#  FAIR DATA

3.1. Making data findable, including provisions for metadata:

  * **Outline the discoverability of data (metadata provision)**

  

  * **Outline the identifiability of data and refer to standard identification mechanism. Do you make use of persistent and unique identifiers such as Digital Object Identifiers?**

  

  * **Outline naming conventions used**

  

  * **Outline the approach towards search keyword**

  

  * **Outline the approach for clear versioning**

  

  * **Specify standards for metadata creation (if any). If there are no standards in your discipline describe what metadata will be created and how**

  

The two datasets will be identified using two unique identifiers (DOI) by
uploading them onto a public repository. Data discoverability will be
facilitated by adding a data description with keywords related to potential
users (e.g. developers of new analysis tools), as described above.

For the Phantom dataset, different updated measurement sessions are possible
depending on updated versions of the prototype. Conversely, for the Clinical
dataset a single measurement session is foreseen, since there is no provision
to recall back the same patient. Different versions of analysis are possible,
depending on the update of the analysis tools. Therefore, the versioning will
foresee a first number for the raw data acquisition (only for phantoms) and a
second number for the analysis.

Naming conventions will be specified in a more advanced version of the DMP
foreseen at month 24 of the SOLUS Project, and still before the actual data
collection (starting after month 24).

Apart from clinical images (e.g. US images) for which the DICOM standard is
usually adopted, there are no specific standards for optical data. In general,
we will create metadata files in XML, embedding large binary data in XML with
Base91 encoding.

3.2. Making data openly accessible:

  * **Specify which data will be made openly available? If some data is kept closed provide rationale for doing so**

  

  * **Specify how the data will be made available**

  

  * **Specify what methods or software tools are needed to access the data? Is documentation about the software needed to access the data included? Is it possible to include the relevant software (e.g. in open source code)?**

  

  * **Specify where the data and associated metadata, documentation and code are deposited**

  

  * **Specify how access will be provided in case there are any restrictions**

  

Data will be made "as open as possible, as closed as necessary". In this
respect, all data described above will be made open apart from:

  * algorithms for data analysis which could be considered for IP protection 

  

  * personal data subject to privacy protection as foreseen in the clinical protocol (Deliverable D5.1) and ethical provisions. 

  

Final decisions on these two aspects and specific identification of closed
data, or data subject to specific embargo related to IP policies will be taken
in the updated DMP at month 24. Related access policies will be defined at due
time.

All specifications required to access the data will be inserted in the data
repository. The segmentation of US images, and in general the extraction of
optical properties for suspect lesions/inhomogeneities require advanced
analysis tools, generally pertaining to the methods of inverse problems in
diffuse optics. If already published or not involved in IP protections, the
algorithms will be described in detail to permit replications. Inclusion of
software tools for data processing will be considered if not causing
significant overburden distracting important energies from the fulfilment of
the project aims.

A three-phase process for data storage is foreseen. Initially, data will be
collected by the SOLUS prototype and stored locally on the instruments, while
other information will be gathered by clinicians and recorded on paper (as
described in Deliverable D5.1). In the second phase, all collected data will
be stored at POLIMI data warehouse, apart from protected clinical information
which will be retained at Ospedale San Raffaele. This will permit construction
of the database and initial tests on analysis. In the third phase, when data
acquisition is complete, data will be uploaded on an open repository. At
present, the choice is for Zenodo, because of perfect match with requirements,
and increased interest in the International community. Still final decision
will be taken close to the actual deposition (not earlier than m36) to take
into account the updated status of public repositories.

3.3. Making data interoperable:

  * **Assess the interoperability of your data. Specify what data and metadata vocabularies, standards or methodologies you will follow to facilitate interoperability.**

  

  * **Specify whether you will be using standard vocabulary for all data types present in your data set, to allow inter-disciplinary interoperability? If not, will you provide mapping to more commonly used ontologies?**

  

The realm of clinical optical data is at present not covered by standards or
specific vocabularies. The numerosity of the clinical study limits its
potential use mainly to researchers and operators within the field. The
definition of metadata and in particular the fields in the XLM will match the
vocabularies most often covered by scientific publications in diffuse optics.

3.4. Increase data re-use (through clarifying licenses):

  * **Specify how the data will be licenced to permit the widest reuse possible**

  

  * **Specify when the data will be made available for re-use. If applicable, specify why and for what period a data embargo is needed**

  

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

  

  * **Describe data quality assurance processes**

  

  * **Specify the length of time for which the data will remain re-usable**

  

Licensing policies will be defined later (around M24) when the general
dissemination, IP protection and exploitation policies are more clearly drawn.

Typically, a 6-12 months embargo after acceptance of relevant publications can
be considered.

Data will be made available and reusable through open data repositories for
periods of 10 years.

#  ALLOCATION OF RESOURCES

**Explain the allocation of resources, addressing the following issues:**

  * **Estimate the costs for making your data FAIR. Describe how you intend to cover these costs**

  

  * **Clearly identify responsibilities for data management in your project**

  

  * **Describe costs and potential value of long term preservation**

  

Since data deposit in a local data warehouse and an external repository will
not start earlier than 2 years from now, cost estimate will be performed at
due time since policies and costs are rapidly changing under great internal
and external pressure on data preservation and sharing. In general terms, it
is highly probable that no extra-costs will be incurred for the storage of
data since the overall dimension of data will be handled by standard POLIMI
data facilities and fit in the free allowances of Zenodo repository. Dr Andrea
Farina is responsible for the coordination of the overall data management.

#  DATA SECURITY

**Address data recovery as well as secure storage and transfer of sensitive
data**

The second phase of data storage will be perfomed internally at a data
warehouse of POLIMI and at Ospedale San Raffaele for protected clinical
information. No access external to the consortium will be possible.

The actual data repository in force for the research group at POLIMI is stored
in secure hard-drives provided by a redundant system (RAID 5) that is backed
up every week by an incremental back-up script (rsbackup) to other external
servers. The data servers are located in the basement of the Physics
Department of Politecnico di Milano in a restricted access area. The data
servers have an access controlled by passwords, and they are part of a VLAN
without access from outside the POLIMI institution. The VLAN at which not only
the data servers are connected but all the PCs used for this project is part
of an institutional network protected by a firewall. We note that POLIMI group
has a proven track-record in long-term data storage and access going back to
the 80s.

In the final phase, the public repository will be chosen to grant requirements
of long-term secure storage. The most probable choice - Zenodo - already
fulfils all requirements.

Sensitive data - mostly personal data of the clinical study - will not be
shared and will be stored only at Ospedale San Raffaele to comply with the
privacy policies foreseen in the clinical protocol.

#  ETHICAL ASPECTS

**To be covered in the context of the ethics review, ethics section of DoA and
ethics deliverables. Include references and related technical aspects if not
covered by the former**

The Clinical protocol (Deliverable 5.1 - Definition of the clinical protocol -
produced at M3) and the ethical requirements in terms of protection of
personal data (Deliverable D5.2 - Approval of clinical protocol by ethical
committee - due at M36) set specific requirements for anonymization of data
and protection of personal data of patients. These requirements will be
strictly followed and will prevent sharing of some part of information.

All data stored at POLIMI data warehouse and deployed at public repository
will be completely anonymized.

The patient information and consent will follow the guidelines set forth in
ISO 14155 for patient information and informed consent, and will imply also
sharing of data excluding sensitive data.

#  OTHER

**Refer to other national/funder/sectorial/departmental procedures for data
management that you are using (if any)**

At present, the main local procedures for data management are related to the
requirements of sensitive data protection described in the clinical protocol
(Deliverable D5.1) and operated by Ospedale San Raffaele. No other
prescriptive procedures are identified so far. However, since local policies
are rapidly evolving to cope with the increased demand for Open Data and Data
Management, this section will be updated in a future release (M24) to describe
the actual situation.