#  Executive Summary

AIMS-2-TRIALS is a project bringing together multiple stakeholders, including
autistic people themselves and their families, to support the development of
new therapies and a better understanding of challenges impacting both quality
and length of life. This document is a first draft of a data management plan
for the project, and is intended to be a living document. It describes how the
data collected by the project will be made findable, accessible, interoperable
and reusable under field-wide best practices as well as all relevant regional,
national, and international law.

#  Introduction

The AIMS-2-TRIALS project brings together autistic people and their families,
academic institutions, charities and pharmaceutical companies to study autism
and provide an infrastructure for developing and testing new therapies. In
line with the autism community’s priorities, the consortium will also focus on
why some autistic people develop additional health problems that severely
impact both quality and length of life.

The purpose of data collection within the project is to begin to address a
number of challenges facing individuals with Autism Spectrum Disorder (ASD).
In particular, with the data collected by AIMS-2-TRIALS we aim to enable a
precision medicine approach to better target treatments to patients through
the use of validated stratification biomarkers, and by testing novel or
repurposed drugs in a highly trained European-wide clinical trials network for
ASD that links to other international efforts. To fully achieve these goals,
the data collected by the consortium needs to be findable, accessible,
interoperable and reusable (FAIR) and soundly managed.

To that end, this document describes the Data Management Plan (DMP) for
AIMS-2-TRIALS and is based on the Guidelines on FAIR Data Management in
Horizon 2020 document version 3.0 of 26 July 2016. The AIMS-2-TRIALS DMP
describes the data management life cycle for the data to be collected,
processed and generated within the project. Strategies to guarantee good data
management are also provided.

This DMP initial release includes a collection of the first ideas from the
AIMS-2-TRIALS partners and as the project will evolve and progress, the
consortium will produce a second (to be issued in Month 24) and a third (to be
issued at the end of the project, Month 60) release in order to include the
applied procedures in terms of methodology and the exhaustive group of data
collected processed and generated by the project.

#  Data Summary

The data of AIMS-2-TRIALS are new data and data collected during the EU-AIMS
project (grant no. 115300). The data from EU-AIMS were stored by CEA and have
been transferred to INSPAS mid-2018.

The dataset includes questionnaires, eCRF, and analysis results (brain
imaging, genetics, electrophysiology eye-tracking, and neuropsychological
data). The dataset is composed of collected data sent by the different
partners of the consortium and of processed data generated by INSPAS or the
core analytics groups. These processed data are made available to the
consortium members after access is granted.

Currently, the data are in the state left by the CEA at the end of the EU-AIMS
project and transferred to INSPAS mid-2018.

Data formats are detailed in Table 1.  
  
<table>  
<tr>  
<th>

**Data type**

</th>  
<th>

**Collected**

</th>  
<th>

**Processed**

</th> </tr>  
<tr>  
<td>

Questionnaires, eCRF,

Clinical data

</td>  
<td>

json

</td>  
<td>

json, csv, xlsx

</td> </tr>  
<tr>  
<td>

Genomics

</td>  
<td>

Fastq, bam, vcf

Genotyping final report

</td>  
<td>

bam, vcf g.vcf

</td> </tr>  
<tr>  
<td>

MRI

</td>  
<td>

DICOM

</td>  
<td>

NIFTII

</td> </tr>  
<tr>  
<td>

EEG

</td>  
<td>

csv, matlab, vhdr, vmrk, eeg

</td>  
<td>

csv, matlab

</td> </tr>  
<tr>  
<td>

MRS

</td>  
<td>

NIFTI

</td>  
<td>

LCModel output

</td> </tr>  
<tr>  
<td>

Eye-tracking

</td>  
<td>

csv, matlab

</td>  
<td>

csv, matlab

</td> </tr> </table>

Table 1. Data format for collected and processed data for each type

The expected size of the data is 1PB.

The data are collected to be made available to all the consortium members that
have been granted access by one or several core analytics groups. For the
AIMS-2-Trials project the data from the EU-AIMS project are re-used. These
data that were hosted by the CEA had been transferred to INSPAS mid-2018.

#  FAIR Data

##  Data discoverability (metadata provision)

No DOI are yet assigned to the data. The clinical data are stored into a
database integrated to Padawan using the FHIR standard. Wherever possible,
metadata will be coded using standard dictionaries and ontologies (e.g. HPO,
HL7). In case metadata standards do not exists, they will be created following
the guidelines of the  _Clinical & Phenotypic Data Capture _ _Work Stream_ of
the  _Global Alliance for_ _Genomics & Health (GA4GH) _ .  The data and
metadata will be indexed regularly and made searchable through a faceted
search interface compliant with the  _Discovery Work Stream_ of the GA4GH.

##  Data identifiability

Each participant is assigned a identification number (PSC1) in each
investigative center. After transfer of the data to INSPAS the PSC1 code is
double-coded by conversion to a PSC2 code. In each questionnaire file, the
participant data can be found using this PSC2 code. Experiment files
(genetics, brain imaging, etc) of each participant are stored in a folder
named by this PSC2 code. The PSC2 is also added as a keyword for each file.
Other keywords describing the type of data are also added to each file. BIDS
format will be used for magnetic resonance imaging data, and other field-wide
standards will be used as appropriate.

Version numbers will be included for processed data. The possibility to
include version numbers for raw data is currently being evaluated.

##  Making data openly accessible

###  Data availability

During the project the data are shared only to consortium members. After the
project the data will be shared with researchers outside the project. These
data will be shared outside the consortium by integration with other
international efforts (e.g. EU ELIXIR), including the use of platforms for
data integration (e.g. GA4GH federated credentialing and tranSMART) that allow
federation and open access. This will include how best to enable the data to
be findable such as the eTRIKS IMI project data catalogue.

Data which can not be shared in raw format due to sensitivity, regulatory
reasons, or because of a lack of participant consent will only be shared to
the fullest extent possible under relevant law. Access may require recipients
to consent to a data sharing agreement (particularly in light of GDPR, and
other local regulations as relevant).

###  Data location and accessibility

The data are hosted in Paris into the storage facility of INSPAS. At INSPAS,
the data are stored into Padawan, a data warehouse developed internally at
INSPAS. The data are accessible through a website connected to Padawan. A
simple web browser is enough to access and download the data for authorized
researchers. Documentation and source code of Padawan and the website are not
accessible.

The repository containing the data is saved on a daily basis. The recovery
system is tested multiple times every year.

###  Data restriction

Access to the data is restricted during the project. Access is granted to
researchers from the consortium by Core Analytics Groups, depending of the
type of data is required. Access policies for data collection will be
constructed to respect data use restrictions specified by the consent with
which the data were obtained. Consent will be digitally coded and attached as
metadata using the system described  _here_ as a foundation. In the future,
access to datasets may be streamlined through the integration of the systems
described  _here_ ,  for identity concentration and federation, and  _here_ ,
for algorithmically making access decisions based on user identity and access
policies. At the first connection an authorized user will have to accept Terms
and Conditions of the service. Identity of the researcher will be ascertained
by a login/password system.

##  Making data interoperable

Questionnaires files and clinical data are stored in text files and in the
FHIR standard into the Padawan database. The experiments results are stored in
standardized format suitable to the data type (see Table 1). Data will be
shared according to current standards in the community (e.g., NIFTI for
magnetic resonance imaging data).

##  Increase data re-use (through clarifying licenses)

###  Data licensing

At the end of the project, data will be shared across a global federated
network with tiered access to data and metadata, following the model laid out
by the Beacon network and GA4GH.

###  Reusability

Some data might not be shared because of their sensitivity or regulatory
reasons (eg. personal data with no consent for sharing outside the
consortium). The choice of the participant will in all cases be respected.

**Data quality assurance process**

When receiving the data from the CEA, a data integrity check has been
performed.

#  Allocation of resources

The AIMS-2-Trials Project Manager at INSPAS is responsible for data management
of the project. The cost of the data management and for making data FAIR is
covered by the AIMS-2-Trials grant.