#  1 Executive Summary

The Data Management Plan (DMP) of the project TBO-Met is presented in this
document. Its target audience is the SESAR Joint Undertaking and the
consortium members: Agencia Estatal de Meteorología (Spain), MeteoSolutions
GmbH (Germany), University of Salzburg (Austria), University Carlos III of
Madrid (Spain), and University of Seville (Spain, consortium coordinator).

TBO-Met addresses the topic SESAR-04-2015 - Environment and Meteorology in
ATM, of the call H2020-SESAR-2015-1; in particular Meteorology. The overall
objective of the project is threefold: 1) to advance in the understanding of
the effects of meteorological uncertainty in TBO; 2) to develop methodologies
to quantify and reduce the effects of meteorological uncertainty in TBO; and
3) to pave the road for a future integration of the management of
meteorological uncertainty into the air traffic management system.

The DMP is intended to describe the data management life cycle for all
datasets to be collected, processed or generated by an H2020 project. The DMP
should address, at least, the data needed to validate the results presented in
scientific publications, including information on:

  * the handling of research data during and after the end of the project, 

  

  * what data will be collected, processed and/or generated, 

  

  * what methodology and standards will be applied, 

  

  * whether data will be shared /made open access, and 

  

  * how data will be curated and preserved (including after the end of the project). 

  

These elements are described in this document.

The input data used in the project is collected and identified in the
Appendix.

##  2 Introduction  1

According to the Guidelines on FAIR Data Management in H2020 [1], the Data
Management Plan (DMP) is intended to describe the data management life cycle
for all datasets to be collected, processed or generated by an H2020 project.
The DMP should address, at least, the data needed to validate the results
presented in scientific publications, including information on:

  * the handling of research data during and after the end of the project, 

  

  * what data will be collected, processed and/or generated, 

  

  * what methodology and standards will be applied, 

  

  * whether data will be shared /made open access, and 

  

  * how data will be curated and preserved (including after the end of the project). 

  

The TBO-Met project does not participate in the extended Open Research Data
Pilot; however, the delivery of a DMP was foreseen in the Grant Agreement on a
voluntary basis, because a DMP is a key element of good data management, and
implementing a good data management is considered to be a research best
practice.

This DMP describes a data management policy in line with the consortium
agreements on data management (see [2]), and consistent with exploitation and
Intellectual Property Rights (IPR) requirements. In particular, the data
management policy is based on making the research data findable, accessible,
interoperable and reusable (FAIR) in order to enhance knowledge discovery and
innovation, and subsequent data and knowledge integration and reuse.

The data handled in TBO-Met project is classified into three different
categories: Research data generated within the project, research data used
within the project and survey data. According to this classification, this
document is organized as follows. Next in this section, a list of acronyms is
given. A short explanation on generated research data is included in Section
3, whereas the used research data is described in Section 4. In Section 5, the
exclusion of survey data from data management is pointed out. Some provisions
for updating the DMP during TBO-Met project life cycle are given in Section 6
(the input data used in the project is collected and identified in the
Appendix). Finally, references are listed in Section 7.

#  3 Generation of Research Data

The TBO-Met project will not generate any research data, but it will develop
methodologies for trajectory planning under meteorological uncertainties, and
for sector demand analysis under meteorological uncertainties. In fact, one of
the expected outcomes of the project is to develop methodologies to quantify
the impact of meteorological uncertainty in TBO.

#  4 Use of Research Data

The TBO-Met project will make use of the following pre-existing research data:

  1. EPS data (provided by Met Offices). 

  

  2. Nowcast data (also provided by Met Offices). 

  

  3. Aircraft model data (provided by Eurocontrol). 

  

  

###  4.1 Data Description

Data used (EPS, Nowcast, and aircraft model) constitute the input of the
project, as they are needed to define methodologies for both trajectory
planning under meteorological uncertainty (WP4) and sector demand analysis
under meteorological uncertainty (WP5), and to perform the evaluation and
assessment of those methodologies (WP6).

####  EPS Data

In this project, EPS data are the output data of the global ensemble forecast
system ECMWF-EPS (ENS) and of the Grand Limited Area Model Ensemble Prediction
System GLAMEPS. AEMET as a project partner has access to data of these two
ensemble systems. In D2.1 [3], a larger description of ECMWFEPS and GLAMEPS,
and detailed information about data type, format, and processing technique can
be found. Relevant information will be excerpted below for completeness.

The meteorological information will include wind, temperature, and convection
indicators (or other variables that allow for computation of convection
indicators). The data concerning wind, temperature, and two convection
indicators will be obtained from ECMWF-EPS whereas the data concerning one of
these convection indicators and some temperatures that allow for the
computation of the other convection indicator will be obtained from GLAMEPS.

The data will be retrieved from the ECMWF MARS (Meteorological Archive and
Retrieval System) data base. The data will be downloaded as files in GRIB
format which contain meteorological parameters on a regular latitude-longitude
grid and in hybrid vertical coordinates for the desired forecast times. The
data will be extracted from the model grid to cover only the desired analysis
region in time and space for the flights to be examined. This is done with the
purpose of reducing the data amount and thus computation time in all further
data processing because the raw EPS output has a large or even global coverage
(ENS). The region to be extracted is defined by the minimum and maximum of
latitude/longitude, the pressure level where the flights will take place. The
extraction of the above defined sub grid can be realized by defining certain
request files for the MARS database interface.

####  Nowcast Data

In the 1  st  Steering Board (SB) Meeting, the definition of the nowcast data
to be used was set as an internal milestone. Therefore, this section will
subsequently be updated (see schedule in Section 6).

####  Aircraft Model Data

In the Kick-off Meeting of the TBO-Met project, it was decided to use the Base
of Aircraft DAta (BADA), from Eurocontrol. According to Eurocontrol [4], BADA
is made of two components: The model specifications, which provide the
theoretical fundaments used to calculate aircraft performance parameters, and
the datasets containing the aircraft-specific coefficients necessary to
perform calculations. It includes:

  * Aircraft operating parameters. 

  

  * Aerodynamic model. 

  

  * Fuel consumption model. 

  

  * Available thrust model. 

  

###  4.2 FAIR data management scheme

####  Making data findable

In order to make the data used in the project identifiable and locatable,
unique identifiers must be defined. In particular, the following is proposed:

  * EPS datasets will be identified by a string containing the following attributes: name, issuing office, date, delivery time, time step, coverage area, spatial grid resolution, barometric altitude, and variable name. 

  

  * Nowcast datasets. The identification of the nowcast data will be done once the data is defined (this section will be updated according to the schedule in Section 6. 

  

  * Datasets from BADA will be identified by the aircraft code and the BADA version. 

  

####  Making data accessible

Each dataset used in the TBO-Met project is obtained from a pre-existing data
base, whose access is restricted to registered users. Some TBO-Met project
partners have been granted access to those data bases, but they have accepted
terms and conditions of use including non-disclosure clauses. Therefore, the
datasets cannot be made openly available or shared. However, obtaining access
for this databases is not difficult (at least for researchers in ATM
community), and therefore good data accessibility is had.

For certain datasets, a specific software tool can be used to automatize the
access to data. In particular, for the data retrieved from the ECMWF MARS data
base, ECMWF have developed an application program interface (called GRIB-API)
to provide an easy and reliable way for encoding and decoding GRIB messages.
With the GRIB-API library, which is written entirely in C, some command line
tools are provided to give a quick way to manipulate GRIB data. Moreover, a
Fortran 90 interface is available giving access to the main features of the C
library. Further information on GRIB-API can be found in

[5].

####  Making data interoperable

To facilitate interoperability of the data used, standard vocabulary from ATM
and MET disciplines will be used throughout the project. No uncommon nor
project specific ontologies or vocabularies will be generated.

####  Making data reusable

There is no restrictions in data re-use by third parties, other than the fact
that these third parties must have granted access to the aforementioned pre-
existing data bases

###  4.3 Data storage

To store all the data used in the project, a private space in the TBO-Met
website will be created, where all the unique identifiers will be collected.

#  5 Survey Data

To help in achieving TBO-Met project objectives, a survey among the
stakeholders involved (airlines,

ANSPs and Network Manager) is to be performed (WP3). The goals of the survey
are to ensure TBOMet is aligned with their current meteorological practices in
aviation (particularly any issue regarding meteorological uncertainty), and to
understand future expectations regarding meteorological uncertainty
management. The survey will provide information on the type of meteorological
services/products being used; the common understanding of meteorological
uncertainty; how the different actors provide robustness to the systems; the
desired values of predictability; and the efficiency cost they are willing to
pay.

The collected and processed survey data will provide a first-hand expert
description of current practice and future expectations, which will serve as a
valuable reference for the project activities. However, the survey data are
(anonymized) personal data, not research data. This fact has two immediate
consequences.

On one hand, two ethics requirements (that the TBO-Met project must comply
with) related to the protection of these personal data were identified in the
project Grant Agreement [6], and included as deliverables D8.2 and D8.3 (Refs.
[7, 8]). In deliverable D8.2, detailed information on the procedures that will
be implemented for survey data collection, storage, protection, retention and
destruction and confirmation that they comply with national and EU legislation
is provided. In deliverable D8.3, detailed information on the informed consent
procedures that will be implemented is provided.

On the other hand, the survey data are excluded from the data management
process outlined in this document, because they follow the procedures for the
protection of the personal data.

#  6 Updating the Data Management Plan

Following the Guidelines on FAIR Data Management in H2020 [1], updates in the
DMP are foreseen as new input data are used in the project. This does not
exclude the possibility of updating the DMP whenever unexpected significant
changes arise, such as changes in consortium policies, and changes in
consortium composition and external factors, _inter alia_ . Furthermore, the
DMP will be updated in time with the periodic evaluation of the project (that
is, every six months), and in time with the final review. Hence, the timetable
for DMP review can be summarized as follows:

Table 6.1. DMP Updating Timetable  
  
<table>  
<tr>  
<th>

**Updating cause**

</th>  
<th>

**Due date**

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

Include data used in WP4

</td>  
<td>

T0+12 (31/05/2017)

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

Include data used in WP5

</td>  
<td>

T0+18 (30/11/2017)

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

###  Updates

The DMP has been updated on 01 March 2018, after finishing all the technical
tasks that have required new input data. This update includes an Appendix
where all the input data used in the project is collected and identified.