflow can follow.
 </hidden>
-==== Step 6: Move Data Package to Archive ====
+==== Step 5: Move Data Package to Archive ====
 <hidden>
 **Active role**: Data Manager\\
-**Via sidebar item**: [[rdms:workflows:start|Workflows tab]].
+**Prerequistes**: Step 4 is finished, data and metadata are complete.
-At this stage, nearly all is set, but a last confirmation is needed by the data manager to finish the workflow. In this step, which is again done via the workflows tab.
-The data manager can either put the workflow back to the add/confirm metadata stage or use the "Archive" button to finish the workflow.
+In this step, a last confirmation is needed by the data manager to finish the workflow, if everything has been set up properly. This is the last step of the workflow and a **point of no return**.
-{{:rdms:workflows:rdms_archiving_appove_1.png?800|}}
+----
-This will present once more all the info about the archived data package, its final destination as well all metadata that will be added.
+At this stage of the archiving workflow, you have two options left as the data manager. You can either push the archive draft back to the add/confirm metadata stage by pressing //Metadata//, because some things are still missing, or press the //Archive// button to create the final archive and finish the workflow.
-{{:rdms:workflows:rdms_archiving_appove_2.png?800|}}
+{{ :rdms:workflows:rdms_archiving_appove_1.png?direct&800 |}}
-If the data manager agrees with all that, using the "Archive" button will finalize the workflow.
+Pressing //Archive// will open a new window one last time, presenting all the info about the archived data package, its final destination, as well all metadata that will be added tot he archive. If everything looks good, you can use the //Archive// button to finalize the workflow.
-The data package can now be found at its final destination including all the metadata that was added during the workflow.
+{{ :rdms:workflows:rdms_archiving_appove_2.png?direct&800 |}}
+When the operation is finished, you can find the data package in its final destination, as shown in the screenshot below. The archive will contain all the data added during the workflow, as well as all the metadata. For an explanation of the structure of the archive, please look to the next section.
+{{ :rdms:workflows:rdms_archiving_approve_3.png?direct&800 |}}
-{{:rdms:workflows:rdms_archiving_approve_3.png?800|}}
 </hidden>
 ===== The Data Package and its Content =====
-At the end of the archiving workflow, a so called data package is created. This is the name in the RDMS for a data set with a specific structure that resulted from the archiving workflow.
+At the end of the archiving workflow, you will have created a **data package**. In the RDMS, we use this term to identify a data set with a specific structure that resulted from the archiving workflow. In this section, we will have a more detailed look at the data package and explain its internal structure.
-In this section, we will have a more detailed look at the data package and explain its internal structure.
 In general, the following applies:
   * The created data package is always in a structured ''*.tar'' format which is a standard format for bundling data that can be opened with different tools.
-  * Inside the tar, there are different subfolders for the selected and archived data as well as the information about the metadata that was available for the included data in a separate folder in ''*.json'' format. The second folder with the metadata info is only created if it was selected during the archiving workflow (step 2) that RDMS metadata should be included in the created data package. Otherwise this folder does not exist.
+  * Inside the tar, there are different subfolders for the selected and archived data, as well as the information about the metadata on files and folders included in the archive, saved in ''*.json'' format. This second folder with the metadata info is only created if you selected to include metadata during step 2 of the archiving workflow. Otherwise, you will only see the folder containing the data.
-In our case where we selected metadata to be included and where we had only one data folder selected to be included in the archive, our archive has in the end the following structure after being downloaded and extracted locally:
+In our example case, we selected metadata to be included and one folder containing the data. Thus, our archive has the following structure in the end:
 <code>
-# This is the general structure of the created datapackge after being extracted
+# This is the general structure of the created data package after being extracted.
 archive1740649820/                            # This is the name (version tag) of the archive that we specified during the workflow
 ├── 2025_2_27_10_51_11_889000000              # Subfolder that contains the selected (meta)data
-│   └── Some_project_data                     # This is the folder from which we started the workflow. Below it is content (not completely shown)
+│   └── Some_project_data                     # This is the folder from which we started the workflow. Below is its content (not completely
-│       └── LA-187-1
+│       └── LA-187-1                          # shown)
 └── RUGRDMS_METADATA                          # As we selected in the example to have metadata included, we get this folder as well
-    └── 1Some_project_data.metadata.json      # This is the available metadata for the "Some_project_data" folder in json format.
+    └── 1Some_project_data.metadata.json      # This is the available metadata for the "Some_project_data" folder in .json format.
 </code>
-If we have a look at the json file with the metadata, we see that it contains info about the metadata that was available for the selected data. The following is a snippet of that file that shows how this info is exported and included in the data package.
+If we have a look at the JSON file with the metadata, we see that it contains info about the metadata related to the selected data, not the one related to the archive. The following is a snippet of that file that shows how this info is exported and included in the data package.
 <code>
@@ Line 258: / Line 269: @@
 ===== Best Practices =====
-This section elaborates on how the project and its roles can be setup to spread the different tasks in the workflow efficiently. It will also give some more info about best practices in the context of the project archiving workflow.
+This section explains our suggestions on how you can set up the roles in the project to more efficiently spread the tasks of the workflow among project participants. It will also give some more information about best practices in the specific context of the project archiving workflow.
-In general, these is how the roles could be assigned in a project:
+In general, this is how the roles could be assigned in a project:
-  * **Project Admin**: This role should be taken by the project lead. This is the person that manages the project (permissions, roles, etc.) and is also the only one that can start the workflow. Other than that, this roles does not need to take additional steps in the workflow.
+  * **Project Admin**: This role should be taken by the project lead. This is the person that manages the project (permissions, roles, etc.) and is also the only one that can start the workflow. Other than that, this role does not need to take additional steps in the workflow.
-  * **Data Manager**: As this role verifies that all data that should be archived is included during the workflow, it makes sense to assign this role to the person that is most familiar with the data. In the case of a simple research project that could be the main researcher that produces that data. Of course, it is also possibly to assign multiple data managers if the project needs multiple people to check that the data is correct, but one has to take the lead in the end to confirm the correctness and move the workflow to the next step. The data manager can also add metadata in the following step which also makes sense if this role is assigned to the main researchers of the project. They likely now best what should be included as metadata.
+  * **Data Manager**: As this role verifies that all data that should be archived is included during the workflow, it makes sense to assign this role to the person that is most familiar with the data. In the case of a simple research project that could be the main researcher that produced that data. In cases where **multiple people are familiar with different parts of the data**, we recommend assigning the data manager role to each person, so they can individually verify the integrity of their part of the data. Since it is possible to assign multiple data managers, we also suggest to discuss beforehand **who will have final say** in the workflow, as only one approval is needed to move to the next step. The data manager can also add metadata in the following step of the workflow, but cannot approve the metadata.
-  * **Metadata Manager**: The main role of the metadata manager is to confirm that the metadata that was entered is correct. It makes sense to assign this role to another user, not the same that added the metadata. For a project/research group that has staff that takes care of the data management, it makes sense to assign this role to that person. Moreover, it is also possible that the metadata manager does both, adding the metadata and also approving it.
+  * **Metadata Manager**: The main role of the metadata manager is to confirm that the metadata associated to the archive is correct and complete. We suggest assigning this role to a person in the project that has knowledge of the data, but that has not been involved in previous workflow steps. If no such person exists, then a data manager is also suited for this role. If you had multiple data managers in previous steps, we suggest appointing a data manager that did not have final say over the data set to this role. If your project/research group has staff that takes care of the data management, we suggest assigning them to metadata manager.
-As already mentioned above, it is also possible to give the data and metadata manager role to the same person. In this cases, the whole workflow, except the initialization, can be done by a single user. This is also a valid possibility, but it should be mentioned that the "checks and balanced" that the archiving workflow introduces via its different roles is then minimized.
+As already mentioned above, multiple roles can be assigned to the same user. If a user is both data and metadata manager, then the whole workflow, except the initialization, can be done by that single user. This is also a valid possibility, but we suggest you make use of the "checks and balances" that the archiving workflow introduces by assigning roles to different users, where possible.