**Executive Summary**

This is the first version of the Data Management Plan, which explains the
methods used to manage the data generated within the ChipScope project and the
criteria and methods agreed between partners to make them openly accessible,
in fulfillment of the Open Data obligations defined in the Grant Agreement.
The document will be updated every 12 months until the end of the project.

  1. **Data summary**

    1. **State the purpose of the data collection/generation**

  
  

  

  

The research activities of the ChipScope project will generate data of two
types:

**Type I: Design and fabrication details:** This data relates to the
fabrication of the microscope prototypes and their parts. Includes, but it is
not restricted to:

  * _Engineering drawings_

  

  * _Chip layouts_

  

  * _Semiconductor processing specifications_

  

  * _Flow diagrams_

  

  * _Programming code_

  

  * _User protocols and manuals_

  

**Type II: Measurements and simulation data:** This data relates to the
experiments carried out during the project, which include the characterization
and simulation of the microscope parts, and the application of the microscopes
to observe samples. These experiments will generate, among other, datasets of:

  * _Optoelectronic and spectroscopic measurements_

  

  * _Images of different kinds_

  

  * _Numeric simulation results_

  

  * _New theoretical models_

  

  2. **Explain the relation to the objectives of the project**

  

  

The data generated in the research activities of ChipScope will serve us to
achieve the objectives #1 and #2, which relate to the design, fabrication, and
experimental proof-of-concept of the microscope prototypes.

The objective #3 relates to the dissemination, communication, and exploitation
of the project results. This states the obligation to make our best to
exploit, and not jeopardize, the technological assets developed in ChipScope.
Therefore, the achievement of objective #3 has strong implications on level of
open availability of the data generated.

  3. **Specify the types and formats of data generated/collected Type I: Design and fabrication details**

     * _Engineering drawings:_ CAD files, with defined schemas, shapes and dimensions of the prototypes’ parts (e.g. mechanical holders, stages, microfluidic system, wiring, etc.) and their integration. 

  

     * _Chip layouts:_ mask designs to be used in the production steps of the nanoLED and of the CMOS ASICS. Typically, in gds format. 

  

     * Semiconductor processing specifications: detailed list of steps, conditions, and materials’ qualities to be used in the production of chip devices. Typically, in Office file (or equivalent) format. 

  

     * _Flow diagrams:_ detailed graphical descriptions of the algorithms and procedures to be implemented in software. Typically, in Office file (or equivalent) format. 

  

     * _Programming code:_ source code of the programs running in the microscope prototypes, both in the computer side and in the embedded side, as well as source codes of simulation software. Typically, in ASCII files encoding different programing languages. 

  

     * _User protocols and manuals:_ detailed written and graphical descriptions on how to operate the different parts of microscope that accompany each prototype when being transferred among partners. Typically, in Office file (or equivalent) format. 

  

  

  

**Type II: Measurements and simulation data**

  * _Optoelectronic and spectroscopic measurements:_ electrical records, impedance spectra, digital bit stream records, electroluminescence and photoluminescence spectra. Typically, in CSV, Origin or Excel files. 

  

  * _Images:_ photo/micro/nanographs taken by camera, optical microscope, scanning electron microscope, and transmission electron microscope of microscope’s prototypes, reference metrological samples and living tissues. Involve image files (e.g. BMP, TIFF, JPG ...) and video files (e.g. MP4, AVI, MOV...) 

  

  * _Numeric simulation results:_ calculated physical quantities associated to spatial coordinates (spatial data), like particle densities, recombination rates, energy levels, electromagnetic field strength (associated with the mesh (grid) of the spatial discretization); and global quantities obtained from the simulations, like eigen mode frequencies, contact currents, emission powers, emission spectra (not associated to a spatial discretization). Depending on the specific software, data produced might be in stored in VTK format or ASCII files (for mesh dependent data). 

  

  * _New theoretical models:_ description of new formulas and algorithms. Typically, in Office file (or equivalent) format. 

  

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

  

  

No data, other than expertise from partners’ background (e.g. layouts of
similar devices or software 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 ChipScope project.

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

     * _Engineering drawings:_ 1MB – 100 MB per design 

  

     * _Chip layouts:_ 10MB – 100 MB per chip 

  

     * _Semiconductor processing specifications:_ 10kB – 10MB per process 

  

     * _Flow diagrams:_ 10kB – 10 MB per diagram 

  

     * _Programming code:_ 1MB – 10 MB per program 

  

     * _User protocols and manuals:_ 1MB – 100MB per document. **Type II: Measurements**

  

     * _Optoelectronic and spectroscopic measurements:_ 1kB – 100 MB per file. 

  

     * _Images of different kinds:_ 1MB – 1GB per image/video 

  

     * _Numeric simulation results:_ 1 MB – 1GB per simulation 

  

  

  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 digital imaging, metrology, multiscale simulations, and medical
diagnostics as well; either for a better understanding of the development and
its performances or for benchmarking and reproduction of the results.

  2. **FAIR data**

    1. **Making data findable, including provisions for metadata:**

      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.

  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. **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.

  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.

  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.

  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.

  2. **Making data openly accessible:**

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

  
  

  

  

**Type I data will NOT be made openly available.** This is necessary to
protect the technological asset developed in the project, and comply with the
project objective #3. Any public disclosure of the fabrication details would
jeopardize the chances of exploiting the technology, among the project
partners, with members of the Industry Advisory Board, or with third parties.

**Type II data will only be made openly available partially** . In fulfillment
of project objective #3, 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 II data used to prepare these
public communications.

_In brief, only the data relative to experimental measurements (Type II) used
to prepare publications disclosed in open access will be made openly
available._

  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. **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, and open output
formats like VTK or HDF5 for mesh related simulation data.

  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 

  

###  2.2.5 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 II associated to open access publication): open data that is shared for re-use that underpins a scientific publication. 

  

  * Consortium Confidential data (Type I and the rest of Type II data): accessible to all partners within the conditions established in the Consortium Agreement. 

  

##  2.3 Making data interoperable: 2.3.1 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.

###  2.3.2 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.

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

###  2.4.1 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).

###  2.4.2 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.

###  2.4.3 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.

###  2.4.4 Describe data quality assurance processes.

The repository platform functioning guarantees the quality of the dataset.

###  2.4.5 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.

#  3 Allocation of resources

**3.1 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.

##  3.2 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.

##  3.3 Describe costs and potential value of long term preservation.

Does not apply for the moment.

#  4 Data security

##  4.1 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.

#  5 Ethical aspects 5.1 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.**

Concerning the use of the prototypes for medical research applications, all
patient centered data will be kept exclusively within MUWs. Forwarded to the
technical Partners (AIT) will be only project relevant data (e.g. histological
diagnosis) in strictly anonymized form.

#  6 Other 6.1 Refer to other national/funder/sectorial/departmental
procedures for data

##  management that you are using (if any)

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

This DMP has been created with the tool “Pla de Gestió de Dades de Recerca”

( _https://dmp.csuc.cat/_ )  .

#  7 List of References

Does not apply.