#  1 Introduction

##  1.1 FLAIR Objectives

FLAIR (Flying ultra-broadband single-shot InfraRed sensor) is a Research and
Innovation Action (RIA) funded by the European Union’s H2020 programme under
the Photonics Key Enabling Technologies (KET) topic.

Its core objective is to develop a high-performance air sampling sensor based
on cutting-edge photonic technology capable of performing high-specificity and
high-sensitivity (ppbv) air quality sensing in large areas as a result of its
installation aboard an Unmanned Aerial Vehicle (UAV), also known as a drone.

Today, significant effort is devoted globally to improve air quality through
e.g. land-use planning strategies, replacement of fossil fuels by clean energy
sources and lower level of industrial emission. In order to be successful,
these measures need be accompanied by air quality monitoring at large scale to
ensure compliance with air quality legislation but also to provide information
for political decision making regarding air quality and safety. This is
particularly challenging outside the dense urban network of air quality
monitoring stations. FLAIR addresses this challenge by mounting a high-
performance air sampling sensor based on photonic technology on an UAV for
pervasive and large area coverage high-specificity and high-sensitivity air
quality sensing. Operating in the two atmospheric windows of 2-5 µm and 8-12
µm wavelength, FLAIR can detect minute traces of molecules in complex gas
mixtures from their characteristic IR absorption fingerprints and provide real
time information to the operator of the drone. FLAIR can operate in remote or
dangerous areas and outside of established monitoring networks.

FLAIR applications include the monitoring of air around industrial
infrastructure, maritime and land based traffic, landfills and agriculture
facilities and the project contributes to a safer environment by providing
detailed air quality data around current facilities and locations of interest
or in the case of catastrophic events like wildfires, volcanic eruption or
chemical accidents.

The advantages of using UAVs for this application are essentially related to
the fact that these vehicles can rapidly access areas that are too dangerous
or too difficult to reach by humans. Moreover, due to the local sampling FLAIR
can provide data from inside optically dense clouds and plumes that are not
accessible by ground based laser remote sensing methods.

Photonics technology is a promising approach to the challenge of air quality
monitoring, as it can provide, in principle, accurate identification and
concentration measurements of specific species in complex environments.
Current solutions include several methods for air quality monitoring, among
which are mass spectrometry, electronic noses and optical detection. While
systems based on mass spectrometry are highly sensitive, they suffer from
complexity and high footprint. Electronic noses are cheap but suffer from low
accuracy.

Several systems based on light sources operating in the IR range such as
quantum cascade lasers, diode laser, optical parametric oscillators or
frequency combs have enabled highly sensitive and selective detection of
molecules. Such high performance tools, however, typically remain confined to
academic research laboratories due to their narrow spectral operating window
(covering only very few molecules), their operational complexity and their
prohibitively high cost. These are the technical challenges FLAIR is
addressing.

The FLAIR project will generate trace gas absorption spectra from which
information on the levels of pollutants can be derived through data
processing. The datasets generated throughout the project will be fundamental
to validate the sensor prototype itself, to benchmark its performance against
current standards and to assess the feasibility of using unmanned vehicles as
a new instrument for deploying air quality sensors and implementing mobile
dynamic measuring stations.

The FLAIR project participates in the Pilot on Open Research Data (ORD)
launched by the European Commission (EC) under H2020. The ORD pilot aims to
improve and maximize access to and re-use of research data generated by H2020
projects. As such, the development and use of a Data Management Plan (DMP) is
required for all projects participating in the ORD Pilot.

##  1.2 Purpose of the Data Management Plan

A Data Management Plan consists of a living document that describes the data
management life cycle for the data collected, processed and generated by a
H2020 project. It is considered a key element of good data management. The
plan outlines how data will be created, managed, shared and preserved
throughout the project, providing arguments for any restrictions that apply to
any of these steps or any of the data.

The EC encourages all projects to follow and apply principles that will allow
all research data to be Findable, Accessible, Interoperable and Reusable (FAIR
principles).

The research data generated or created under the projects may include
statistics, results of experiments, measurements, observations resulting from
fieldwork, survey results, interview recordings and images. Open access to
research data is important to allow validation of the results presented by
project researchers and consortia in scientific publications.

As the project evolves and the research progresses, datasets will be created
and may be subject to changes or updates in terms of the types, formats and
origins of the data. Furthermore, the way the data is named or made accessible
may change according to consortium policy changes and/or identification of
potential for exploitation by project partners. Therefore, it is expected that
the DMP will not remain unaltered throughout the project’s lifespan. This
document constitutes the first version of the DMP and an official deliverable
of the project as defined in the Grant Agreement (GA) of FLAIR.

The FLAIR DMP will be updated at months 18 (April 2018) and 36 (December 2019)
in line with the mid-term and final reviews respectively, as recommended in
the EC Guidelines on FAIR Data Management in Horizon 2020.

The obligations to disseminate results (Article 29.1 of the GA), provide open
access to scientific publications (Article 29.2 of the GA) and open access to
research data (Article 29.3 of the GA) do not, in any way, change the
obligation of consortia to protect results, ensure confidentiality obligations
and the security obligations or the obligations to protect personal data, all
of which still apply. Consequently, consortia do not have to ensure open
access to specific parts of their research data if the achievement of the
action's main objective or the exploitation of results would be jeopardised.
Whenever this is the case, the DMP will identify said data and explain the
reasons for not giving access.

##  1.3 Approach

The FLAIR DMP has been created and developed following the Guidelines on FAIR
Data Management in Horizon 2020 published by the EC in 2016 as well as the
UK’s Digital Curation

Center (DCC) guide on How to Develop a Data Management and Sharing Plan from
2011 and the European Research Council’s (ERC) Guidelines on Implementation of
Open Access to Scientific Publications and Research Data from 2017.

##  1.4 Maintenance of the FLAIR DMP

The FLAIR DMP will be maintained throughout the project’s lifespan by the
coordinator with support from the other partners. This activity falls under
WP1 of the project (Project Management).

#  2 FLAIR data

Large amounts of data in different formats will be collected and generated
during the FLAIR project. These will consist mainly of physical parameters,
designs, blueprints for hardware, electronic circuit design, and technical
data. These data will be shared and exploited according to the policies
established under the Grant and Consortium Agreements of the project. All data
collected during the project will be placed in the official FLAIR repository,
where they will be available for authorized persons and will be properly
secured against theft.

In the context of the Pilot on ORD in H2020, all data will be made accessible
to the general public for verification and further re-use. However, it is
necessary to take into account the possibility that some of them will be part
of the Intellectual Property Rights (IPR) of individual partners and therefore
will be protected. The following sections describe the current picture of
datasets to be generated or used in the project and provide answers to the
questions of Annex 1 of the EC Guidelines on FAIR Data Management in Horizon
2020.

##  2.1 FLAIR laboratory dataset

###  2.1.1 Summary

####  2.1.1.1 Purpose of the data collection/generation

The FLAIR laboratory dataset will comprise the set of measurements of trace
gas absorption spectra accomplished with the FLAIR sensor in a controlled
laboratory environment. The purpose of this dataset is to validate the FLAIR
sensor design and components, and to characterize its performance against
known quantities of the target trace gases.

####  2.1.1.2 Relation to the objectives of the project

The FLAIR laboratory dataset is fundamental for achieving the project core
objectives. It will be through this dataset that the design of the FLAIR
sensor and the prototype of the sensor and its components will be evaluated
and characterized. The sensor’s performance will be benchmarked against
standard sets of parameters such as the HITRAN database and the PNNL spectral
library described in sections 3.1 and 3.2.

####  2.1.1.3 Data types and formats

The data comprising the FLAIR laboratory dataset will consist of:

  * Trace gas concentrations in ppbv (parts per billion volume). 

  

  * Gas absorption spectra in the 2-5 µm and 8-12 µm windows as a set of absorbance per wavelength measurements. 

  

At the moment of writing, the consortium plans to generate the data above for
the following gases (according to project deliverable D2.1 – Requirements for
FLAIR Sensor System):

  * CO  2  – Carbon Dioxide 

  

  * CH  4  – Methane 

  

  * CO – Carbon Monoxide 

  

  * O  3  – Ozone 

  

  * N  2  O – Nitrous Oxide 

  

  * SO  2  – Sulfur Dioxide 

  

  * NH  3  – Ammonia 

  

  * HCl – Hydrogen Chloride 

  

Comparison results between the results obtained and the standard values of
benchmarks may also be included in the dataset as absolute and relative
differences.

The consortium does not foresee the inclusion of the data processing algorithm
details in the dataset as this can be commercially exploited by the project
partners.

**2.1.1.4 Re-use of existing data**

No existing data will be re-used in the generation of the FLAIR laboratory
dataset.

####  2.1.1.5 Data origin

The data for the FLAIR laboratory dataset will be generated at the
laboratories of partners of the FLAIR consortium directly by the researchers
involved in the project. The generation procedures will be described in detail
in the appropriate deliverables and associated with the dataset.

**2.1.1.6 Expected size of the data**

At the moment the expected size of the dataset is not known.

####  2.1.1.7 Data utility

The FLAIR laboratory dataset will be useful to the entire consortium (namely
in helping accomplish the project objectives as outline above) as well as for
other researchers wishing to evolve the work of FLAIR and potential customers
interested in new sensors based on the FLAIR technology.

###  2.1.2 FAIR

####  2.1.2.1 Making data findable

The FLAIR laboratory dataset will be made discoverable through the association
of metadata to the dataset. At the moment of writing the type of metadata and
identification mechanism to be applied is not yet defined. The process or
standard to be used to create the metadata is not clear yet. However, the
consortium expects to associate the following metadata to the dataset:

  * Date of measurement 

  

  * Gases measured 

  

  * Absorption windows 

  

Files in the dataset will be clearly named and their names will include the
date of measurement, gas to which the file refers to and whether the file
refers to the absorption spectrum or the detected concentration. The following
is an example of such a name: 20180428-FLAIR-CO2AbsSpectrum.ext.

All files in the dataset will allow the clear identification of the version.
This may be achieved through the addition of a version suffix to the filename
or by supporting versioning in the FLAIR repository. The chosen solution is
not defined at the moment. In case the consortium opts for versioning through
the filename, then the file itself will describe in its initial contents the
major changes to the previous version (e.g. different laboratory test run).

####  2.1.2.2 Making data openly accessible

At the moment of writing, the consortium expects to make the entire FLAIR
laboratory dataset openly available. The consortium expects to make the
dataset available through the project’s repository (which is foreseen to
support versioning). The repository is maintained by the project coordinator
and access to it is authenticated. Access to the repository will be enabled
through a web interface that only allows download of the dataset (i.e. it will
not be possible to delete, upload, check-out or commit other files).

Registration to the repository will be required and will consist in providing
the name, entity and reason of interest or foreseen purpose of use for the
FLAIR dataset.

####  2.1.2.3 Making data interoperable

FLAIR will provide the data in the FLAIR laboratory dataset in the standard
units for detected concentration and those used in absorption spectra. This
should be enough to ensure the interoperability of the data. Parts per billion
volume (of air) is a commonly accepted unit for measuring concentrations of
compounds in the air. The standard way of presenting an absorption spectrum is
to represent the absorbance (unitless) against the wavelength in µm or nm
depending on the spectrum window of interest.

####  2.1.2.4 Increasing data re-use

At the moment of writing the consortium has not yet addressed this issue.
However, it is expected that the data will be made available for re-use after
the conclusion of the project. It is not clear if licensing will be applied
nor if an embargo period will be needed.

###  2.1.3 Resources

At the moment, and based on the assumptions and plan above, the costs for
making the FLAIR laboratory dataset FAIR will be covered by the regular
testing activities of the project (WP5 and WP6) and by project management
(WP1, where the responsibility for data management lies). Data management
responsibility lies with the project coordinator through WP1. The consortium
has not analysed or estimated the costs and/or potential benefits of long term
preservation of the FLAIR laboratory dataset.

###  2.1.4 Security

The FLAIR laboratory dataset will not include sensitive data. The dataset will
be stored in the project repository which is hosted in a server of the project
coordinator’s IT infrastructure. The repository supports version control which
should be enough to ensure data recovery in case of accidental deletions. Data
back-ups will be done according to the internal IT policy of the project
coordinator as applicable to all other relevant digital data of the company.
Access to the data will only be possible through authenticated access to the
repository: one account per partner and one account per external individual
(i.e. not belonging to the consortium) requesting access to the data – see
2.1.2.2 above.

###  2.1.5 Ethical aspects

Not applicable.

##  2.2 FLAIR field test dataset

###  2.2.1 Summary

####  2.2.1.1 Purpose of the data collection/generation

The FLAIR sensor system will be operated at the sensor test facility on the
roof of the suburban air quality monitoring station on the premise of EMPA in
Dübendorf, Switzerland. It will be run for several days next to the inlet of
high precision reference instruments. These parallel measurements are used for
the determination of the sensitivity and the measurement uncertainties of the
FLAIR sensor system for the four target gas species (CO  2  , CH  4  , CO and
O  3  ) under real world conditions.

####  2.2.1.2 Relation to the objectives of the project

The FLAIR field test dataset is fundamental for achieving the project core
objectives. It will be through this dataset that the design of the FLAIR
sensor and the prototype of the sensor and its components will be evaluated
and characterized under real world conditions.

####  2.2.1.3 Data types and formats

The data comprising the FLAIR field test dataset will consist of:

  * Trace gas concentrations measured by the FLAIR instrument in ppbv (parts per billion volume) for CO  2  , CH  4  , CO and O  3 

  

  * Trace gas concentrations measured by the Dübendorf air quality monitoring station in ppbv (parts per billion volume) for CO  2  , CH  4  , CO and O  3 

  

  * Absolute difference between the measurements of previous bullets 

  

  * Relative difference between the measurements of first two bullets 

  

The consortium does not foresee the inclusion of the data processing algorithm
details in the dataset as this can be commercially exploited by the project
partners.

**2.2.1.4 Re-use of existing data**

No existing data will be re-used in the generation of the FLAIR field test
dataset.

####  2.2.1.5 Data origin

The data for the FLAIR field test dataset will be generated at the Dübendorf
air quality monitoring stations in Switzerland by researchers directly
involved in the project. The measurement process will be described in detail
in the appropriate deliverable and associated with the dataset.

**2.2.1.6 Expected size of the data**

At the moment the expected size of the dataset is not known.

####  2.2.1.7 Data utility

The FLAIR field test dataset will be useful to the entire consortium as well
as for other researchers wishing to evolve the work of FLAIR and potential
customers interested in new sensors based on the FLAIR technology.

###  2.2.2 FAIR

####  2.2.2.1 Making data findable

The FLAIR field test dataset will be made discoverable through the association
of metadata to the dataset. At the moment the consortium expects to associate
the following metadata to the dataset:

  * Date of measurement 

  

  * Gases measured 

  

  * Time of measurement 

  

Files in the dataset will be clearly named and their names will include the
date of measurement and gas to which the file refers to.

Versioning may be achieved through the addition of a version suffix to the
filename or by supporting versioning in the FLAIR repository. The chosen
solution is not defined at the moment although it is already clear that the
repository will support versioning.

####  2.2.2.2 Making data openly accessible

At the moment of writing, the consortium expects to make the entire FLAIR
laboratory dataset openly available. The consortium expects to make the
dataset available through the project’s repository.

Registration to the repository will be required and will consist in providing
the name, entity and reason of interest or foreseen purpose of use for the
FLAIR dataset.

####  2.2.2.3 Making data interoperable

FLAIR will provide the data in the FLAIR field test dataset in the standard
units for detected concentration. This should be enough to ensure the
interoperability of the data. Differences will be provided in concentration
units (ppbv) for absolute differences or percentages for relative differences.

**2.2.2.4 Increasing data re-use**

At the moment of writing the consortium has not yet addressed this issue.

###  2.2.3 Resources

The costs of making and maintaining the dataset FAIR will be covered by the
regular testing activities of the project (WP5 and WP6). Data management
responsibility lies with the project coordinator through WP1.

The consortium has not analysed the costs and/or potential benefits of long
term preservation of this dataset.

###  2.2.4 Security

The FLAIR field test dataset will not include sensitive data. The dataset will
be stored in the project repository which is hosted in a server of the project
coordinator’s IT infrastructure. The repository supports version control. Data
back-ups will be done according to the internal IT policy of the project
coordinator. Access to the data will only be possible through authenticated
access to the repository.

###  2.2.5 Ethical aspects

Not applicable

##  2.3 FLAIR UAV dataset

###  2.3.1 Summary

####  2.3.1.1 Purpose of the data collection/generation

The FLAIR UAV dataset will comprise the following:

  * Set of measurements of trace gas absorption spectra and minimum detected concentrations performed by the FLAIR sensor equipped UAV with profiling in o The vertical direction o The radius direction 

  

  * Measurements of concentration of gas obtained from the tall tower atmospheric research site in Beromünster (Switzerland); 

  

  * Number of particles measured near emission sources (e.g. the motorway in the area of the NABEL site Härkingen in Switzerland) 

  

  * Particle concentration measured near emission sources (e.g. the motorway in the area of the NABEL site Härkingen in Switzerland) 

  

The purpose of this dataset is to prove the suitability of the airborne FLAIR
sensor system for vertical profiling of atmospheric trace gases and for
airborne atmospheric measurements in general. It will also serve the purpose
of helping to interpret the measured spatial variation of gases that are
emitted by road traffic emissions (or influenced by road traffic emissions
like O  3  ) and will help to demonstrate the usefulness of the FLAIR system
for other applications.

####  2.3.1.2 Relation to the objectives of the project

The FLAIR UAV dataset contributes directly to the achievement of the project
core objectives. The vertical mapping of CO  2  , CH  4  and CO at the tall
tower atmospheric research site in Beromünster (Switzerland), where precise
measurements of these atmospheric trace gases are available at different
heights will be compared to the vertical profiles of CO  2  , CH  4  and CO
obtained by the UAV flying the FLAIR sensor by averaging the measurements
obtained at different altitudes. This comparison will confirm or reject the
suitability of the airborne FLAIR sensor system for vertical profiling of
atmospheric trace gases and for airborne atmospheric measurements in general.

The particle sensor measurements will be compared with the concentration
measurements obtained from the FLAIR sensor at a different location and will
contribute to demonstrate the usefulness of the FLAIR system for applications
where toxic gases and particle emission occur simultaneously (such as in road
traffic).

####  2.3.1.3 Data types and formats

The data comprising the FLAIR UAV dataset will consist of:

  * FLAIR sensor trace gas concentrations in ppbv (parts per billion volume) o against height in meters 

    * against horizontal distance from tower in meters 

  

  

  * FLAIR sensor gas absorption spectra in the 2-5 µm and 8-12 µm windows as a set of absorbance per wavelength measurements o against height in meters 

    * against horizontal distance from tower in meters 

  

  

  * Beromünster tower trace gas concentrations in ppbv (parts per billion volume) against height in meters. 

  

  * Total number of particles measured in the UAV at Härkingen (site to be confirmed) against height in meters and horizontal distance in meters. 

  

  * Particle concentration measured in the UAV at Härkingen (site to be confirmed) in total particles per ccm against height in meters and horizontal distance in meters 

  

At the moment of writing, the consortium plans to generate the data above for
the following gases:

  * CO  2  – Carbon Dioxide 

  

  * CH  4  – Methane 

  

  * CO – Carbon Monoxide 

  

The consortium does not foresee the inclusion of the data processing algorithm
details in the dataset as this can be commercially exploited by the project
partners.

**2.3.1.4 Re-use of existing data**

No existing data will be re-used in the generation of the FLAIR UAV dataset.

####  2.3.1.5 Data origin

The data for the FLAIR UAV dataset will be generated at the locations of the
flights (to be confirmed later during the project) directly by the FLAIR
consortium and the operation of the UAV. The generation procedures will be
described in detail in the appropriate deliverables and associated with the
dataset.

**2.3.1.6 Expected size of the data**

At the moment the expected size of the dataset is not known.

####  2.3.1.7 Data utility

The FLAIR UAV dataset will be useful to the entire consortium (namely in
helping accomplish the project objectives as outline above) as well as for
other researchers wishing to evolve the work of FLAIR and potential customers
interested in new sensors based on the FLAIR technology.

###  2.3.2 FAIR

####  2.3.2.1 Making data findable

The FLAIR UAV dataset will be made discoverable through the association of
metadata to the dataset. At the moment of writing the type of metadata and
identification mechanism to be applied is not yet defined. The process or
standard to be used to create the metadata is not clear yet. However, the
consortium expects to associate the following metadata to the dataset:

  * Date of measurement 

  

  * Gases measured 

  

  * Absorption windows 

  

  * Time of measurement 

  

  * Location of measurement 

  

Files in the dataset will be clearly named. All files in the dataset will
allow the clear identification of the version. This may be achieved through
the addition of a version suffix to the filename or by supporting versioning
in the FLAIR repository. The chosen solution is not defined at the moment.

####  2.3.2.2 Making data openly accessible

At the moment of writing, the consortium expects to make the entire FLAIR UAV
dataset openly available. The consortium expects to make the dataset available
through the project’s repository (which is foreseen to support versioning).
The repository is maintained by the project coordinator and access to it is
authenticated. Access to the repository will be enabled through a web
interface that only allows download of the dataset (i.e. it will not be
possible to delete, upload, check-out or commit other files).

Registration to the repository will be required and will consist in providing
the name, entity and reason of interest or foreseen purpose of use for the
FLAIR UAV dataset.

####  2.3.2.3 Making data interoperable

FLAIR will provide the data in the FLAIR UAV dataset in the standard units as
described above in section 2.3.1.1.

**2.3.2.4 Increasing data re-use**

At the moment of writing the consortium has not yet addressed this issue.

###  2.3.3 Resources

The costs of making and maintaining the FLAIR UAV dataset FAIR will be covered
by the regular testing activities of the project (WP5 and WP6). Data
management responsibility lies with the project coordinator through WP1.

The consortium has not analysed or estimated the costs and/or potential
benefits of long term preservation of the FLAIR UAV dataset.

###  2.3.4 Security

The FLAIR UAV dataset will not include sensitive data. The dataset will be
stored in the project repository which is hosted in a server of the project
coordinator’s IT infrastructure. The repository supports version control. Data
back-ups will be done according to the internal IT policy of the project
coordinator. Access to the data will only be possible through authenticated
access to the repository.

###  2.3.5 Ethical aspects

Not applicable

#  3 Other data

##  3.1 HITRAN database

###  3.1.1 Summary

The FLAIR consortium will collect data from the HITRAN (High resolution
TRANsmission molecular absorption) database that will be used to benchmark and
characterize the FLAIR laboratory performance. HITRAN is a compilation of
spectroscopic parameters that a variety of computer codes use to predict and
simulate the transmission and emission of light in the atmosphere. The goal of
HITRAN is to have a self-consistent set of parameters. The database is a long-
running project started by the Air Force Cambridge Research Laboratories
(AFCRL) in the late 1960s in response to the need for detailed knowledge of
the infrared properties of the atmosphere.

The initial HITRAN database included only the basic parameters necessary to
solve the Lambert-Beers law of transmission. In addition, the air-broadened
Lorentz width was included as well as the unique quantum identifications of
the upper and lower states of each transition.

The parameters stored in HITRAN are a mixture of calculated and experimental.
HITRAN provides the sources for the key parameters within each transition
record whereby the user can determine from where the value came. The
experimental data that enter HITRAN often come from the results of analysis of
Fourier transform spectrometer laboratory experiments. Many other experimental
data also are inputted, including lab results from tuneable-diode lasers,
cavity-ring down spectroscopy, heterodyne lasers, etc. The results usually go
through elaborate fitting procedures. The theoretical inputs include standard
solutions of Hamiltonians, ab initio calculations, and semi-empirical fits.

The HITRAN parameters will be compared to the data obtained from the FLAIR
sensor in a lab environment. This way, the consortium will be able to
characterize the performance of the FLAIR sensor and this will help establish
the validity of the FLAIR design and the prototype.

HITRAN parameters can be obtained directly from the HITRAN database website (
_http://hitran.org_ ) and are output in records of 160 characters which
include parameters in integer, real and text data types. The data types and
formats can be consulted at _https://www.cfa.harvard.edu/hitran/formats.html_
.

At the moment of writing the size of the data to be used by FLAIR is not
known. FLAIR will not store HITRAN data nor will it make the data available as
it can be freely obtained directly from HITRAN. It is mentioned here as it
will have an important role in the validation of FLAIR results.

Whenever HITRAN data is used the research results will clearly identify which
parameters have been used.

##  3.2 PNNL spectral library

###  3.2.1 Summary

The Pacific Northwest National Laboratory (PNNL) has created a quantitative
database containing the vapour-phase infrared spectra of pure chemicals. The
digital database has been created with both laboratory and remote-sensing
applications in mind.

This unique library is the "gold standard" of vapour phase infrared reference
spectra and is uniquely adapted to both remote and point sensing. The library
is a unique asset to the development of infrared sensors and methods. Data
from the PNNL spectral library will be used in FLAIR as benchmark against
which the FLAIR sensor’s performance will be measured. This way, the
consortium will be able to characterize the performance of the FLAIR sensor
and this will help establish the validity of the FLAIR design and the
prototype.

PNNL parameters can be obtained directly from the PNNL library website

( _https://secure2.pnl.gov/nsd/nsd.nsf/Welcome_ ) via registration.

At the moment of writing the size of the data to be used by FLAIR is not
known. FLAIR will not make PNNL data available as it can be freely obtained
directly from the PNNL library. Whenever PNNL data is used the research
results will clearly identify which parameters have been used.

##  3.3 UAV performance data

###  3.3.1 Summary

The FLAIR sensor will be installed on a modified Unmanned Aerial System based
on an existing product from TEKEVER Autonomous Systems. While the consortium
will gather and collect performance data for the FLAIR-equipped UAV for the
purpose of characterizing the performance of the system while in flight and to
validate the sensor application, specific UAV performance data will not be
made available outside the consortium.

Specific UAV sub-systems data is proprietary and can be used to infer the
solutions and specific components used in the product. As the UAV is a
commercial product, open access to this data could result in the loss of
competitive advantage in the commercial exploitation of the product. Any data
which is considered relevant for the characterization and validation of the
FLAIR sensor itself while installed in the UAV (e.g. altitude, GPS position,
etc.) will be made available through the FLAIR UAV dataset.

##  3.4 FLAIR system design data

###  3.4.1 Summary

The FLAIR sensor system is described in detail in deliverable D2.3 – List of
specifications doe all system (UAV and assembled sensor) and sub-system
parameters. Designs, blueprints for hardware, electronic circuit design and
technical data for the sub-systems will be generated throughout the project
and will be made available in corresponding deliverables, most of which are of
public dissemination. However, it must be noted that the consortium may
decide, as the project progresses that some specific design details be kept
confidential as they provide the added value or the competitive advantage that
will allow the generating partner(s) to protect and exploit the results.
Examples of these include design and test data related to:

  * Data processing algorithm due to its commercial potential; 

  

  * Subsystem development; 

  

  * UAV adaptation; 

  

  * And Sensor/UAV fitting. 

  

Furthermore, while all of the physical components of the FLAIR sensor are
public, open access to the HW and prototypes will not be ensured by the
consortium. Rather, a description of the units will be published but the unit
itself will not be public as it is needed in the FLAIR drone system.