D1.3 Data Management Plan HURRICANE

Deli e able D1.3: Da a Managemen Plan 2025
Resilien and holisc
soluon o
fi s esponde s
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Inno aon P og am unde G an Ag eemen N°101168017. Views
and opinions exp essed a e howe e hose o he au ho (s) only
and do no necessa ily eflec hose o he Eu opean Union
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Table o Con en s
Lis o Tables ................................................................................................................................ 3
Documen His o y ........................................................................................................................ 4
Disclaime ................................................................................................................................... 5
Lis o Pa icipan s ........................................................................................................................ 5
1. Execu i e Summa y ............................................................................................................... 5
2. Ac onyms ............................................................................................................................. 6
3. In oduc ion .......................................................................................................................... 7
3.1 B ie desc ipon o he p ojec and i s objec es ........................................................................................... 7
3.2 Pu pose o he DMP and how i aligns wi h Ho izon Eu ope's Open Science policy ....................................... 7
4. Da a Summa y ...................................................................................................................... 7
4.1 Risk: The po enal impac i he da a is imp ope ly disclosed. Po enal use cases o he da a.................... 9
5. FAIR Da a Managemen ........................................................................................................ 10
5.1 Me ada a s anda ds and idenfie s (e.g., DOIs, URIs)................................................................................... 10
5.2 Naming con enons o da ase s .................................................................................................................. 10
5.3 Da a documen aon and me ada a schemas ................................................................................................ 11
5.4 File o ma s ensu ing in e ope abili y ........................................................................................................... 12
6. S o age and backup du ing he esea ch p ocess ................................................................... 12
6.1 Cen alized S o age wi h edundancy ............................................................................................................ 12
6.2 Au oma ed and Regula Backups ................................................................................................................... 12
6.3 Ve sion Con ol and Change Managemen .................................................................................................... 12
6.4 Compliance wi h Secu i y and Da a P o econ S anda ds ............................................................................ 12
7. Da a managemen esponsibili ies and alloca ion o esou ces .............................................. 13
7.1 Roles and esponsibilies o eam membe s in da a managemen .............................................................. 13
7.2 T aining equi emen s o da a handling ....................................................................................................... 14
7.3 Budge allocaon o da a managemen and s o age. .................................................................................. 14
8. Da a secu i y (sha ing and long- e m p ese a ion) ................................................................ 15
8.1 Da a Classificaon and Access Con ol .......................................................................................................... 15
8.2 Enc ypon and Secu e S o age ...................................................................................................................... 15
8.3 Long-Te m P ese aon S a egy .................................................................................................................. 15
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9. Legal and e hical equi emen s, codes o conduc ................................................................. 16
10. In ellec ual P ope y Righ s ............................................................................................... 16
Lis o Tables
Table 1 Types o da a o be collec ed, gene a ed, o eused ............................................................................. 8
Table 2 Po enal da a use cases ........................................................................................................................ 9
Table 3 Da a managemen esponsibilies pe WP ......................................................................................... 13
Table 4 Lis o da a s ewa ds om each o ganizaon ...................................................................................... 14
Table 5 P ese aon s a egies ........................................................................................................................ 15
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Documen His o y
PROJECT ACRONYM HURRICANE
P ojec Ti le Holisc UGV-based Resilien and Real-me In elligence o
C isis And Na u al Eme gency
G an Ag eemen Nº 101168017
P ojec Du aon 01/01/2025 – 31/12/2028 (48 Mon hs)
Wo k Package WP 1
DoA This deli e able e e s o Task 1.5
Deli e able No. D1.3
Due da e 06/30/2025
Submission da e 08/29/2025
Disseminaon SE
Deli e able Lead EURAC
Au ho name(s): Eka e ina Chup iko a
S a us 1.0
Da e Ve sion Au ho Commen
02/04/2025 0.1 Eka e ina
Chup iko a (EURAC)
Fi s e sion
02/19/2025 0.2 Eka e ina Chup iko a
(EURAC)
In e nal i e aon
02/25/2025 0.3 Eka e ina Chup iko a
(EURAC)
In e nal i e aon
03/07/2025 0.4 Eka e ina Chup iko a
(
EURAC)
In e nal i e aon
03/13/2025 0.5 Eka e ina Chup iko a
(EURAC)
In e nal i e aon
05/30/2025 0.6 Eka e ina Chup iko a
(
EURAC)
In e nal i e aon
06/20/2025 0.7 Eka e ina Chup iko a
(EURAC)
In e nal i e aon
06/20/2025 0.8 Eka e ina Chup iko a
(
EURAC)
In e nal i e aon
06/23/2025 0.9 Lucia Paladino (EURAC) Re iew
08/29/2025 1.0
Ab aham MEJIA-AGUILAR
(EURAC)
Final e sion
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Disclaime
Funded by he Eu opean Union unde he Ho izon Eu ope F amewo k P og amme G an Ag eemen Nº:
101182176. Views and opinions exp essed a e howe e hose o he au ho (s) only and do no necessa ily
eflec hose o he Eu opean Union o o he Eu opean Resea ch Execu e Agency. Nei he he Eu opean
Union no he g anng au ho i y can be held esponsible o hem.
Lis o Pa cipan s
Pa cipan No. Pa cipan legal name Sho Name Type Coun y
1 (Coo d.) Academia Eu opea di Bolzano EURAC RTO IT
2 Robo nik Au omaon SL ROB SME SP
3 MAVTech s. .l. MAV SME IT
4 Ins u o de Engenha ia de Sis emas e Compu ado es,
Tecnologia E Ciência
INESC TEC RTO PT
5 Cen e Technologique ALPhANOV ALPhA RTO FR
6 Uni e si y o Twen e UTwen e ACA NTHDS
7 Uni e sidad Complu ense de Mad id UCM ACA SP
8 XLIM Resea ch Ins u e - CNRS UMR N°7252 XLIM ACA FR
9 MidGa d SAS MidGa d SME FR
10 Blue Tenso s. .l. BlueTenso SME IT
11 Uni e si y o Žilina UNIZA ACA SK
12 TIMELEX BV TLX SME BE
13 Se ice d’incendie e de secou s de Hau e Co se SIS2B Fi s R. FR
14 Agencia de Segu idad y Gesón In eg al de Eme gencia
-
INFOCA
EMA-INFOCA Fi s R. SP
15 Ayun amien o de Almuñeca ALMU Au ho i y SP
1. Execu e Summa y
HURRICANE will unlock he po enal o UGV ope aon in haza dous en i onmen , elying on enhanced ision
capabilies and sma in eg aon o e a holisc, esilien and eal-me si uaonal awa eness in as uc u e
ha includes inno a e UAV-UGV coope aon pa hways and mul- echnology communicaon
in as uc u e. Da a-d i en opmizaon models will p o ide ecommendaons h ough a use - iendly API
o suppo fi s esponde s’ accs. Th ee complemen a y pilo s will be implemen ed o demons a e he
benefi s b ough by HURRICANE soluons. Las , bu no leas , EU-wide aining modules will be implemen ed
o aise awa eness among fi s esponde s abou hese inno a e echnologies, in eg ang new ope aonal
p ocedu es.

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2. Ac onyms
AI A ficial In elligence
COTS Comme cial Off-The-Shel
D&E&C Disseminaon, Exploi aon, Communicaon
FR Fi s Responde s
FSO F ee Space Opcs
KER Key Exploi able Resul s
KET Key Enabling Technology
KIP Key Impac Pa hway
KPI Key Pe o mance Indica o s
KSO Key S a egic O ien aons
IPR In ellec ual P ope y Righ s
LoS Line o Sigh
OWC Opcal Wi eless Communicaons
QoS Quali y o Se ice
P/M Pe sons/mon hs
SO Specific Objec e
SoA S a e-o - he-A
UAV Unmanned Ae ial Vehicle
UGV Unmanned G ound Vehicle
UxV Unmanned Vehicle
WP Wo k packages
WPT Wi eless Powe T ans e
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3. In oducon
3.1 B ie desc ipon o he p ojec and i s objec es
P og amme: Disas e -Resilien Socie y 2023
Call: Robocs: Au onomous o semi-au onomous UGV sys ems o supplemen skills o use in haza dous
en i onmen s (HORIZON-CL3-2023-DRS-01-05)
HURRICANE’s ision is he es ablishmen o UGV sys ems – and, in a b oade sense, au onomous sys ems -
as a s anda d o i s esponde s’ (FR) ope a ions. Thanks o enhanced sensing capabili ies, UGV will p o ide
high quali y g ound da a o be sen o he command s a ion, elying on an inno a i e communica ion
in as uc u e ha in ol es s ong coope a ion wi h UAV. This will allow a cu ing-edge eal- ime si ua ional
awa eness ha will eed da a op imiza ion models which will gene a e eliable ecommenda ions o i s
esponde s.
3.2 Pu pose o he DMP and how i aligns wi h Ho izon Eu ope's Open Science
policy
The DMP aligns wi h Ho izon Eu ope's Open Science policy, which emphasizes open access, anspa ency,
and he eusabili y o esea ch ou pu s while ensu ing da a p i acy and secu i y whe e necessa y. To suppo
hese p inciples, he p ojec commi s o open access and FAIR da a by making esea ch ou pu s a ailable
h ough eposi o ies such as ZENODO o he Eu opean Open Science Cloud (EOSC), ensu ing ha me ada a
and non-sensi i e da ase s a e openly sha ed o maximize hei impac wi hin he scien i ic communi y.
Fu he mo e, he DMP acili a es s uc u ed da a sha ing among conso ium membe s, eme gency esponse
agencies, and esea ch ins i u ions, p omo ing collabo a ion and in e ope abili y ac oss di e en
s akeholde s.
4. Da a Summa y
Table 1 in eg a es he p e iously defined da a ca ego ies wi h hei o igins. I shows ha mos da a a e
de i ed om obse aonal sou ces ( eal-me senso ou pu s and s akeholde eedback) and expe imen al
se ups (con olled es s and pilo demons aons). In addion, simulaon-based and hi d-pa y da a (e.g.,
sa elli e image y) complemen he p ojec da ase s, suppo ng obus analysis and decision-making ac oss
a ious wo k packages.
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Da a
Da a Type
Fo ma s
WP
Sensi i y
O igin
Senso &
Image y Da a
High- esoluon ideo
and sll images (RGB,
he mal, NIR), dehazed
images, LIDAR eadings,
and o he senso logs
JPEG, PNG,
RAW ideo
files,
CSV/Bina y
senso logs
WP2 – Enhanced
UGV Sensing
High (mission-
c ical,
ope aonal)
Expe imen al
/
Obse aonal
Geospaal &
Mapping Da a
2D/3D maps, Digi al
Su ace Models,
mulspec al maps
gene a ed om
combined UGV/UAV da a
GeoTIFF, PNG
Shapefiles,
o he GIS
o ma s
WP2/WP3 –
Sensing &
Na igaon
Medium
(open o
public
o ma s)
Expe imen al
/
Obse aonal
Communicaon
& Teleme y
Da a
Real-me
communicaon logs
(RF/opcal), eleme y
da a (posioning,
na igaon, pe o mance
me ics), signal quali y
(SNR, la ency)
CSV, JSON,
XML,
p op ie a y
senso logs
WP4 – Resilien
Communicaon
In as uc u e
High (secu i y
and
ope aonal
de ails)
Expe imen al
/
Obse aonal
Remo e Sensing
& Sa elli e Da a
SAR image y, opcal
image y, and
wea he /en i onmen al
da a om sa elli e
sys ems (e.g.,
Cope nicus)
GeoTIFF,
Ne CDF, HDF
WP5 – Da a-
d i en
Opmizaon
Models
Medium
(mos ly public
sou ces)
Thi d-Pa y
Expe imen al &
Pilo
Demons aon
Da a
Field es measu emen s,
en i onmen al condion
eco ds, ope aonal
pe o mance me ics,
and pilo demons aon
epo s
CSV, Excel,
senso logs,
PDF epo s
WP7
–
Demons a o s
High
(p op ie a y
pilo da a)
Expe imen al
S akeholde &
Use -Gene a ed
Da a
Su ey esponses,
in e iew ansc ip s,
wo kshop eedback, and
consul aon ou comes
Tex
documen s,
audio
eco dings,
sp eadshee s
WP1/DEC
–
S akeholde
Engagemen &
Managemen
High (pe sonal
and sensi e
in o maon)
Obse aonal
Modeling &
Simulaon Da a
T aining da ase s,
simulaon ou pu s,
haza d p edicon
models, and opmizaon
model ou pu s
CSV, HDF5,
pickle files,
MATLAB
o ma s
WP5 –
Opmizaon
Models &
Visualizaon
Tools
Medium
(in e nal use,
modeling
da a)
Simulaon-
Based
Table 1 Types o da a o be collec ed, gene a ed, o eused
The sensi i y column indica es:
 Confidenali y: How p i a e o c ical he da a is.
 P o econ Requi emen s: The le el o secu i y measu es needed.
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4.1 Risk: The po en ial impac i he da a is imp ope ly disclosed. Po enal use
cases o he da a
Table 2 ou lines key po enal use cases o he collec ed da a. I highligh s how da a om a ious sou ces—
such as senso image y, geospaal maps, and simulaon ou pu s—can be in eg a ed o enhance eal-me
si uaonal awa eness, suppo au onomous na igaon, in o m eme gency decision suppo sys ems,
o ecas haza ds, moni o communicaon esilience, and de elop aining simulaons o fi s esponde s.
Each use case idenfies he ele an da a ypes and desc ibes he benefi s, including imp o ed esponse
mes, enhanced sa e y, and p oac e disas e managemen .
Use case Desc ipon Rele an Da a Types Benefi s
Real-Time Si uaonal
Awa eness
In eg aon o mul-
senso da a ( ideo,
he mal, LIDAR, e c.)
o build a li e
ope aonal pic u e
Senso & Image y,
Communicaon &
Teleme y, Geospaal
Da a
Enhanced decision-making and apid
esponse
Au onomous
Na igaon & Obs acle
A oidance
Use o senso usion
and mapping da a o
suppo UGV/UAV
na igaon in complex,
haza dous e ains
Senso & Image y,
Geospaal Da a
Imp o ed mobili y and sa e y in
eme gency en i onmen s
Eme gency Decision
Suppo
Da a-d i en
opmizaon models
ha ansla e aw da a
in o aconable
ecommendaons
Modeling &
Simulaon,
Expe imen al Da a,
Remo e Sensing
Timely guidance o esou ce
deploymen and haza d migaon
Haza d P edicon &
Fo ecasng
P edic e models
using simulaon and
emo e sensing da a
o o ecasng e en s
like fi es o s uc u al
damage
Simulaon Da a,
Remo e Sensing Da a
P oac e disas e planning and isk
educon
Communicaon
Resilience Moni o ing
Real-me moni o ing
o communicaon
channels o ensu e
obus connec i y
du ing c ises
Communicaon &
Teleme y Da a
Sus ained connec i y and
ope aonal eliabili y
T aining & Simulaon
o Fi s Responde s
Using eal-wo ld da a
o de elop i ual
aining scena ios and
simulaons o fi s
esponde s
Expe imen al Da a,
S akeholde & Use -
Gene a ed Da a,
Simulaon Da a
Imp o ed p epa edness and skill
de elopmen
Table 2 Po en ial da a use cases
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9. Legal and e hical equi emen s, codes o conduc
The HURRICANE p ojec embeds igo ous compliance and legal conside aons wi hin i s da a managemen
plan o ensu e ha all p ojec ac ies mee cu en and e ol ing egula o y s anda ds. The p ojec will
conduc a comp ehensi e legal assessmen ocusing on EU da a p o econ egulaons such as GDPR,
alongside eme ging amewo ks like he AI Ac , o sa egua d pe sonal and ope aonal da a. This in ol es
ensu ing da a in eg i y, quali y, and aceabili y h ough obus da a go e nance p acces, as well as
implemenng cybe secu i y measu es o p o ec agains unau ho ized access and cybe h ea s. Addionally,
he legal amewo k will add ess c oss-bo de da a ans e s and he in e play be ween UGV-UAV sys ems
and exisng communicaon in as uc u es, ensu ing ha all echnologies and da a sha ing p acces comply
wi h naonal and in e naonal s anda ds. These measu es, combined wi h ongoing consul aons wi h legal
and e hical expe s, gua an ee ha Hu icane’s inno a e soluons uphold ci il libe es and p omo e us
among s akeholde s while os e ing a ha monized egula o y en i onmen ac oss he EU.
10. In ellec ual P ope y Righ s
The HURRICANE p ojec p io izes clea and ai In ellec ual P ope y Righ s (IPR) a angemen s o suppo
inno aon, ensu e anspa ency, and enable effec e collabo aon. These a angemen s align wi h he
G an Ag eemen and a e go e ned by he Conso um Ag eemen (CA), which defines he managemen o
backg ound and o eg ound knowledge, access igh s, and licensing e ms.
 P ima y da a—collec ed o p oduced du ing p ojec ac ies—will be co-owned by he conso um
bu e ain he in ellec ual au ho ship o he indi iduals who gene a ed hem. These con ibu o s mus
be c edi ed in any euse o publicaon. They also ha e he igh o be consul ed be o e ex e nal da a
sha ing, especially be o e he official public elease, o ensu e e hical use and main ain in e nal us .
 Seconda y da a—exisng o ex e nally sou ced da a— emain he sole p ope y o he o iginal
p o ide . Thei use is subjec o exisng licenses o ag eemen s. Howe e , i seconda y da a a e
p ocessed (e.g., ia modeling o machine lea ning) o c ea e new da ase s, hese will be ea ed as
new p ojec ou pu s and all unde he same co-owne ship and au ho ship ules as p ima y da a.
 Access o p ima y and de i ed da a will be g an ed unde ai and easonable condions, ollowing
Open Science p inciples while especng con ibu o 's igh s. Any ex e nal da a sha ing will comply
wi h he p ojec ’s Open Access policy (e.g., using CC-BY licenses), wi h clea c edi and ci aon
equi emen s.
 Collabo a e ou pu s will be join ly owned, wi h a Join Owne ship Ag eemen (JOA) defining e ms
o use, licensing, e enue sha ing, and access.
All IPR policies in HURRICANE adhe e o FAIR p inciples, s iking a balance be ween openness, p ope
a ibuon, legal cla i y, and long- e m da a sus ainabili y.