#  INTRODUCTION

PD_manager voluntarily (since it was not approved under one of the thematic
areas for which it was obligatory) explored the flexible pilot under Horizon
2020 called the Open Research Data Pilot (ORD pilot). The ORD pilot aims to
improve and maximise access to and re-use of research data generated by
Horizon 2020 projects and takes into account the need to balance openness and
protection of scientific information, commercialisation and Intellectual
Property Rights (IPR), privacy concerns, security as well as data management
and preservation questions.

The scope of this document is to answer all questions related to FAIR ** 1  **
data management and provide information about PD_manager compliance with FAIR
principles. In general terms, research data should be 'FAIR', that is
findable, accessible, interoperable and reusable. These principles precede
implementation choices and do not necessarily suggest any specific technology,
standard, or implementation-solution.

#  DATA SUMMARY

_What is the purpose of the data collection/generation and its relation to the
objectives of the project?_

Data were collected in two phases for the project needs:

  1. During the 1  st  year of the project (Sep – Dec 2015) the involved partners (IRCCS Fondazione Ospedale San Camillo, IRCCS Santa Lucia Foundation and University of Ioannina - UOI) have gathered preliminary data from 20 patients (in total) affected by Parkinson’s disease, both in ON and OFF state in order to feed the research of WP4 for the detection and evaluation of symptoms and the detection of fluctuations. Useful data about the usability and wearability of the devices and the feasibility of the recordings in daily in-hospital and out-hospital settings were also collected. 

  

  2. During the last year of the project (July 2017-Mar 2018) the involved partners 

  

  

(IRCCS Fondazione Ospedale San Camillo, IRCCS Santa Lucia Foundation,
University Of Ioannina and University of Surrey) conducted a non-blinded
parallel two group randomized controlled pilot study in which, 133 patients
have been enrolled, of which 75 have been assigned and tested to the
PD_manager group, while 58 have been assigned and tested to the control group
(clinical diaries).In both groups the duration was 2 weeks and the main
outcomes were: to assess (1) the acceptability and usability of the PD_manager
system, compared to traditional practices for Patients and Caregivers (dyads)
and (2) the Usefulness of intervention/value of the information provided by
PD_manager for decision making with respect to patient management, its
acceptability in clinical practice and the confidence/reliability in the
information (clinicians).

_What types and formats of data the project generated/collected?_

The data from the 1  st  phase were:

  * Clinical information (baseline) 

  

  * UPDRS items (not all of them) for annotation 

  

  * raw data from the MS Band sensors: 3-axis accelerometer, gyroscope, steps, heart rate and skin temperature 

  

  * raw data from the BQ Aquaris sensors: 3-axis accelerometer, gyroscope 

  

  * raw data from insoles: 3-axis accelerometer, pressures, steps 

  

  * video of the whole protocol for annotation 

  

  * cognitive battery usability questionnaire 

  

  * wearability questionnaire 

  

  * user needs questionnaire 

  

The data from the 2  nd  phase were:

  * Clinical information (baseline) 

  

  * UPDRS for annotation 

  

  * raw data from the MS Band sensors: 3-axis accelerometer, gyroscope, 

  

  * raw data from the BQ model M sensors: 3-axis accelerometer, gyroscope 

  

  * raw data from insoles: 3-axis accelerometer, pressures, steps 

  

  * Features from motor symptoms manifested in legs captured with the sensor insole. 

  

  * Features from motor symptoms manifested in upper limbs captured with the wristband 

  

  * Activity and sleep data from the wristband (it was optional and only a few patients could activate it) 

  

  * Speech quality (sound analysis, language deficit) captured with the smartphone microphone 

  

  * Data for non-motor symptoms and impulsivity through questionnaires on smartphone 

  

  * Cognitive status data captured with cognitive monitoring app 

  

  * Data on mood with smartphone app 

  

  * Adherence to medication data with the mobile app 

  

_Will you re-use any existing data and how?_

The 2  nd  phase data will be reused for studying fluctuations and developing
a more sophisticated method.

The 2  nd  phase data will also be reused for validating the data mining
studies we have conducted (correlation of H&Y with UPDRS) and for further
validating DSS (clinicians decision against PD_manager suggestion).

Raw data from 2  nd  phase can also be reused from project partner for
building new methods for motor symptoms monitoring and evaluation since they
cover more days and different algorithms can be applied.

_What is the origin of the data?_

During the 1st phase a total of 20 patients were recruited (n.10 by IRCCS
(IT), n.5 by Fondazione Santa Lucia (IT), n.5 by UOI (GR)).

During the 2  nd  phase 133 people with Parkinson’s disease (n=133, with 133
caregivers) have been enrolled into the study through clinical centers in
England (n=21, i.e. 10 each from

Royal Surrey NHS Hospital Trust in Guildford and St Peter’s NHS Hospital Trust
in Chertsey, Surrey), Greece (n= 20, Ioannina) and Italy (n= 41, IRCCS
Fondazione Ospedale San Camillo - Venice, and n= 50, IRCCS Fondazione Santa
Lucia - Rome).

_What is the expected size of the data?_

For 1  st  phase each “. go" file (Moticon software) that includes all raw
data and the video for all 8 sessions of the patient, all synchronized, and is
compressed, is around 350 MB. However, the separate files for each patient are
between 2 and 3 GBs because of the videos.

Since videos cannot be shared the shared dataset will be just a few MBs.

For 2  nd  phase the data size is around 3 GB for each patient.

_To whom might it be useful ('data utility')?_

PD Researchers; Researchers in signal processing; Researchers in medical data
mining

#  FAIR DATA

##  Making data findable, including provisions for metadata

_Are the data produced and/or used in the project discoverable with metadata,
identifiable and locatable by means of a standard identification mechanism
(e.g. persistent and unique identifiers such as Digital Object Identifiers)?_

NO, but DOI versioning in Zenodo is straightforward in case it is decided to
upload the data in a public repository

_What naming conventions do you follow?_

Name of the organization_patient_nr (2 digits)

e.g. UOI_patient_01

_Will search keywords be provided that optimize possibilities for re-use?_

Parkinson’s, Parkinson’s Disease, sensor data, UPDRS annotation etc.

_Do you provide clear version numbers? What metadata will be created?_

Even though there aren’t any versions, the dates of data recordings are
available. Moreover, the protocol description will be available for
researchers

_In case metadata standards do not exist in your discipline, please outline
what type of metadata will be created and how._

The data collection protocols will be provided as metadata (always if that
option is selected) since they complement the information needed to use the
PD_manager data. The protocols are already described in detail in deliverables
4.1 and 6.1 and 6.2 respectively.

##  Making data openly accessible

_Which data produced and/or used in the project will be made openly available
as the default? If certain datasets cannot be shared (or need to be shared
under restrictions), explain why, clearly separating legal and contractual
reasons from voluntary restrictions. Note that in multi-beneficiary projects
it is also possible for specific beneficiaries to keep their data closed if
relevant provisions are made in the consortium agreement and are in line with
the reasons for opting out._

PD_manager will probably opt-out from making some of its data openly
available.

The reasons are:

  * For the 2  nd  phase dataset the consent we have is for use only for the purpose of the pilot study and just for other related purposes within the project. 

  

  * For the 1  st  phase dataset commercial exploitation is still explored for some of the modules. 

  

However, even at a next stage the 1  st  phase consent forms enable the
consortium to change that decision and all necessary steps for streamlining
the process (approval) and especially the access (repositories) to data have
been made. Below the PD_manager data access Board is presented.

_How will the data be made accessible (e.g. by deposition in a repository)?_

A version of CKAN (ckan.org) was deployed within the project (currently
running on  _http://195.130.121.50/_ )  . CKAN is a data management system
that makes data accessible – by providing tools to streamline publishing,
sharing, finding and using data.

_What methods or software tools are needed to access the data?_

Approval from the PD_manager Board is necessary. For processing the data
Matlab or any similar software is needed. The synchronized data can be
accessed without any additional effort using Moticon (www.moticon.de)
proprietary software.

_Is documentation about the software needed to access the data included?_

Nothing additional. You need to know how Matlab or Moticon software works.

_Is it possible to include the relevant software (e.g. in open source code)?_

Two open source alternatives to Matlab could be:

  1. GNU Octave (  _www.gnu.org/software/octave/_ ) 

  

  2. Scilab (  _www.scilab.org_ ) 

  

  

_Where will the data and associated metadata, documentation and code be
deposited? Preference should be given to certified repositories which support
open access where possible._

Initially, in an SFTP server running on University of Ioannina infrastructure.

Zenodo (zenodo.org) also is a good choice, especially now that it linked with
Github that we have used during the mobile apps development.

_Have you explored appropriate arrangements with the identified repository?_

No need to, Zenodo features and policies cover our needs. Specifically:

It supports DOI versioning; uploads gets a Digital Object Identifier (DOI) to
make them easily and uniquely citable

It supports Flexible licensing

It is integrated with GitHub that was used within PD_manager for the
development

They currently accept up to 50GB per dataset (one can have multiple datasets);
there is no size limit on communities.

All research outputs from all fields of science can be stored: publications
(book, book section, conference paper, journal article, patent, preprint,
report, thesis, technical note, working paper, etc.), posters, presentations,
datasets, images (figures, plots, drawings, diagrams, photos), software,
videos/audio. i.e. all the types of data in PD_manager

Zenodo was launched within an EU funded project, the knowledge bases were
first filled with EU grants codes

The data is stored in CERN Data Center. Both data files and metadata are kept
in multiple online and independent replicas. CERN has considerable knowledge
and experience in building and operating large scale digital repositories and
a commitment to maintain this data center to collect and store 100s of PBs of
LHC data as it grows over the next 20 years. In the highly unlikely event that
Zenodo will have to close operations, they guarantee that they will migrate
all content to other suitable repositories, and since all uploads have DOIs,
all citations and links to Zenodo resources (such as PD_manager data) will not
be affected.

_If there are restrictions on use, how will access be provided?_

Through the UOI SFTP server.

_Is there a need for a data access committee?_

Yes, we have patient data and we need to know the intended data use and the
purpose of the studies.

_Are there well described conditions for access (i.e. a machine readable
license)?_

NO

_How will the identity of the person accessing the data be ascertained?_

Probably an official letter from the organization in which the person studies/
works will be requested in addition to any documentation is typically
requested by the person himself.

##  Making data interoperable

_Are the data produced in the project interoperable, that is allowing data
exchange and reuse between researchers, institutions, organisations,
countries, etc. (i.e. adhering to standards for formats, as much as possible
compliant with available (open) software applications, and in particular
facilitating re-combinations with different datasets from different origins)?_

YES

_What data and metadata vocabularies, standards or methodologies will you
follow to make your data interoperable?_

Those provided by ZENODO

_Will you be using standard vocabularies for all data types present in your
data set, to allow inter-disciplinary interoperability?_

The data models are named according to the indications of FHIR – Fast
Healthcare Interoperability Resources (hl7.org/fhir) which is the next
generation standards framework created by HL7.

_In case it is unavoidable that you use uncommon or generate project specific
ontologies or vocabularies, will you provide mappings to more commonly used
ontologies?_

We already adopted FHIR.

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

_How will the data be licensed to permit the widest re-use possible?_

To be defined. In any case:

  1. We will only provide data that has been de-identified 

  

  2. the patients that participated in the PD_manager studies are fully informed and provided their consent that access to their de-identified data can be granted in the future for specific scientific purposes 

  

  

_When will the data be made available for re-use? If an embargo is sought to
give time to publish or seek patents, specify why and how long this will
apply, bearing in mind that research data should be made available as soon as
possible._

The final decision should be made in 3 years after the end of the project,
i.e. by March 2021.

_Are the data produced and/or used in the project useable by third parties, in
particular after the end of the project? If the re-use of some data is
restricted, explain why._

They could be re-used under specific conditions.

_How long is it intended that the data remains re-usable?_

In case they are made openly available there will be no time restriction.

_Are data quality assurance processes described?_

Yes.

#  ALLOCATION OF RESOURCES

_What are the costs for making data FAIR in your project?_

They are minor since they include only server maintenance costs or zero in
case we upload in Zenodo

_How will these be covered? Note that costs related to open access to research
data are eligible as part of the Horizon 2020 grant (if compliant with the
Grant Agreement conditions)._

They are indirect costs covered by the University

_Who will be responsible for data management in your project?_

A board consisting from one representative from each organization (permanent
staff) and led by Prof Angelo Antonini. The other members are:

Prof D Fotiadis from UOI

Prof MT Arrendondo from UPM

Prof G Spalletta from IRCCS Santa Lucia Foundation

Prof H Gage from University of Surrey

Dr D Miljkovic from JSI

Dr A Marcante from IRCCS San Camillo Hospital

Dr I Chkajlo from URI

Dr R Vilzmann from Moticon

Dr H Hatzakis from B3D

Dr M Rafaelli from Live

_Are the resources for long term preservation discussed (costs and potential
value, who decides and how what data will be kept and for how long)?_

A final decision will be made by March 2021 from this Board.

#  DATA SECURITY

_What provisions are in place for data security (including data recovery as
well as secure storage and transfer of sensitive data)?_

Information will be kept in locked filing cabinets and password protected
computers, in a room with restricted access at the University of Ioannina.

Back up will be kept in an external hard disc locked in the same room.

Moreover, the final FTP will be SFTP (SSH File Transfer Protocol) which also
protects against password sniffing and man-in-the-middle attacks. It protects
the integrity of the data using encryption and cryptographic hash functions
and authenticates both the server and the user.

_Is the data safely stored in certified repositories for long term
preservation and curation?_

Zenodo allows up to 50 GB per dataset which means we can upload there the
complete 1  st  phase dataset and split the 2  nd  phase dataset in 2-3 parts.

#  ETHICAL ASPECTS

_Are there any ethical or legal issues that can have an impact on data
sharing? These can also be discussed in the context of the ethics review. If
relevant, include references to ethics deliverables and ethics chapter in the
Description of the Action (DoA)._

Yes, there are. The data were collected from consenting patients that were
fully informed that their de-identified data may be sued for research also
after the end of the project. Details about the protocol and the information
sheets and consent forms are provided in the Ethics Deliverables.

_Is informed consent for data sharing and long term preservation included in
questionnaires dealing with personal data?_

YES.

For the 1  st  phase the consent included the following statements from the
patients:

  * I understand that all data collected during the study, may be looked at for monitoring and auditing purposes by authorized individuals working for, or reviewing the outcomes of the PD_manager project from regulatory authorities where it is relevant to my taking part in this research. I give permission for these individuals to have access to my records. 

  

  * I agree for my anonymised data and/or samples to be shared with the EU PD_Manager project partners 

  

  * I agree for my anonymised data and/or samples to be shared with other scientists conducting relevant research from outside the PD_manager project if this is the decision of the PD_manager project committee. 

  

For the 2nd phase the consent included “I consent to my personal data being
used for the study as detailed in the information sheet. I understand that all
personal data relating to volunteers is held and processed in the strictest
confidence, and in accordance with the Data Protection Act (1998).”

According to the information sheet: “The information collected will be
analysed to meet the aims of the study. Under no circumstances will any of
your personal details be passed onto third parties or appear in any reports on
this study.”

The data, anonymised

The data sharing and ownership policies are the same across the datasets and
are in accordance with the Consortium Agreement (v. 3, 01/01/2015) as well the
data access procedures and rights in relation to the data gathered through the
whole PD_MANAGER project.

For any data sharing request that will be issued – which focuses on analysing
data collected within the project for different purposes – after the approval
from the PD_manager board, the Principal Investigator will be asked to submit
his research purpose to the competent ethical committee and receive approval
to get access to the data.

#  OTHER ISSUES

_Do you make use of other national/funder/sectorial/departmental procedures
for data management?_

NO

_If yes, which ones?_

Not applicable

#  FURTHER SUPPORT IN DEVELOPING YOUR DMP

The Research Data Alliance provides a Metadata Standards Directory that can be
searched for discipline-specific standards and associated tools.

The EUDAT B2SHARE tool includes a built-in license wizard that facilitates the
selection of an adequate license for research data. Useful listing of
repositories include:

  * Registry of Research Data Repositories 

  

  * Some repositories like Zenodo, an OpenAIRE and CERN collaboration), allow researchers to deposit both publications and data, while providing tools to link them. 

  

  * Other useful tools include DMP online and platforms for making individual scientific observations available such as ScienceMatters.