#  Introduction

This document is a deliverable of the µSPIRE project which is funded by the
European Union’s H2020 Programme under Grant Agreement No. 766955\. This first
version of the Data Management Plan (DMP) describes the main elements of the
data management policy that will be used by the members of the Consortium with
regard to the data generated throughout the duration of the project and after
its completion.

The µSPIRE consortium shall implement procedures that are in line with
national legislation of each consortium partner and in line with the European
Union standards. This DMP will apply to all data under µSPIRE consortium
control. If we shall strive to make data open, we cannot overrule limitations
that partner institutions put on data that they contributed to generate (see
e.g. the grant agreement).

This first version of the Data Management Plan (DMP), based on the knowledge
available and developed at the moment of the deliverable submission, describes
the main elements of the data management policy that will be used by the
members of the Consortium with regard to the data generated throughout the
duration of the project and after its completion.

The DMP will be regularly updated as far as necessary during the development
of the project activities. The next editions of the DMP will provide
additional details. New versions will be relased at months M18 and M36.

The DMP is released in compliance with the H2020 FAIR [1] (making data
Findable, Accessible, Interoperable and Reusable).

#  Administrative data

**Project name:** micro-crystals Single Photon InfraREd detectors - µSPIRE

**Grant reference number:** H2020-FETOPEN-1-2016-2017 – ID: 766955

**Project description:** µSPIRE aims at establishing a technological platform
for homo- and hetero- structure based photonic and electronic devices using
the self-assembling of epitaxial crystals on patterned Si substrates. Emerging
micro-electronic and photonic devices strongly require the integration on Si
of a variety of semiconducting materials such as Ge, GaAs, GaN and SiC, in
order to add novel functionalities to the Si platform. µSPIRE pursues this
goal employing a novel deposition approach, which we termed vertical hetero-
epitaxy (VHE). VHE exploits the patterning of conventional Si substrates, in
combination with epitaxial deposition, to attain the self-assembly of arrays
of Ge and GaAs epitaxial micro-crystals elongated in the vertical direction,
featuring structural and electronic properties unparalleled by “conventional”
epitaxial growth. As a concrete demonstration of VHE potentialities, we will
deliver a complete set of novel photon counting detectors: VHE micro-crystals
will be used as the

elementary microcells for single-photon detectors with performances far beyond
those of current state-of-the-art devices.

**Consortium members:**

  1. Politecnico di Milano – Polimi (coordinator) 

  

  2. Università degli Studi Milano Bicocca – Unimib 

  

  3. University of Glasgow – UGLA 

  

  4. Philipps-Universität Marburg – UMR 

  

  5. Technische Universität Dresden – TDU 

  

  6. Micro Photon Devices Srl.- MPD 

  

  

**Project data contact:** Giovanni Isella

Politecnico di Milano - Polo Territoriale di Como

Via Anzani 42 , 22100 Como Phone: +39 0313327303 e-mail:
giovanni.isella@polimi.it

#  Dataset description and generation/collection

The data generated in µSPIRE will mainly be:

  1. **Design Data**

  

  2. **Protocol Data**

  

  3. **Experimental and Characterization Data**

  

  4. **Computational and Modeling Data**

  

  

A comprehensive description of such data is given in the tables here below:

##  Design data

_Table 1: Design of substrate pattern_  
  
<table>  
<tr>  
<th>

Type of study

</th>  
<th>

</th>  
<th>

Schematics representing the geometry and dimensions of the silicon (Si)
pillars etched in the Si wafer.

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

DEV<progressive number> (substrates meant for device fabrication)

DIS<progressive number> (substrates meant for dislocation expulsion studies)

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

Provenance of data

</td>  
<td>

</td>  
<td>

Original data produced by: Ugla, Unimib, Polimi.

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

Type of data

</td>  
<td>

</td>  
<td>

Relevant dimensions of the pillars etched into the Si substrate: pillar shape
(square, round) orientation with respect to crystallographic directions,
pillar height, lateral dimension and spacing between adjacent pillars.

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

Nature and formats

</td>  
<td>

</td>  
<td>

Text document(PDF).

Images (PNG).

Autocad file (gds).

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

Amount of data

</td>  
<td>

Based on previous studies, the amount of resulting data is estimated around
500MB per year. Some text format data files are also required for post-
processing in the laboratory and are anticipated to be around 5MB per year.

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

Requirements for software and hardware

</td>  
<td>

Substrate patterns are typically designed by using proprietary software such
as AutoCAD. Free viewers for gds files are available and all relevant
information can be exported as text document (PDF) or images (PNG).

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

3.2. Protocol data

_Table 2: Protocol Data_  
  
<table>  
<tr>  
<th>

Type of study

</th>  
<th>

</th>  
<th>

Relevant parameters used during low-energy plasma-enhanced chemical vapour
deposition (LEPECVD) and molecular beam epitaxy (MBE) growth (substrate
temperature, plasma current, gas flow, pressure and growth rate) and
microfabrication.

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

LG<number of deposition system (1 or 2)>_<progressive number identifying the
epitaxial growth>

MBE_<progressive number identifying the epitaxial growth>

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

Provenance of data

</td>  
<td>

</td>  
<td>

Original data produced by: Polimi and Unimib.

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

Type of data

</td>  
<td>

</td>  
<td>

Intended profile of the epilayer stack: silicon (Si), germanium (Ge) and
aluminum-gallium-arsenide (AlGaAs) concentration and thickness.

Relevant growth parameters: deposition temperature, deposition rate, plasma
parameters.

Substrate pattern as described in Table 1.

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

Nature and formats

</td>  
<td>

</td>  
<td>

Text document (TXT) organized in columns with headers indicating the quantity
measured and unit of measure used.

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

Amount of data

</td>  
<td>

</td>  
<td>

We expect a total of 1GB.

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

Requirements for software and hardware

</td>  
<td>

Any text editor.

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

3.3. Experimental and characterization data

_Table 3: Experimental and Characterization Data_  
  
<table>  
<tr>  
<th>

Type of study

</th>  
<th>

</th>  
<th>

Morphological data (scanning electron microscopy – SEM, trasmission electron
microscopy – TEM and high-resolution X-ray diffraction – HRXRD),
optical/spectroscopical data (photoluminescence – PL, µPL, Raman and µRaman)
and optoelectronic data (current-voltage characteristics, photoresponse).

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

PL_<progressive number> identifying the epitaxial growth as indicated in Table
2 and **Error! Reference source not found.** >

TEM_<progressive number>

AFM_<progressive number>

IV_<progressive number>

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

Provenance of data

</td>  
<td>

</td>  
<td>

Original data produced by: Unimib (PL), Umar (TEM and SEM), Polimi (SEM, AFM
and electrical measurements).

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

Type of data

</td>  
<td>

</td>  
<td>

Photoluminescence response of the sample.

TEM, SEM and AFM images showing crystal defects with atomic resolution and
micro-crystals morphology.

Electro-optical characterization of µSPIRE’s devices.

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

Nature and formats

</td>  
<td>

</td>  
<td>

PL and electrical measurement data: text document (TXT) organized in columns
with headers indicating the quantity measured and unit of measure used.

TEM data: images (bmp, tiff, jpeg…) Post processed images can be visualized
with free software.

SEM data: images (bmp, tiff, jpeg…).

AFM data: raw data are in flt format and can exported in an image format (bmp,
tiff, jpeg…). Accessing raw data is possible by means of freely available
software such as Gwyddion.

Electrical measurements: text document (TXT) organized in columns with headers
indicating the quantity measured and unit of measure used.

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

Amount of data

</td>  
<td>

</td>  
<td>

1TB

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

Requirements for software and hardware

</td>  
<td>

TXT file can be accessed with several free software.

Image file are also freely accessible.

Accessing .flt raw data is possible by means of freely available software such
as Gwyddion.

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

3.4. Computational and modeling data

_Table 4: Computational and Modeling Data_  
  
<table>  
<tr>  
<th>

Type of study

</th>  
<th>

</th>  
<th>

Modeling of the morphological properties of Si, Ge and AlGaAs micro-crystals
as a function of substrate patterning and growth conditions.

Electronic design of µSPIRE devices: material (Si, Ge or GaAs), doping profile
and micro-crystals shape/dimensions.

Modeling of the micro-crystals bandstructure.

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

MOD_<progressive number identifying the morphological modeling>

ELDES<progressive number identifying the electronic modeling>
BAND_<progressive number identifying the bandstructure calculation>

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

Provenance of data

</td>  
<td>

</td>  
<td>

Original data produced by: Polimi, TUD and Unimib

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

Type of data

</td>  
<td>

</td>  
<td>

Morphological modeling: phase field calculation of micro-crystals morphology.

Electronic modelling: drift-diffusion Poisson calculations of optoelectronic
response of µSPIRE devices.

Bandstructure calculations: K-dot-P or effective mass calculation.

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

Nature and formats

</td>  
<td>

</td>  
<td>

Morphological modeling: images (bmp, tiff, jpeg).

Electronic modeling: such calculations are performed using the proprietary
software Synopsis Sentaurus TCAD. Selected image can be exported in almost any
image format.

Bandstructure calculationsSuch calculations are performed using the
proprietary software Nextnano. Results are exported as TXT files.

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

Amount of data

</td>  
<td>

</td>  
<td>

1TB

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

Requirements for software and hardware

</td>  
<td>

Any image viewer or TXT editor

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

#  Data management documentation and curation

This section describes the processes and actions that will be implemented
during the course of the research for data management, documentation, sharing
between partners and curation (saving and preservation).

_Table 5: File naming convention_  
  
<table>  
<tr>  
<th>

**Convention**

</th>  
<th>

_**[time_stamp]_microSPIRE_[data type]_[Partner]_[Version].[file format]** _

</th>  
<th>

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

</td>  
<td>

Time Stamp

</td>  
<td>

Data Type

</td>  
<td>

Partner

</td>  
<td>

Version

</td>  
<td>

File format

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

YYYY_MM_DD

</td>  
<td>

Data set reference and name as describe in tables 1 to 4

</td>  
<td>

Polimi,

Unimib,

Ugla

Umar

TDU

MPD

</td>  
<td>

V1

</td>  
<td>

According to software:

txt

csv

odt ods pdf

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

**Examples**

</td>  
<td>

2018_04_30_LEPECVD_10001_Polimi_v1.txt

</td>  
<td>

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

##  Data Managing: access, storage and back-up

µSPIRE data are mainly created _ex novo_ as a result of the research
activities listed from 1 to 4 in Section 3. Common rules will be used for file
naming in order to favour data sharing and accessibility.

The proposed naming convention is described in Table 5. The data managing
cycle is composed of three steps:

  1. data production and storage by each partner; 

  

  2. data sharing and storage on a repository accessible only to the project participants; 

  

  3. data open-access on a public repository. 

  

  

###  Data production and storage by each partner

The first responsible for each data set is the Partner ho generated it,
therefore a copy of the data set will be stored and maintained on the Partner
servers according to its internal practices and regulation described in Table
6.

_Table 6_  
  
<table>  
<tr>  
<th>

Polimi

</th>  
<th>

All data is stored on a local server, Dr. Chrastina is the server
administrator and provides access and read/write permissions to the different
members of the group. Data transmission can be accessed through secure file
transfer protocol. A back-up procedure on an external hard disk is performed
weekly.

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

Unimib

</td>  
<td>

All local data is stored on a local server. Access and permission is granted
to the project members by the server administrator, Dr. Bergamaschini. The
access to the data is possible through secure file transfer protocol and
network file system export on local computers (password protected). The server
is configured as RAID-5 and a weekly backup is done to local hard drives.

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

Ugla

</td>  
<td>

All data is stored on a raid server which is backed up every evening to a set
of secondary discs. The server is also backed up to a tape system every month.
The server is administered by the School’s IT department and user access is
controlled by Prof. Paul. The server is accessed through secure file transfer
or secure https protocols.

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

Umar

</td>  
<td>

All data is stored on a local server, Dr. Beyer is the server administrator
and provides access and read/write permissions to the different members of the
group. Data transmission can be accessed through secure file transfer
protocol. The server is integrated in the daily backup scheme of the
university´s computer centre.

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

TUD

</td>  
<td>

All challenges to store, process and manage data at TUD, are addressed
according to the

``Guidelines on the Handling of Research Data at TUD". TUD closely cooperates
with the Saxon State and University Library (SLUB) and started in 2018 an
institutional repository and longterm preservation infrastructure for research
data (Project OpARA). This system will be used as the central base for data
management.

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

MPD

</td>  
<td>

All data is stored on external servers administered by our secure cloud
infrastructure provider. Mr Sandro Rizzetto is our internal server
administrator and provides access with individual read/write permissions to
the different MPD employees. Local MPD data can be accessed through a secure
VPN connection. A back-up procedure is daily performed by our external IT
infrastructure provider.

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

###  Data sharing and storage on a repository accessible only to the project
participants

Each Partner will transfer data which are considered relevant for the project
on a server set-up and maintained by personnel of the ICT services of the
Politecnico di Milano (ASICT Polimi). The system operates as a Git server (
_http://gitlab.polimi.it/_ )  . The access is granted by means of
username/password provided by ASICT.

Gitlab allows for access control: different users can be given different
access permit. Each Partner will be allowed to add data to the repository.
Only the Coordinator will be allowed to delete data from the repository.

Versioning and profiling are implemented, it is therefore possible to trace
which changes have been made to the database and who made them.

Back-ups are performed daily and kept for 30 days (i.e. each given day it is
possible to recovery the data as they were in any of the 30 days before). A
full back-up is performed every 12 months and kept for 12 months. The gitlab
repository will ensure preservation of the data also after the duration of the
project for a time of at least 5 years. We do not envision any need to
transfer data to a different server during the project. The costs are covered
by the Polimi budget and consists of 200 € for the gitlab set-up and 360
€/year for its maintenance.

###  Data open access

Data underpinning published papers will be made available through ZENODO

( _https://zenodo.org/_ )  , an open access repository for all fields of
science that allows uploading any kind of data file formats. ZENODO is
recommended by the Open Access Infrastructure for Research in Europe
(OpenAIRE). ZENODO assign a persistent digital identifier to all published
records. ZENODO will also be used for the long term preservation of data, even
those not shared, after completion of the project.

##  Metadata standards and data documentation

Different information will be stored as metadata and associated to the
different types of data set, from 1 to 4, described in Section 3. Some
examples are given in Table 7.

_Table 7: Metadata_  
  
<table>  
<tr>  
<th>

Metadata associated to

Design Data

</th>  
<th>

Units of measurement (in case they are not specified in the TXT file headers),
software required to make the data usable.

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

Metadata associated to

Protocol Data

</td>  
<td>

Information allowing for the correct interpretation of the growth parameters
used: units of measurement of the relevant physical quantities (pressure, gas
flow, temperature, shutters pneumatic valves staus).

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

Metadata associated to

Experimental and

characterization data

</td>  
<td>

Equipment used for the measurements, measuring condition

(temperature), sample preparation,

Information on data analysis procedures, software required for making data
readable.

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

Computational and

modelling data

</td>  
<td>

Equipment used for the measurements, measuring condition

(temperature), sample preparation,

Information on data analysis procedures, software required for making data
readable.

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

#  Data sharing

µSPIRE DMP is inspired by the FAIR data Principles i.e. making data findable,
accessible, interoperable and reusable[1]. Therefore, µSPIRE will consider the
following approaches as far as applicable for providing the open access to
research data:

  * data appearing or underpinning publications will be available on the web trough the ZENODO platform under a Creative Commons license of the CC BY-NC-SA (non commercial share alike) type (https://creativecommons.org/); 

  

  * open-source formats and softwares (e.g. CSV instead of Excel) will be preferred over their commercial counterpart; 

  

  * interoperability will be enforced by using Metadata to specify the data type (as highlighted in Table 1 to 4), and the software required to analyze and process data. The Metadata file (typically in the form of a README.txt file) will be filled by the authors in order to summarize the characteristics of each data set to give a quick understanding of the content of the data to anyone that reads it. 

  

The policy for open-access to the research data in µSPIRE will follow two core
principles:

  1. The generated research data should generally be made as widely accessible as possible in a timely and responsible manner; 

  

  2. The research process should not be impaired or damaged by the inappropriate release of such data. 

  

  

Data sets containing key information that could be patented for commercial or
industrial exploitation will be excluded for public distribution and data sets
containing key information that could be used by the research team for
publications will not be shared until the embargo period applied by the
publisher is over.

µSPIRE will follow the Open Access mandate for its publications (art. 29.2
Grant agreement). Each publication, including associated metadata, will be
deposited in Individual partner repositories (institutional or subject). The
institutional repository of Politecnico of Milano, compliant with OpenAIRE
rules, is  _https://re.public.polimi.it/_ .

#  Ethical Aspects

In the µSPIRE project, there are no ethical or legal issues present which
impairs the data managing. The research does not create, process and store
personal data.