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04_qms.Rmd
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04_qms.Rmd
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# Integration in QMS {qms}
## Start a new project
**Before starting with a new project**, perform the following actions that are
detailed in the following sections:
* Choose a [project identifier](#project-identifier) and identifiers for the
project partners and organisations that data are expected to be received from.
* Create a [data management plan (DMP)](#data-management-plan) for the project.
* Determine a ["data manager"](#data-manager) for the project.
* Setup the [folder structures](#folder-structures) for the project.
**At the start of a research project**:
* Create a subfolder for your project and subfolders for the organisations
in the [rawdata folder structure](#rawdata-folder-structure).
**At the start of a project** (or if an employee or trainee enters the project):
* Give an introduction to our research data management as described in this
document.
**Regularly during the project**:
* Check if the folder structure within your project's rawdata subfolder still
complies with the [rawdata folder structure](#rawdata-folder-structure) and
clean the structure, if not.
### Project and owner identifiers {-#project-identifier}
Documents and data that are collected or created during the lifetime of a
project will be stored in the form of electronic files on the institute's file
server or on the personal computers of the employees. We aim at being able to
clearly identify the related project and the owner of the data for any file or
folder that resides on the institute's file system.
Therefore, we recommend to use unique identifiers, either as (part of) the
name of the file or as (part of) the name of the folder or parent folder that
the file resides in. The usage of a consistent project identifier becomes
particularly important when - as defined we suggest for a good [data workflow](#data-workflow),
different types of data and documents of the project are stored at different places
on the file system.
Together with the team members, the project leader is requested to define the
project identifier at the start of the project. Whenever the belonging of a file or
folder to the project is to be indicated, only this "official" identifier in
the exact spelling that was defined, has to be used.
The project identifier should
* be unique within all identifiers of current or former projects that have ever
been carried out at the institute,
* be as short as possible but as long as required to be meaningful and easy to
remember.
In order to minimise the risk of spelling mistakes and to avoid errors in
automated processing we require the identifier to
* start with a lowercase letter,
* consist of only lowercase letters (`a-z`), digits (`0-9`) or the hyphen (`-`),
* end with a lowercase letter or digit,
* consist of at least four and at last 16 letters,
* not contain two hyphens in sequence (`--`).
Examples for valid project identifiers are:
* `sema-berlin-2`
* `aquanes`
* `ist4r`
Invalid project identifiers are:
* `sema-berlin_2` (has underscore)
* `Aquanes` (has uppercase letters)
* `4you` (starts with a digit)
* `abc` (does not have at least four letters)
* `this-project-name-is-too-long` (has more than 16 letters)
The project identifier is not to be confused with the project acronym or project
title as it has been aggreed on by the project consortium during the project
development.
We propose to document the choice of project identifier, project acronym and
project title in a [project's metadata file](#file-projects). This will be
described in another chapter of this document.
For data that are received from external partners or organisations we recommend
to indicate the origin of the data by means of another type of identifier in the
names of the corresponding files and folders. The same strict naming convention
as for the project identifiers should be applied to these institutional
identifiers that are to be documented in another special [metadata
file](#file-organisations). At the start of a project it should be checked if
the organisations that are expected to receive data from are listed in this
metadata file. If not, the metadata file is to be extended as necessary.
### Data Management Plan {-#data-management-plan}
Data Management Plans (DMP) document the type of data that is expected to be
acquired or generating during the life time of a project. The DMP will show you
and your colleagues how this data is described, analyzed and stored and how you
intend to share and preserve the data after the project has ended. The DMP will
help you to formalize data handling processes and discloses potential weaknesses
in your project. The overall goal of a DMP is to comply with the FAIR principles
that will make your data:
* **F**indable
* **A**ccessible
* **I**nteroperable
* **R**eusable
The DMP gives information on how you intend to make the data findable with
metadata and standard identification mechanism (e.g. a
[DOI](https://en.wikipedia.org/wiki/Digital_object_identifier)). This is achieved
through e.g. repositories and usage of metadata standards. The DMP also contains
adequate documentation and necessary tools needed to access the data. You are
aware that the DMP needs to balance openness on one hand and protection of
scientific information, commercialisation and Intellectual Property Rights (IPR)
on the other hand. If certain datasets cannot be shared, provide a clear reason
why.
Interoperability enables data exchange and re-use between researchers and across
institutions and also requires standardised [metadata](#metadata) and methodologies.
Reusability of data requires the data to be tagged with a [license](#licenses)
that clarifies how data can be re-used.
Please note that data management is a dynamic process, hence the DMP requires
regular adaptations during the course of a project. It is therefore strongly
recommended to announce a `data manager` who takes over responsibility for any
data management related issues. Please use DMP online to create the DMP.
[DMP online](https://dmponline.dcc.ac.uk/) is a tool with a lot of tips and links
that will construct your DMP according to the funder requirements. It will guide
you through the whole DMP process in a threefold process (initial, detailed and
the final DMP).
The costs for data management are eligible for most funders. The write up of an
initial DMP will cost you between 1 hour and 1 day of work, depending on nature
of your project and the data that is acquired.
Data should normally be provided in a non-proprietary format (for example .csv
Your organisation is coordinating a proposal for a EU H2020 call and requires a
DMP. You can inform the consortium members that each member has opt-out possibilities
at application phase, during grant agreement preparation and after signature of
the grant agreement.
Look through a (Research) Data Management Planning (DMP) checklist, e.g. here:
[DMP checklist](http://www.dcc.ac.uk/resources/data-management-plans/checklist)
If the project's funding organisation demands a Data Management Plan, use the
template that is provided by the funder. You find different DMP-templates (e.g.
that required for European Horizon 2020 projects) here:
[DMP Online](https://dmponline.dcc.ac.uk/).
### Responsibilities of the Data Manager {-#data-manager}
The `data manager` is responsible for:
* saving raw data in the `rawdata` network folder (see below). The data manager
gets a special login account with write-access to the `rawdata` folder. The login
information can be got from [Michael Rustler](https://www.kompetenz-wasser.de/en/ueber-uns/team-2/?search-employee-grid=michael%20rustler) or [Hauke Sonnenberg](https://www.kompetenz-wasser.de/en/ueber-uns/team-2/?search-employee-grid=hauke%20sonnenberg), the members of
the FAKIN project team.
* regularly checking if both the file and folder names as well as the folder
structure comply with the best practices described in this document and with the
naming conventions aggreed on at the start of the project. The data manager curator
checks if metadata files are available and up-to-date.
### Setup folder structures {-}
At the start of the project, define and create folder structures for the three
areas `rawdata`,`processing`, `results` that we propose in this document.
Create the folders and provide a metadata file (see below) describing their
meaning. In addition to the general recommendations given in this document,
create and document naming conventions for files and folders for your project.