2. Chiral nanostructures: detailed written and graphical descriptions of the synthetic protocols for nanostructure preparations. Typically, in Office and ChemDraw file (or equivalent) formats. CIF files for the description of crystal structure determinations 

  

  3. Thin film depositions: Office files for protocols; typically, in CSV, Origin or Excel files. Characterizations of the films involve photos taken by camera, optical microscope, scanning electron microscope, and transmission electron microscope. Involve image files (e.g. BMP, TIFF, JPG ...) and video files (e.g. MP4, AVI, MOV...) 

  

  4. Sensor array: CAD files, with defined schemas, shapes and dimensions of the prototypes’ parts (e.g. mechanical holders, transducers, microfluidic system, data storage, etc.) and their integration. 

  

  5. Measurements data: Frequency data and photoluminescence spectra. Typically, in CSV, Origin or Excel files. It can include image files (e.g. BMP, TIFF, JPG ...) and video files (e.g. MP4, AVI, MOV...). Data analyses in MatLab. 

    4. **Specify if existing data is being re-used (if any)**

  
  

  

  

No data, other than expertise from partners’ background (e.g. chiral
receptors, nanostructures and chemical sensors produced in the past), is being
re-used.

  5. **Specify the origin of the data**

  

  

All the data generated will be the product of the research carried out by the
partners in the framework of the INITIO project.

  6. **State the expected size of the data (if known)** **Type I: Design and fabrication details**

  

  

  * Synthetic protocols: 1MB – 100 MB per information file 

  

  * Chiral nanostructures: 10MB – 100 MB per information file 

  

  * Thin film depositions: 1MB – 100MB per process - Sensor arrays: 10MB – 1GB per file. 

  

  * Measurements data: 10MB – 1GB per file; 1MB – 1GB per image/video 

  

  * Data analysis: 1 MB – 1GB per experiments 

  

**1.7 Outline the data utility: to whom will it be useful**

The data will be used for internal validation of the processes, benchmarking
of the performances of the prototypes, and research on metrology and medical
applications.

It may also be useful for research institutions and companies working in the
field of chemical sensors, and environmental control as well; either for a
better understanding of the development and its performances or for
benchmarking and reproduction of the results.

#  FAIR data

**3.1 Making data findable, including provisions for metadata:**

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

Usually, the data will be self-document. When uploaded to public repositories
(e.g. European OpenAIRE repository), metadata might accompany it, to be
defined in further versions of the DMP.

**3.1.2 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?**

To be defined in further versions of the DMP, when the public repository
system will be fully defined.

**3.1.3 Outline naming conventions used.**

To be defined in further versions of the DMP, when the public repository
system will be fully defined. As a general rule, it should include information
related to the project, partner generating the data, serial number or date and
description of the dataset.

**3.1.4 Outline the approach towards search keyword.**

To be defined in further versions of the DMP, when the public repository
system will be fully defined.

**3.1.5 Outline the approach for clear versioning.**

Version control mechanisms should be established and documented before any
data are made openly public. During generation and collection, each partners
will follow its own internal procedures.

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

To be defined in further versions of the DMP, when the public repository
system will be fully defined. Metadata will be created manually by depositors
in the deposit form at the repository

**3.2 Making data openly accessible:**

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

**Type a), b), c), e) data will be made openly available.** In fulfillment of
project objectives, the consortium oversees any disclosure of scientific and
technical data made by the partners, in the form of summaries, conference
contributions, paper publications, online communications, etc. The content of
the approved communications is considered not confidential and its
communication is deemed beneficial for the achievement of the project
objectives. Consistently with this communication protocol, the consortium will
make public all the original datasets of Type **a), b), c), e) data** used to
prepare these public communications.

**Type II data will only be made openly available partially** . This is
necessary to protect the technological asset developed in the project. Any
public disclosure of the fabrication details of sensor devices would
jeopardize the chances of exploiting the technology, among the project
partners, in particular with SMEs participating to the project, or with third
parties.

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

Data will be made openly available in relation to an associated open access
publication. For each publication, the associated Type II data will be filed
together in a container format (e.g. zip, or tar). Information to relate each
data set with the corresponding figure, table or results presented in the
publication will be provided.

Data will be made openly available following the same time rules that apply to
the associated open access publication, e.g. in terms of timeliness, and
embargo.

**3.2.3 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)?**

Data will be made available in standard file formats that could be accessed
with common software tools. This will include, ASCII or Office files for
numeric datasets, and standard picture formats for images.

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

Details about the public repository system to be used will be fully defined in
further versions of the DMP. In deciding where to store project data, the
following choice will be performed, in order of priority:

  * An institutional research data repository, if available 

  

An external data archive or repository already established in the project
research domain (to preserve the data according to recognized standards)

  * The European sponsored repository: Zenodo (http://zenodo.org) 

  

  * Other data repositories (searchable here: re3data http://www.re3data.org/), if the previous ones are ineligible 

  

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

Data availability is categorized at this stage in one of two ways:

  * Openly Accessible Data [Type a), b), c) and e) associated to open access 

  

publication]: open data that is shared for re-use that underpins a scientific
publication.

  * Consortium Confidential data [Type d) data]: accessible to all partners within the conditions established in the Consortium Agreement. 

  

**3.3 Making data interoperable:**

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

  

  

Does not apply for the moment.

  2. **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?**

  

  

Does not apply for the moment.

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

  1. **Specify how the data will be licensed to permit the widest reuse possible**

  

  

The Openly Accessible Datasets will be licensed, when deposited to the
repository, under an Attribution-NonCommercial license (by-nc).

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

  

  

The Openly Accessible Datasets could be re-used in the moment of the open
publication.

  3. **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.**

  

  

Each archived Openly Accessible Dataset will have its own permanent repository
ID and will be easily accessible, and could be used by any third party under
by-nc license.

  4. **Describe data quality assurance processes.**

  

  

The repository platform functioning guarantees the quality of the dataset.

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

  

  

Openly Accessible Datasets will remain re-usable after the end of the project
by anyone interested in it. Accessibility may depend on the functioning of the
repository platform, and the project partners do not assume any responsibility
after the end of the project.

#  Allocation of resources

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

There are no costs associated to the described mechanisms to make the datasets
FAIR and long term preserved.

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

The project coordinator has the ultimate responsibility for the data
management in the Project. Each partner is requested to provide the necessary
information to compose the Openly Accessible Datasets in compliance of the
terms defined in the DMP agreed by the consortium.

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

Does not apply for the moment.

#  Data security

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

Data security will be provided in the standard terms and conditions available
in the selected repository platform.

#  Ethical aspects

**6.1 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.**

Does not apply for the moment.

#  Other

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

The project data and documentation are also stored in the project intranet,
which is accessible to all project partners.