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Union´s Ho izon Eu ope esea ch and Inno a ion
p og amme unde he ag eemen No. 101136701
DELIVERABLE 6.2
Da a Managemen Plan - 1
D6.2 – Da a Managemen Plan - 1
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P ojec i le
BRinging E idence-bAseD ood Chain solu ions o p e en and RedUce ood
was e ela ed o Ma ke ing s anda ds, and deli e clima e and ci cula i y co
Bene i s
P ojec ac onym
BREADCRUMB
Call opic
HORIZON-CL6-2023-FARM2FORK-01
Type o ac ion
HORIZON-RIA
Coo dina o
EIGEN VERMOGEN VAN HET INSTITUUT VOOR LANDBOUW- EN
VISSERIJONDERZOEK - EV ILVO
P ojec numbe
101136701
P ojec s a da e
01/01/2024
Du a ion
36 mon hs
URL
h ps://www.b eadc umb-p ojec .eu/
D6.2 – DATA MANAGEMENT PLAN - 1
Due da e
31/03/2024
Deli e y da e
30/03/2024
Wo k package
WP6
Responsible Au ho (s)
Capwell Fo bang Echo (EV-ILVO), Anna Twa ogowska (EV-ILVO), So ie De
Man (EV-ILVO), Rani Van Gompel (EV-ILVO), Ka ima Abunada (EV-ILVO).
Con ibu o (s)
Re iewe (s)
Sasa S aus (ITC), Lau a Mo cillo (PNO)
Ve sion
1.0
Dissemina ion le el
Public
D6.2 – Da a Managemen Plan - 1
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DISCLAIMER
The con en o he publica ion he ein is he sole esponsibili y o he publishe s and i does no necessa ily
ep esen he iews exp essed by he Eu opean Commission o i s se ices.
While he in o ma ion con ained in he documen s is belie ed o be accu a e, he au ho s(s) o any o he
pa icipan in he BREADCRUMB conso ium make no wa an y o any kind wi h ega d o his ma e ial
including, bu no limi ed o he implied wa an ies o me chan abili y and i ness o a pa icula pu pose.
Nei he he BREADCRUMB Conso ium no any o i s membe s, hei o ice s, employees o agen s shall be
esponsible o liable in negligence o o he wise howsoe e in espec o any inaccu acy o omission he ein.
Wi hou de oga ing om he gene ali y o he o egoing nei he he BREADCRUMB Conso ium no any o i s
membe s, hei o ice s, employees o agen s shall be liable o any di ec o indi ec o consequen ial loss o
damage caused by o a ising om any in o ma ion ad ice o inaccu acy o omission he ein.
COPYRIGHT MESSAGE
© BREADCRUMB Conso ium, 2024-2026. This deli e able con ains o iginal unpublished wo k excep whe e
clea ly indica ed o he wise. Acknowledgmen o p e iously published ma e ial and o he wo k o o he s has
been made h ough app op ia e ci a ion, quo a ion, o bo h. Rep oduc ion is au ho ised p o ided he sou ce is
acknowledged.
VERSION AND AMENDMENTS HISTORY
Ve sion
Da e
(DD/ MM/ YYYY)
C ea ed
/Amended by
Changes
0.1
29/03/2024
Capwell Fo bang Echo
Fi s d a
0.2
04/04/2024
Lau a Mo cillo
Re iew
1.0
15/04/2024
Capwell Fo bang Echo
Mino changes and
s yling
D6.2 – Da a Managemen Plan - 1
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TABLE OF CONTENTS
TABLE OF CONTENTS ..................................................................................................................................... 3
EXECUTIVE SUMMARY ................................................................................................................................... 8
1 INTRODUCTION ....................................................................................................................................... 9
1.1 MAIN AIMS OF BREADCRUMB ............................................................................................................ 9
1.2 FROM BREADCRUMB OUTPUTS TO IMPACT ...................................................................................... 11
1.3 DATA MANAGEMENT IN BREADCRUMB ............................................................................................ 12
2 FAIR DATA .............................................................................................................................................. 14
2.1 MAKING DATA FINDABLE, INCLUDING PROVISIONS FOR METADATA ...................................................... 14
2.2 MAKING DATA ACCESSIBLE ............................................................................................................. 16
2.2.1 Open da a .................................................................................................................................... 16
2.2.2 Closed da a .................................................................................................................................. 16
2.2.3 Assigning a eposi o y o Open Access o da a in he p ojec .................................................... 17
2.3 MAKING DATA INTEROPERABLE ..................................................................................................... 18
2.4 ENHANCING DATA RE-USE ................................................................................................................ 19
2.4.1 Licensing ...................................................................................................................................... 19
2.4.2 Re-use pa hways ......................................................................................................................... 20
2.4.3 Da a quali y assu ance ................................................................................................................ 20
3 DATA OVERVIEW ................................................................................................................................... 22
3.1 DATA GENERATED AND ITS PURPOSE ................................................................................................... 22
3.2 DATA TYPE AND FORMATS................................................................................................................... 24
3.3 DATA PROVENANCE ............................................................................................................................ 30
3.4 DATA UTILISATION .............................................................................................................................. 31
3.5 RE-USE OF DATA ................................................................................................................................ 32
3.6 PRACTICALIZING THE FAIR PRINCIPLES PER WP ................................................................................. 33
4 ALLOCATION OF RESOURCES ............................................................................................................ 36
4.1 WHAT WILL THE COSTS BE FOR MAKING DATA AND OTHER RESEARCH OUTPUTS FAIR IN YOUR PROJECT? 36
4.2 HOW WILL THESE COSTS BE COVERED? ............................................................................................... 36
4.3 WHO WILL BE RESPONSIBLE FOR DATA MANAGEMENT IN YOUR PROJECT? ............................................. 36
4.4 HOW WILL LONG-TERM PRESERVATION BE ENSURED? .......................................................................... 37
5 DATA SECURITY .................................................................................................................................... 38
5.1 WHAT PROVISIONS ARE OR WILL BE IN PLACE FOR DATA SECURITY? ...................................................... 38
5.2 WILL THE DATA BE SAFELY STORED IN TRUSTED REPOSITORIES FOR LONG TERM PRESERVATION AND
CURATION? .................................................................................................................................................... 39
6 ETHICS .................................................................................................................................................... 40
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6.1 ARE THERE, OR COULD THERE BE, ANY ETHICS OR LEGAL ISSUES THAT CAN HAVE AN IMPACT ON DATA
SHARING? ...................................................................................................................................................... 40
6.2 WILL INFORMED CONSENT FOR DATA SHARING AND LONG TERM PRESERVATION BE INCLUDED IN
QUESTIONNAIRES DEALING WITH PERSONAL DATA ............................................................................................ 41
7 ANNEX ..................................................................................................................................................... 42
7.1 ANNEX 1: BREADCRUMB DELIVERABLE QUALITY REVIEW TOOL ............................................................ 42
7.2 ANNEX 2: INFO SHEET ANONYMISING OR PSEUDONYMISING DATA .......................................................... 45
7.2.1 Why anonymise o pseudonymise? ............................................................................................. 45
7.2.2 Wha is anonymisa ion o pseudonymisa ion? ............................................................................ 46
7.2.3 S o age o he da a ...................................................................................................................... 47
7.2.4 When o anonymise o pseudonymise? ...................................................................................... 48
7.2.5 How o anonymise o pseudonymise? ......................................................................................... 48
7.3 ANNEX 3: TEMPLATE INFORMATION SHEET AND INFORMED CONSENT .................................................... 54
7.4 ANNEX 4: TEMPLATE FOR AN APPROVAL OF COMESSH FROM EV ILVO ............................................... 57
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LIST OF FIGURES
FIGURE 1: BREADCRUMB AT A GLANCE .................................................................................................. 10
FIGURE 2: OVERVIEW OF BREADCRUMB IMPACT PATHWAYS............................................................. 11
FIGURE 3: FLOW OF DATA IN BREADCRUMB PROJECT ........................................................................ 13
LIST OF TABLES
TABLE 1: LIST OF DESIGNATED DATA PROTECTION STEWARDS (DPSS) .......................................... 12
TABLE 2: FIRST QUALIFIER THAT REFERS TO THE DATA COLLECTION METHOD ............................ 18
TABLE 3: DELIVERABLE OVERVIEW ACCORDING TO THE BREADCRUMB GRANT AGREEMENT ... 25
TABLE 4: IMPLEMENTATION OF THE FAIR PRINCIPLE PER WP ............................................................ 33
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Glossa y o e ms and ac onyms used
Ac onym/Te m
Desc ip ion
ABM
Agen -Based Model
AI
A i icial In elligence
CC0
C ea i e Commons no igh s ese ed
CC BY
C ea i e Commons A ibu ion License
CERN
Conseil Eu opéen pou la Reche che Nucléai e
ComESSH
Commission o E hics in Social Science and Humani ies
CS
Case S udy
CSV
Comma-sepa a ed alues
D
Deli e able
DDMMYYYY
Day and Mon h in 2 numbe s, Yea in 4 numbe s e.g. 31042024
DM
Da a Managemen
DMP
Da a Managemen Plan
DMT
Da a Managemen Team
Docx
Mic oso Wo d ex documen
DOI
Digi al Objec Iden i ie
DPS
Da a P o ec ion S ewa d
EU
Eu opean Union
FAIR
Findable, Accessible, In e ope able, and Reusable
FLW
Food Loss & Was e
FW
Food Was e
GDPR
Gene al Da a P o ec ion Regula ion
GIT
Global In o ma ion T acke
HE
Ho izon Eu ope
IP1, 2, 3, …
Impac Pa hway 1
ISO
In e na ional S anda ds O ganisa ion
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JRC
Joined Resea ch Cen e
M
Mon h
MS
Membe S a es
IDI
In-dep h In e iews
FGI
Focus G oup In e iew
MOA
Mo i a ion, Oppo uni y, Abili y
MP3, MP4
Mo ion Pic u es Expe G oup Audio Laye 3, 4
MS
Mic oso
O1
Objec i e 1
OEI
O he E hics Issues
ORD
O ice o Resea ch and De elopmen
PID
Pe sonal Iden i iable Da a
R1, 2, 3, …
Resul 1
R&I
Resea ch & Inno a ion
RAR
Roshal A chi e o ma
SSL/TLS
Secu e Socke s Laye /T anspo Laye Secu i y
TXT
Tex
USB
Uni e sal Se ial Bus
WP
Wo k Package
T
Task
ZIP
Comp essed ile
TCB
Technical Coo dina ion Boa d
SEN
Sensi i e
PU
Public
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EXECUTIVE SUMMARY
The Da a Managemen Plan – 1 is a i s o h ee planned epo s ha p o ides a comp ehensi e o e iew o
he key aspec s add essed in he BREADCRUMB p ojec , ocusing on da a managemen , FAIR p inciples
implemen a ion, esou ce alloca ion, da a secu i y, and e hical conside a ions.
The BREADCRUMB p ojec aims o acili a e impac ul esea ch ou comes h ough e ec i e da a managemen
p ac ices. By ensu ing he anspa ency, accessibili y, and in e ope abili y o da a, he p ojec seeks o
maximize he u ili y and eusabili y o esea ch ou pu s.
Emphasizing he p inciples o Findabili y, Accessibili y, In e ope abili y, and Reusabili y (FAIR), he DMP
s a egies o making da a mo e disco e able, accessible, and usable. This includes p o isions o me ada a,
open and closed da a access, eposi o y assignmen , and pa hways o da a e-use. The da a o e iew sec ion
u he delinea es he ypes, o ma s, p o enance, and u iliza ion o da a gene a ed wi hin he p ojec . By
unde s anding he na u e and pu pose o he da a, s akeholde s can be e le e age i o esea ch pu poses
and ensu e compliance wi h FAIR p inciples. Addi ionally, e ec i e esou ce alloca ion is c ucial o
implemen ing FAIR da a p ac ices. This sec ion ou lines he an icipa ed cos s, unding sou ces, esponsible
pa ies o da a managemen , and s a egies o long- e m p ese a ion o ensu e he sus ainabili y o he
p ojec 's da a in as uc u e. Mo eso, add essing conce ns abou da a secu i y, he DMP highligh s p o isions
in place o sa egua d da a in eg i y and con iden iali y. T us ed eposi o ies and p o ocols o long- e m
p ese a ion and cu a ion a e emphasized o mi iga e isks associa ed wi h da a s o age and sha ing. E hical
conside a ions a e pa amoun in da a-in ensi e esea ch p ojec s. The DMP acknowledges po en ial e hical
and legal implica ions o da a sha ing, emphasizing he impo ance o in o med consen and adhe ence o
p i acy egula ions in handling pe sonal da a.
In conclusion, he BREADCRUMB p ojec as highligh ed in he DMP is commi ed o p omo ing anspa ency,
accessibili y, and e hical in eg i y in da a managemen p ac ices. By adhe ing o FAIR p inciples, alloca ing
esou ces e ec i ely, ensu ing da a secu i y, and upholding e hical s anda ds, he p ojec aims o maximize
he impac o i s esea ch ou comes while sa egua ding he igh s and p i acy o indi iduals in ol ed.
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Ve sioning
Ve sion e e s o sa ing new copies o iles, so p e ious e sions can be e e ed o. This p ac ice o acking
and managing changes made o a ile o e ime ensu es ha a eco d o changes is being made o he iles
and o gi e he new iles a unique name. Each ime a ile is modi ied, sa ed, o upda ed, a new e sion is
c ea ed, allowing use s o access p e ious i e a ions o he ile i needed. This p ocess helps in main aining a
his o y o changes, acili a ing collabo a ion, and ensu ing accoun abili y in p ojec s o documen managemen
sys ems. A unique e sion numbe should be assigned o each e sion o a documen depending on whe he
he changes a e signi ican (majo ) o no (mino ).
In he BREADCRUMB p ojec , a s ic e sioning o he p ojec iles and documen s will be ollowed:
✓ The au ho o he documen will ensu e he cu en e sion numbe is iden i ied on he app op ia e
place on he i s page o he documen .
✓ The i s d a o a documen will be e sion 0.1, while subsequen d a s will be an inc ease o “0.1
” in he e sion numbe (e.g., 0.2, 0.3, 0.4, 0.9, 0.10, e c.).
✓ The i s inal e sion o a documen will be Ve sion 1.0, while Subsequen inal documen s will ha e
an inc ease o “1.0” in he e sion numbe (1.0, 2.0, e c.)
✓ The second inal e sion o a documen a e e iewing by a pa ne will be Ve sion 1.1, 1.2, e c.
Me ada a
P o enance me ada a shows he sou ce and his o y o an objec . All BREADCRUMB da ase s mus ha e he
ollowing p o enance me ada a de ined in he Da a P o ocol (D1.1):
da ase PID
da ase desc ip ion,
da ase da e o deposi (da a ange),
da ase au ho (s),
da ase enue(in e nal and ex e nal),
da ase emba go,
HE unding s a emen ,
p ojec name,
p ojec ac onym,
p ojec numbe ,
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licensing e ms,
PID o he au ho s,
PID o he au ho s’ o ganiza ions,
PID o he g an ,
PID o ela ed publica ions and o he ou pu s.
In addi ion, he da a p o ocol (D1.1) de ines addi ional da a ype-speci ic me ada a, enume a ing all manda o y
me ada a o be collec ed by esponsible pa ne s. Alongside he da a om he p ojec , ele an me ada a will
be deposi ed in eposi o ies iden i ied in D1.1. I he eposi o y o e s such an op ion, keywo ds o me ada a
will be a ailable.
Apa om he p ojec 's me ada a, ele an me ada a as speci ied in he D1.1 will be deposi ed in he speci ied
eposi o ies (D1.1). I he eposi o y o e s he op ion o ha es ing and indexing me ada a, hen me ada a
om he p ojec and i s a ious ou pu s will be indexed and a ailable o ha es ing.
2.2 Making da a ACCESSIBLE
2.2.1 Open da a
All da a compiled on he p ojec websi e will be made publicly a ailable. This includes:
✓ In o ma ion on exis ing ood ma ke ing s anda ds, as well as anonymized da a om case s udies,
p e iously app o ed by he da a owne h ough in o med consen .
✓ Da a conce ning he MOA model and Role Playing Games, when applicable and app o ed by he da a
owne h ough in o med consen .
✓ De ails o e en s and ac i i ies, such as enue, da e, ype o demons a ions, and pa icipa ing ac o s.
✓ Deli e ables, epo s, scien i ic pape s, capaci y-building ma e ials, and communica ion and
dissemina ion ma e ials.
Accessing he websi e equi es s anda d ools: a web b owse and, o accessing p ojec documen s, MS O ice
o Linux. Da ase s will be anonymized whene e possible. I only pseudonymiza ion is easible, he da ase
will no be publicly accessible due o GDPR egula ions. Sensi i e s akeholde da a held by conso ium
pa ne s (e.g., email and con ac lis s) o communica ion and dissemina ion pu poses mus be s o ed wi h
passwo d-based use au hen ica ion on pa ne ins i u ion se e s.
2.2.2 Closed da a
Sensi i e da a, including de ails o da a collec ion (e.g., da e, o ma , loca ion), mus no be openly accessible.
Any in o ma ion ha could iden i y a na u al pe son, o 'Da a Subjec ,' will be anonymized be o e s o age on
se e s. Business- ela ed da a, such as company owne ship and p ope y de ails, a e conside ed sensi i e
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and mus be emo ed du ing da a anonymiza ion. Fo u he de ails on in o med consen p ocedu es, see he
E hics sec ion.
2.2.3 Assigning a eposi o y o Open Access o da a in he p ojec
The openly a ailable da a will be accessible ia a ee and s anda dized access p o ocol. Pe he g an
ag eemen , BREADCRUMB will ensu e ha openly a ailable da a is accessible h ough an open eposi o y.
The conso ium pa ne s ha e chosen ZENODO o his pu pose due o i s pla o m's sa e y, us wo hiness,
ci abili y, immedia e access, lexibili y o open o closed access, e sioning capabili ies, Gi Hub in eg a ion,
and usage s a is ics acking. This eposi o y will include in o ma ion accompanying any esea ch ou pu .
BREADCRUMB will hence, use ZENODO eposi o y as a main ool o making esea ch da a indable in
acco dance wi h he HE Open Access manda e. This is based on he ecommenda ion o se e al p ojec
pa ne s who ha e knowledge o he unc ional and usage o ZENODO eposi o y in p e ious p ojec s. The e
is lexibili y o p ojec pa ne s o selec o he us ed eposi o ies while aking in o accoun he speci ied
guidelines. All p e e ed eposi o ies we e eco ded in D1.1. Howe e , i pa ne s p e e ano he eposi o y,
hey ha e o in o m he p ojec coo dina o . This was discussed a he kick-o mee ing.
ZENODO, ope a ed by he Conseil Eu opéen pou la Reche che Nucléai e (CERN), is a po al buil upon he
widely ecognized Global In o ma ion T acke (GIT) e sion con ol sys em and he Digi al Objec Iden i ie
(DOI) sys em. Aligned wi h he FAIR p inciples, i se es as an ideal choice o his pu pose. ZENODO
acili a es he disco e y, access, euse, and in e ope abili y o da ase s, in line wi h he equi emen s o O ice
o Resea ch and De elopmen (ORD) p ojec s. I s eposi o y se ices a e p o ided ee o cha ge, allowing
esea che s o sha e and p ese e a ious esea ch ou pu s, including da ase s, images, p esen a ions,
publica ions, and so wa e, ega dless o size o o ma . Th ough es ablished p ac ices like mi o ing and
egula backups, bo h he digi al da a and associa ed me ada a a e sa egua ded. Each uploaded da ase is
alloca ed a unique DOI, ensu ing i s dis inc iden i ica ion, aceabili y, and ci abili y. Fo publicly a ailable da a
on ZENODO, he pla o m's me ada a s anda ds can be applied.
The secu i y se ings o ZENODO a e summa ized as ollows:
✓ Ve sions: Da a iles unde go e sioning, while eco ds do no . Uploaded da a is a chi ed as a
Submission In o ma ion Package, and de i a i es a e c ea ed wi hou al e ing he o iginal con en .
Reco ds can be wi hd awn om public iew, bu bo h da a iles and eco ds a e p ese ed.
✓ Replicas and ile p ese a ion: All da a iles a e s o ed p ima ily in he CERN Da a Cen es in Gene a,
wi h addi ional eplicas in Budapes . These iles a e main ained in mul iple eplicas wi hin a dis ibu ed
ile sys em, which unde go nigh ly backups on o ape.
✓ Re en ion pe iod: I ems emain in he eposi o y o i s li e ime, wi h ZENODO CERN's hos labo a o y
de ining a minimum eposi o y li espan o he nex 20 yea s.
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✓ Func ional p ese a ion: ZENODO does no gua an ee he ongoing usabili y and comp ehensibili y o
deposi ed objec s o e ime.
✓ Fixi y and au hen ici y: Each da a ile is s o ed wi h an MD5 checksum o i s con en , and egula
checks a e conduc ed agains hese checksums o ensu e he in eg i y o he ile con en .
✓ Succession plans: In he e en o eposi o y closu e, ZENODO commi s o mig a ing all con en o
sui able al e na i e ins i u ional and/o subjec -based eposi o ies.
The da ase PID is alloca ed by he da a eposi o y.
2.3 Making da a INTEROPERABLE
In BREADCRUMB, each da a ile/se should be iden i ied by a unique name, as p oposed and elabo a ed in
D1.1 Da a P o ocol. The naming con en ion adhe es o he ollowing ules:
✓ A da a ile/da ase name consis s o se e al pa s (quali ie s) connec ed by pe iods,
✓ Each quali ie mus begin wi h an alphabe ic cha ac e (A-Z) o a special cha ac e ($,#,@),
✓ Each quali ie may con ain alphabe ic cha ac e s (A-Z), digi s (0-9), a hyphen (-), o he special
cha ac e s ($, #, @),
✓ Each quali ie should be as sho and meaning ul as possible,
✓ Each da a ile/se name should be as sho and meaning ul as possible,
✓ Da a ile/se name should include a leas wo quali ie s; he i s quali ie e e s o he da a collec ion
me hod/ echnique and s a s wi h a capi al le e (Table 2)
Table 2: Fi s quali ie ha e e s o he da a collec ion me hod
Da a collec ion me hod/ echnique
Quali ie
Focus G oup In e iew
FGI
In-Dep h In e iew
IDI
Online Su ey
Su ey
Social Simula ion
SocSim
Role Playing Games
RPG
Quali a i e Desk Resea ch
Qual
Quan i a i e Desk Resea ch
Quan
✓ I mul iple iles a e p oduced wi h he use o he same me hod/ echnique in he same case s udy/ ask
(e.g., mul iple in-dep h in e iews), he i s quali ie is appended wi h a unique numbe (e.g., IDI01,
SocSim01),
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✓ The second quan i ie s will indica e he ood sec o . Fo example F&V o ui and ege able, C o
ce eals, M o Mea , E o eggs and F o ish.
✓ The hi d quali ie s deno e he case s udy, and/o he ela ed asks ha p oduce he da ase . This hi d
quali ie is comple ed wi h a hyphen and an indica ion o he loca ion o o igin o he da ase . Fo
example CSx-Y whe e x = case s udy numbe and Y = coun y code. I could also be ela ed o a ask
in he BREADCRUMB p ojec . In which case, TX.Y = T1.1 o example ollowed meaning ask i le.
P oposed da ase names o all da a ypes gene a ed in BREADCRUMB can be ound in Table 1 in deli e able
1.1 Da a p o ocol.
The BREADCRUMB p ojec da a on ology is desc ibed and mapped in D1.1 Da a p o ocol. Whe e e possible,
he da a will include quali ied e e ences
1
o o he da a.
G ouping he da a collec ion me hods and echniques enables us o s anda dize p o enance me ada a ailo ed
o he collec ion app oach.
BREADCRUMB has se e al dedica ed asks and p ocesses o gua an ee he da a quali y: D1.1 Da a p o ocol
and D2.2 Case S udy Plans, deli e able quali y e iew p ocedu e.
2.4 Enhancing da a RE-USE
2.4.1 Licensing
The BREADCRUMB Resea ch da a will be licensed unde he la es e sion o CC BY (a ibu ion equi ed) o
CC0 (public domain), o an equi alen license. Ou s anda d p e e ence is o CC BY 4.0. Howe e , we may
also conside Sha e-Alike and Non-Comme cial Sha e-Alike licenses o speci ic po ions o he da ase s i he
Conso ium decides o make hose pa s public.
✓ Unde he A ibu ion license, use s mus app op ia ely c edi he da ase , p o ide a link o he license,
and indica e any changes made.
✓ The Non-comme cial license p ohibi s comme cial use o he da ase by o he s, while
✓ Sha e Alike license equi es de i a i e wo ks o be licensed unde he same e ms as he o iginal da a.
Me ada a associa ed wi h he da ase will be openly a ailable and licensed unde a public domain dedica ion,
such as C ea i e Commons Public Domain Dedica ion CC0, whene e he da a eposi o y allows o such an
op ion. Rega dless o he le el o p o ec ion applied o he empi ical da a collec ed in he p ojec , p o enance
me ada a in BREADCRUMB Resea ch mus be open unde CC0 o an equi alen license, ensu ing ha
1
A quali ied e e ence is a c oss- e e ence ha explains i s in en . Fo example, X is egula o o Y is a much
mo e quali ied e e ence han X is associa ed wi h Y, o X see also Y. The goal he e o e is o c ea e as
many meaning ul links as possible be ween (me a)da a esou ces o en ich he con ex ual knowledge abou
he da a. (Sou ce: h ps://www.go- ai .o g/ ai -p inciples/i3-me ada a-include-quali ied- e e ences-me ada a/)
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legi ima e in e es s o cons ain s a e sa egua ded. To aid in iden i ying and collec ing ele an me ada a, ools
ailo ed o di e en me hod ypes ha e been p epa ed o p ojec pa ne s (D1.1).
Upon comple ion o he p ojec , all simula ion code wi hin WP 3 will be open-sou ced unde an Apache License
2.0. This license balances being open sou ce while pe mi ing comme cial use s o de elop ex ensions o
isualiza ions wi hou being obliga ed o open sou ce hei addi ions.
2.4.2 Re-use pa hways
Documen a ion needed o he alida ion o da a analysis, and acili a e da a e-use in he p ojec will be
p o ided in he ollowing way:
WP1: The E idence Sea ch Plan/Me hodology (Wo d) o Task 1.3 will p o ide in o ma ion on how and wha
da a was ob ained du ing esea ch and in e iews, and he in e ne o jou nal sou ces o al eady publicly-
a ailable esou ces on ood ma ke ing s anda ds and ood loss and ood was e gene a ion. The subsequen
and emaining ask in WP1 will ely solely on he da a p o ided in T1.3.
UNIBO: me ada a, me hodology epo , codes, ile lis ing lib a ies/packages used o unning he simula ion.
UCPH: Da a will be s o ed in open egis y which de ian ly acili a e da a e-use. O iginal da a will also be made
a ailable o e e ence.
All open da ase s, deli e ables, and scien i ic publica ions will be uploaded o ZENODO. Public deli e ables
will also be accessible on he o icial BREADCRUMB websi e a " h ps://www.b eadc umb-p ojec .eu/ ". These
esou ces will be linked o he OpenAIRE communi y o maximize hei disco e abili y. Uploaded iles will be
app op ia ely agged wi h me ada a acco ding o ZENODO s anda ds, as well as agged wi h he iden i ie
"BREADCRUMB."
The da ase emba go equi es anonymiza ion and ob aining speci ic pa icipan pe mission o sha e po en ially
edac ed ansc ip s. I may con ain pe sonal da a, in which case anonymiza ion o sha ing only agg ega ed
da a would be necessa y. Pe sonal da a, sensi i e da a, o da a pe aining o companies mus be p o ec ed.
The da a will only be made a ailable o ex e nal s akeholde s a e he p ojec , ensu ing ha i does no
comp omise he legi ima e in e es s o he bene icia ies.
An emba go pe iod may be implemen ed i he da a, o ce ain po ions o i , will be u ilized in published a icles
in "G een" open access jou nals. The Eu opean Commission ecommends a maximum emba go pe iod o 6
mon hs in such cases.
2.4.3 Da a quali y assu ance
BREADCRUMB has se e al dedica ed asks o gua an ee he da a quali y. They include:
✓ D1.1 Da a P o ocol,
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✓ D2.2 Case S udy Plans -1 and subsequen upda es
✓ Deli e able Quali y Re iew empla e
✓ Da a Managemen Plans
✓ Da a managemen h ough ins i u ional da a p o ec ion s ewa ds (DPS)
D6.2 – Da a Managemen Plan - 1
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3 DATA OVERVIEW
3.1 Da a gene a ed and i s pu pose
BREADCRUMB s i es o imp o e he unde s anding o how ood ma ke ing s anda ds in luence ood loss and
was e (FLW) gene a ion. This knowledge is c ucial o imp o e he e ec i eness o decision-making and
engagemen o ood chain ac o s, owa ds ze o ood was e. To achie e his aim, he p ojec will pu sue i e
de ailed objec i es (O), and one o e all adminis a i e objec i e.
Objec i e 1:
To es ablish a holis ic iew o he exis ing ood ma ke ing s anda ds in he EU and hei in e ela ions, by
placing special emphasis on he leas documen ed ones, ha is: (i) p i a e s anda ds, and (ii) s anda ds
adop ed a he le el o speci ic MS, and o iden i y he ma ke ing s anda ds which a e mos ele an o FW
gene a ion.
Co esponding WPs: WP1
Main da a sou ces: desk op esea ch supplemen ed by in-dep h in e iews (IDI) will be he main da a collec ion
and e-use me hods. Da a in WP1 will be collec ed o be an in en o y o p i a e and public ma ke ing s anda ds
in EU27.
Objec i e 2:
To c ea e an empi ical e idence base, by using exis ing (O1) and p ojec -gene a ed da a, o p o ide es ima es
o he FW gene a ed due o ma ke ing s anda ds in he supply chains o i e a ge ed ood commodi ies ( ui s
& ege ables, mea , eggs, ce eals, and ish).
Co esponding WP: WP2
Main da a sou ces: desk op esea ch and 16 p ojec case s udies implemen ing su eys, IDI, and ocus g oup
in e iews (FGI). Fu he de ails in D1.1 Da a P o ocol and D2.3 Case S udy Plans - 1.
Objec i e 3:
To unde s and and model: (i) he unde lying mechanisms h ough which, ma ke ing s anda ds lead o FW
gene a ion, and (ii) he ade-o s be ween he objec i e o FW educ ion and o he objec i es pu sued by
ma ke ing s anda ds. This will be s uc u ed o alida e solu ions ( e-balancing) ha alle ia e he nega i e
impac s o ma ke ing s anda ds o FW, while balancing he ade-o s wi h hei o he objec i es.
Co esponding WP: WP3
D6.2 – Da a Managemen Plan - 1
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Main da a sou ces: exis ing knowledge on Mo i a ion, Oppo uni y and Abili y (MOA) app oaches, empi ical
da a collec ion h ough social simula ion
Objec i e 4:
To imp o e ma ke access and business po en ial o oods ha do no mee ma ke ing s anda ds bu a e s ill
sa e o ea (subop imal oods), by: (i) guiding ood businesses in selec ing app op ia e ma ke ing channels and
business models, and assis ing hem in quan i ying hei business alue; (ii) os e ing change in consume s’
and businesses’ a i udes owa ds sub-op imal oods, h ough nudging ma ke ing cues.
Co esponding WP: WP4.
Main da a sou ces: analy ical and epo inpu om WP1 (D1.2: Concep ual F amewo k, D1.3: In en o y o
p i a e and public ma ke ing s anda ds in EU27, and D1.4 FW- ele an ma ke ing s anda ds), WP2 (D2.1 EU
es ima es o FW gene a ed due o ma ke ing s anda ds, D2.3 Case s udy es ima es o FW gene a ed due o
ma ke ing s anda ds, and D2.6 Es ima es o FW gene a ed due o ma ke ing s anda ds, including FW
coe icien s), and WP4 ( D4.1 Typology o subop imal ood alo isa ion op ions).
Objec i e 5:
To e ec i ely manage he upscaling o he p ojec esul s by: (i) de eloping ope a ional guidelines and policy
ecommenda ions on how o p e en / educe FW due o ma ke ing s anda ds, and he eby con ibu ing o
en i onmen al sus ainabili y and ci cula i y o he ood sys em; (ii) o mula ing a Code o Conduc balancing
comme cial and social alue om subop imal oods, and he eby con ibu ing o economic sus ainabili y and
ood po e y educ ion; (iii) de eloping a s a egy o he exploi a ion o key p ojec esul s by he p ojec
pa ne s (indi idually and join ly); (i ) unde aking app op ia e dissemina ion and communica ion ac ions o
maximise he p ojec ’s impac ; ( ) es ablishing o mal ag eemen s (MoUs) wi h ele an p ojec s o achie e
impac syne gies.
Co esponding WP: WP5.
Objec i e 6:
To ensu e
✓ he e ec i e adminis a ion o p ojec ac i i ies acco ding o EU ules, and o sound p ojec
managemen p ac ices;
✓ ha all p ojec ou comes a e deli e ed acco ding o he ag eed ime- and esou ce-planning;
✓ ha all po en ial isks a e iden i ied a an ea ly s age, and app op ia e mi iga ion ac ions a e aken;
✓ a sound e hical ea men o pa icipan s and o mee laws and egula ions ega ding da a
managemen .
D6.2 – Da a Managemen Plan - 1
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Co esponding WP: WP6
3.2 Da a ype and o ma s
BREADCRUMB has a complex and mul idisciplina y na u e equi ing a ious ypes o da a. These da a will
come om se e al sou ces, s o ed in a ious o ma s. The ga he ed da a will be analysed o p ocessed
esul ing in o a se o deli e ables (Table 3) which will be used in communica ion and dissemina ion ac i i ies.
D6.2 – Da a Managemen Plan - 1
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WP4 whe e p ima y da a will also be collec ed om consume s in 27 EU, he D1.1 elabo a es on i s
p o enance.
Seconda y da a will be collec ed om mul iple sou ces, o mul iple asks in di e en WPs including o icial
da abases, su eys, epo s, scien i ic s udies and o he Eu opean p ojec s and o mul iple le els: Eu opean,
na ional, egional and local.
The da a o igin will be explained in each deli e able. The use o exis ing da a o he gene a ion o new da a
will be clea ly iden i ied in each deli e able p oduced. The e hical clea ance o all da a, bo h new and exis ing,
will be add essed by each WP leade and will be clea ly epo ed.
The ga he ed da a will be analysed o p ocessed esul ing in o a se o deli e ables and used in communica ion
and dissemina ion ac i i ies.
All BREADCRUMB da ase s mus ha e a da ase pe sis en Iden i ie (PID), assigned by he indica ed da a
eposi o y.
3.4 Da a u ilisa ion
BREADCRUMB da ase s will be po en ially used by h ee main g oups: he conso ium pa ne s, he scien i ic
communi y and he end-use s. This las g oup is a e y di e se g oup, and conside ing he i e ood sec o s
a ge ed in he p ojec ( ui s and ege ables, ce eals, eggs, mea and ish), hey include: ood p oduce s, ood
businesses, ood p ocessing, e ail, policy make s (EU, Na ional and Regional go e nmen s and local
au ho i ies), educa ional ins i u ions, ci izens/consume s/households/, schools.
A di e en le els, he da a use s du ing he cou se o he p ojec will p ima ily be he 21 conso ium pa ne s,
who ha e speci ied and expec ed da a needs.
All in o ma ion aimed a he scien i ic communi y (p ojec epo s, deli e ables, publica ions) will be cen alised
on he BREADCRUMB p ojec websi e h ps://www.b eadc umb-p ojec .eu/
In addi ion, he esul s and insigh s o ex e nal s akeholde s and o he end use s will be made publicly
a ailable on he p ojec websi e. Gi en he ac ha each conso ium pa ne has a ne wo k, a non-de e mined
numbe o ins i u ions, en e p ises and o ganisa ions in e es ed in Eu opean ood sys em issues especially
ood ma ke ing s anda ds and ood was e gene a ion may also be po en ial use s o he da a gene a ed and
insigh s om he p ojec .
Fu he mo e, he Dissemina ion, Exploi a ion, and Communica ion Plans (D5.1, D5.2 and D5.3) will de ail how
o each hese end-use s.
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Fu he mo e, we will collabo a e wi h he sis e p ojec ROSETTA, o he FLW- ela ed p ojec s such as Ze oW,
CHORIZO, SISTERS, e c. and he JRC o discuss possible join communica ions o simila end-use s. The
esul ing app oach, i necessa y, will be desc ibed in an upda e o he DMP.
3.5 Re-use o da a
Da a e-use will be p esen , pa icula ly in he collec ion and analyses o in o ma ion on exis ing ood ma ke ing
s anda ds (WP1), he collec ion and analyses o ood was e es ima es due o ma ke ing s anda ds (WP2), and
he use o MOA app oaches in he modelling wo k (WP3).
P e ious expe iences and esea ch will se e as da a sou ces and will be collec ed h ough (i) he in ol ed
pa ne s; (ii) a sc eening o exis ing p ojec s and da abases, (iii) collabo a ion wi h JRC, and sis e p ojec
ROSETTA.
The access o sensi i e aw da a collec ed on exis ing ood ma ke ing s anda ds, and on es ima es o ood
was e due o hese ma ke ing s anda ds, in e iews and simila p ima y da a gene a ed wi hin he p ojec , will
be limi ed o he p ojec pa ne s ha wo k di ec ly wi h hese da a. This will be ensu ed by s o ing he sensi i e
aw da a in sepa a e es ic ed access olde s on he MS Teams/Sha ePoin -pla o m.
The non-con iden ial da a gene a ed wi hin he BREADCRUMB p ojec will be a ailable o e-use by he
conso ium pa ne s a e he p ojec ends and will be s o ed on he p ojec Sha ePoin hos ed by EV-ILVO.
The du a ion o kep da a will be discussed in he nex Technical Coo dina ion Boa d (TCB) mee ing. The
publicly a ailable da a will be s o ed on he BREADCRUMB websi e (h ps://www.b eadc umb-p ojec .eu/ ) o
a leas 3 yea s a e he p ojec ends.
D6.2 – Da a Managemen Plan - 1
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3.6 P ac icalizing he FAIR p inciples pe WP
Table 4: Implemen a ion o he FAIR p inciple pe WP
WP
Pa ne
Expec ed size o da a
Desc ip ion
Re e ence
o o he
da a
Re-use o da a
Pu pose o da a
WP1
VLTN
Da a (gene a ed om
desk op esea ch and
>200 in e iews om
ood chain s akeholde s
in EU27 and om he 16
p ojec case s udies) on
exis ing p i a e and
Membe -S a e ood
ma ke ing s anda ds
An e idence sea ch plan and
me hodology has been de eloped
in he amewo k o T1.3 will
p o ide in o ma ion on how and
wha da a was ob ained du ing he
desk op esea ch and in e iews,
and he in e ne o jou nal sou ces.
T1.4 will ely ully on he da a
go en om T1.3
Yes
Collec ion and
analyses o da a
on p i a e and
Membe -S a e
ood ma ke ing
s anda ds
Collec ion and e-use o da a on
exis ing p i a e and Membe -S a e
ood ma ke ing s anda ds o de ine
hypo heses on in T1.4: (i) he links
and he cause-e ec in ensi y (in
quali a i e e ms) be ween speci ic
ood ma ke ing s anda ds and FW;
(ii) he links be ween di e en ood
ma ke ing s anda ds. Based on
hese, a p elimina y iden i ica ion o
FW- ele an ma ke ing s anda ds
will be de eloped
WP2
UCPH
Da a gene a ed om
desk op esea ch and
in e iews on es ima es
o FW as a esul s o
ma ke ing s anda ds in
he 27 EU coun ies. A
minimum o 200
s akeholde s will be
eached.
An aligned e idence sea ch plan
and me hodology as ha o T1.3
will be employed in T2.1 o collec
in o ma ion h ough desk op
esea ch and in-dep h in e iews
on es ima es o FW due o
ma ke ing s anda ds
Yes
Collec ion and
analyses o da a
on FW es ima es
due o ood
ma ke ing
s anda ds
To es ima e FW in 27 EU coun ies
o i e ood sec o s due o
ma ke ing s anda ds
D6.2 – Da a Managemen Plan - 1
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ILVO
16 case s udies, sample
sizes a e de ailed wi hin
he D1.1 Da a P o ocol
and D2.2 Case
S udy plans -1
No
The s o age o
esul s o
e idence-based
analyses o
exis ing ood
ma ke ing
s anda ds and
hei po en ial o
gene a e FW
(es ima es)
Collec ion o da a on 16 case
s udies ( u he de ails in D1.1 Da a
P o ocol and D2.2 Case
S udy Plans - 1)
WP3
UNIBO
Modelling, ole playing
games and social
simula ion: possible o
speci y in M24
Me ada a, me hodology epo ,
codes, ile lis ing
lib a ies/packages used o
unning he simula ion
No
The use o MOA
app oaches in he
modelling wo k
Exis ing knowledge MOA
app oaches, empi ical da a
collec ion h ough social simula ion
WP4
MC
Quali a i e da a
gene a ed h ough
in e iews o
s akeholde s (numbe o
be de e mined in M15)
Desk op quali a i e esea ch da a
on he ypology o subop imal
oods. One speci ic ood p oduc
om each o he a ge ed ood
commodi ies will be selec ed
based on: (i) he high in luence o
ma ke ing s anda ds (based on
he esul s o T1.4), and (ii) he
ood p oduc ’s s ong po en ial
business
Yes
Analy ics in WP1, WP2, WP3 will
eed o guide he da a o be
collec ed and analysed
AINIA
Quali a i e and
Quan i a i e da a
gene a ed om
Su ey on consume accep ance
o subop imal oods gene a ed
Yes
Analy ics in WP1, WP2, WP3 will
eed o guide he da a o be
collec ed and analysed
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app oxima ely 500
consume s in 27 EU
coun ies h ough online
su ey.
h ough online su ey which ill-
a ge 500 consume s
WP5
PNO
Rela i ely in small size
Some Excel iles, Wo d iles,
empla es, logos which a e
in e nally sha ed wi hin he
conso ium. Public in o ma ion is
s o ed on he websi e and in he
newsle e s.
N/A
Ga he da a ela ing o business
and upscaling s a egies o
exploi ing p ojec esul s ha a e
inno a i e. Also, o p o ide
empla es o he pa ne s in he
conso ium o p o essionalize he
wo king me hods e.g. empla es o
deli e ables, p esen a ions, …
Some documen s also ha e he
pu pose o collec in o om he
pa ne s o example,
dissemina ion, exploi a ion and
communica ion.
WP6
EV-ILVO
Rela i ely in small size
Some Excel iles, Wo d iles,
empla es, which a e in e nally
sha ed wi hin he conso ium.
No
N/A
The documen s will only be used o
in e nal p ojec managemen o
example con ac lis , mee ing
minu es, … and o communica ion
wi h ex e nal s akeholde s.
D6.2 – Da a Managemen Plan - 1
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4 ALLOCATION OF RESOURCES
4.1 Wha will he cos s be o making da a and o he esea ch ou pu s FAIR in you p ojec ?
Cos s o da a s o age is o be kep a a minimum in BREADCRUMB using ee se ices and ools, like
ZENODO and p ojec MS Teams si e. S ill, some cos s may s ill incu . The cu en o eseen cos s o making
da a FAIR includes:
✓ Fees associa ed wi h he publica ion o scien i ic a icles con aining p ojec ’s esea ch da a in
“Gold” Open access jou nals. The cos sha ing, in case o mul iple au ho s, shall be decided
among he au ho s on a case-by-case basis.
✓ P ojec websi e de elopmen and ope a ion: budge o PNO. The equi emen is o main ain he
websi e 6 mon hs a e he comple ion o he p ojec .
✓ Da a a chi ing a ZENODO and on o he online da a base: ee o cha ge.
✓ Copy igh licensing wi h C ea i e Commons: ee o cha ge.
Cos s ela ed o open access o esea ch da a in Ho izon 2020 a e eligible o eimbu semen unde he
condi ions de ined in he BREADCRUMB G an Ag eemen , in pa icula A icle 6 (“Eligible Cos ”) and A icle
6.2. (“D.2 Cos s o o he goods and se ices”), bu also o he a icles ele an o he cos ca ego y chosen.
P ojec bene icia ies will be esponsible o applying o eimbu semen o cos s ela ed o making da a
accessible o o he s beyond he BREADCRUMB Conso ium. To be eligible, cos s mus be:
a) pu chased speci ically o he ac ion and in acco dance wi h A icle 10.1.1 (bes alue o money)
o ,
b) con ibu ed in-kind agains paymen and in acco dance wi h A icle 11.1 ( ules o in-kind con ibu ions
o agains paymen ).
4.2 How will hese cos s be co e ed?
O he cos s may incu du ing he p ojec ’s li e ime and will be e alua ed as eligible o no as speci ied in he
G an Ag eemen . Each pa ne is esponsible o he da a hey p oduce. Any ee incu ed o Open Access
h ough scien i ic publica ion o he da a will be he esponsibili y o he da a owne (au ho s) pa ne (s).
4.3 Who will be esponsible o da a managemen in you p ojec ?
Da a manage o BREADCRUMB is EV-ILVO. Capwell Echo Fo bang is he DPS o EV-ILVO.
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4.4 How will long- e m p ese a ion be ensu ed?
The de aul long- e m p ese a ion will be h ough ZENODO. ZENODO s a es ha : "I ems will be e ained o
he li e ime o he eposi o y. This is cu en ly he li e ime o he hos labo a o y CERN, which cu en ly has an
expe imen al p og amme de ined o he nex 20 yea s a leas ." Since uploading o ZENODO is ee o cha ge
his is expec ed o keep o e all e en ion cos s small.
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5 DATA SECURITY
5.1 Wha p o isions a e o will be in place o da a secu i y?
Raw da a will no be sha ed because i is subjec o p i acy laws. Pseudonymised da a will be sha ed wi h all
membe s o BREADCRUMB u ilizing secu i y measu es bu will no be made public. Howe e , in acco dance
wi h he HE policy da a will be made a ailable when anonymisa ion is possible. Anonymisa ion in ol es
echniques ha can be used o con e pe sonal in o ma ion in o anonymised da a; da a oid o pe sonally
iden i iable de ails. . See Annex 7.2 o guidelines on anonymising and pseudonymising da a.
A he le el o he BREADCRUMB p ojec pa ne s:
The BREADCRUMB p ojec uses MS Teams, an online collabo a ion pla o m. On his pla o m, a dedica ed
p ojec si e has been es ablished, accessible only by he pa ne ep esen a i es in he Conso ium.
Fu he mo e, he coo dina o is hinking o c ea ing a olde o collec and s o e da ase s, allowing o s ic e
access con ol han he main p ojec si e, when needed.
The ollowing secu i y se ings on he BREADCRUMB MS Teams ha e been es ablished:
✓ Access le el: Res ic ed o p ojec membe s only. Fu he access es ic ions on speci ic olde s a e
enabled.
✓ Enc yp ion wi h SSL/TLS p o ec s da a ans e be ween pa ne s and he MS Teams si e.
✓ Th ea managemen , secu i y moni o ing, and ile-/da a in eg i y p e en s and/o egis e s possible
manipula ion o da a.
A e conduc ing he in e iew, pe sonal da a should be anonymised as soon as possible (e.g. anonymised
w i en epo whe e he e is no longe any link o he pa icipan )/pseudonymised (e.g. ansc ip ion o in e iew
whe e di ec ly iden i iable elemen s ha e been eplaced by a code). See Annex 7.2 o guidelines on
anonymising and pseudonymising da a.
When s o ing/p ocessing da a, iden i ica ion and analysis da a should be s o ed sepa a ely wi h a common
code. In his way, access o he iden i ica ion da a can be s ic ly limi ed and moni o ed. Only he pe son, who
has he key o he code, can e ie e he pe son behind he code numbe . The key is kep on p o ec ed and
backed-up ne wo k d i es o ins i u ions hemsel es in olde s o which only he ele an esea che s o he
BREADCRUMB p ojec ha e access. See Annex 7.2 o guidelines on anonymising and pseudonymising da a.
The analyses a e conduc ed only based on pseudonymised da a. The pseudonymised da a a e s o ed on
p o ec ed and backed-up ne wo k d i es o he ins i u ions hemsel es and in enc yp ed olde s on
BREADCRUMB MS Teams (whe e i should be checked whe he e e yone needs access o pseudonymised
da a). See Annex 7.2 o guidelines on anonymising and pseudonymising da a.
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Ou side he BREADCRUMB p ojec :
I necessa y, da a ans e o and om end-use s (including ans e o sensi i e da a i allowed) is pe o med
enc yp ed, ei he sen by enc yp ed ZIP o RAR iles, o by download di ec ly as web-based se ices om
se e s. In any case s ong passwo d is equi ed o accessing ans e ed da ase s and passwo ds mus be
sen sepa a ely om he da ase (p e e ably using also di e en channels o communica ion e.g. Wha sApp).
5.2 Will he da a be sa ely s o ed in us ed eposi o ies o long e m p ese a ion and cu a ion?
The de aul long e m p ese a ion will be h ough ZENODO. ZENODO s a es ha : "I ems will be e ained o
he li e ime o he eposi o y. This is cu en ly he li e ime o he hos labo a o y CERN, which cu en ly has an
expe imen al p og amme de ined o he nex 20 yea s a leas ." Since uploading o ZENODO is ee o cha ge
his is expec ed o keep o e all e en ion cos s small.
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6 ETHICS
6.1 A e he e, o could he e be, any e hics o legal issues ha can ha e an impac on da a sha ing?
The p oposed wo k in BREADCRUMB will ully comply wi h he egula ions se ou in A icle 14 o he G an
Ag eemen , which s a es ha all ac i i ies mus be ca ied ou in compliance wi h:
✓ E hical p inciples (including he highes s anda ds o esea ch in eg i y, e.g. he p inciples o he
Eu opean Cha e o Resea che s and The Eu opean Code o Conduc o Resea ch In eg i y), and
✓ Applicable in e na ional, EU, and na ional laws (in pa icula he GDPR).
To ensu e his, BREADCRUMB wo ks wi h he Commission o E hics in Social Science and Humani ies
(ComESSH) a ILVO who’s p esiden P o . Fleu Ma chand will ac as E hics Men o o he BREADCRUMB
p ojec . ComESSH will ad ise he p ojec on a egula basis h oughou he p ojec , and p o ide e hical
app o al and clea ance on da a collec ion p o ocols (see annex 7.4). The speci ic issues ha he commission
will p o ide ad ice on a e lis ed below.
Humans:
The p ojec will implemen quali a i e and quan i a i e s udies by in ol ing he s akeholde s in in e iews,
su eys, case s udies and expe imen s. BREADCRUMB has he help o ComESSH. ComESSH ca ies ou
he e hical e alua ion o esea ch in he domain o 'social esea ch' ha is, "Resea ch wi h human pa icipan s
no co e ed by he Expe imen s Ac o May 7, 2004". The e hics ad iso (Fleu Ma chand) will ad ise use on
he p ocedu es and c i e ia ha will be used o iden i y/ ec ui esea ch pa icipan s, bu also he speci ic a ge
g oups.
Pe sonal Da a:
Unde s anding people's beha iou is key o BREADCRUMB. While he p ojec aims o be e unde s and he
ela ionship be ween ood was e and ma ke ing s anda ds, and iden i y solu ions o alle ia e he nega i e
impac s on ood was e, he o he key objec i e is o imp o e ma ke access o enhance he business po en ial
o ood ha is sa e o ea , bu does no mee speci ic ma ke ing s anda ds. In his espec , in o ma ion abou
consume s’ a i udes – in pa icula as ega ds sub-op imal ood - is pa amoun . Unde s anding he expanse
o consume p e e ences o ce ain oods canno be ully accomplished unless an in eg a ed gende
pe spec i e as well as in e sec ional analysis is inco po a ed in o he p ojec . BREADCRUMB in eg a es bo h
h oughou i s wo k, keeping in mind ha gende and in e sec ional di e ences can a ec he design o and
esponse o ma ke ing s anda ds, a ec ing indi idual ood choices, usage, and was e. Speci ically, he p ojec
will:
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Wi h anonymisa ion, you p ocess you aw da a un il all op ions o ( e)iden i ica ion a e i e e sibly emo ed.
The e is no longe any link o he da a subjec . The da a subjec can no longe be ( e)iden i ied.
This is why bo h di ec iden i ie s and indi ec iden i ie s mus be emo ed o eplaced.
• Di ec iden i ie s: da a ha allow you o di ec ly iden i y he da a subjec . Fo example: name, add ess,
elephone numbe , e-mail add ess, IP add ess, ecognisable image o a da a subjec , oice o a da a
subjec , e c.
• Indi ec iden i ie s: based on a combina ion o da a i is possible o ( e)iden i y he da a subjec . Fo
example: he combina ion o a m ype, municipali y business sea and age.
The GDPR legisla ion no longe applies.
Fo example: anonymised w i en epo o ocus g oup discussion.
Wi h pseudonymisa ion, you p ocess you aw da a un il you can no longe link he pseudonymised da a (=
analysis da a) o he da a subjec wi hou using he da a subjec 's addi ional da a.
You s o e he link be ween he iden i y o he da a subjec and he pseudonym (= iden i ying da a) in a sepa a e
ile: he key ile. Access o he key ile is highly es ic ed and only accessible o a limi ed numbe o people.
Analyses a e done only on he basis o he pseudonymised da a.
The GDPR legisla ion does s ill apply because he pseudonymised da a is linkable o he da a subjec on he
basis o he key ile.
Example: ansc ip ion o in e iew whe e di ec ly iden i iable elemen s ha e been eplaced by a pseudonym
(=code). Lis o in e iewees' names and codes used in he pseudonymised ansc ip a e kep in highly
es ic ed key ile.
7.2.3 S o age o he da a
1 P ocess he ob ained pe sonal da a on p o ec ed and backed-up ne wo k disks o he pa ne
o ganisa ions hemsel es (c . e.g. L-disk o ILVO-T&V115), in olde s o which only he esea che s
in ol ed in he BREADCRUMB p ojec ha e access.
2 A e conduc ing he in e iew, pe sonal da a should be anonymised as soon as possible (e.g.
anonymised w i en epo whe e he e is no longe any link o he pa icipan )/pseudonymised (e.g.
ansc ip ion o in e iew whe e di ec ly iden i iable elemen s ha e been eplaced by a code)
3 When s o ing/p ocessing da a, iden i ica ion and analysis da a should be s o ed sepa a ely wi h a
common code. In his way, access o he iden i ica ion da a can be s ic ly limi ed and moni o ed. Only he
pe son, who has he key o he code, can e ie e he pe son behind he code numbe . The key is kep
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on p o ec ed and backed-up ne wo k d i es o ins i u ions hemsel es in olde s o which only he
ele an esea che s o he BREADCRUMB p ojec ha e access.
4 The analyses a e conduc ed only on he basis o pseudonymised da a. The pseudonymised da a a e
s o ed on p o ec ed and backed-up ne wo k d i es o he ins i u ions hemsel es and in enc yp ed
olde s on BREADCRUMB MS TEAMS (whe e i should be checked whe he e e yone needs access o
pseudonymised da a).
7.2.4 When o anonymise o pseudonymise?
When anonymisa ion is no possible o no desi able in unc ion o you in ended pu pose o you scien i ic
esea ch, pseudonymisa ion is b ough o wa d om he GDPR o p o ec you pe sonal da a.
Fo example: in he con ex o ollow-up esea ch, you wan o be able o ask ques ions o he in e iewee la e
on.
Some imes, in he con ex o esea ch, i is impo an ha you do no anonymise o pseudonymise he
eco ding. Fo example: conside a p ac ice ideo o a ideo es imonial o p omo e and dissemina e bes
a ming p ac ices and inno a ions.
In each case, howe e , i is impo an ha you in o m he da a subjec s abou his in he in o med consen and
ha he da a subjec s ha e gi en hei explici consen o his.
7.2.5 How o anonymise o pseudonymise?
Da ase wi h only di ec iden i ie s
Anonymise (See Table 2 o annex sec ion)
• S ip da a o di ec iden i ie s (name, add ess, phone numbe , email add ess, e c). (See Table
5)
o Di ec iden i ie s a e emo ed (e.g. omi columns in Excel).
o
o Di ec iden i ie s a e masked: comple ely o pa ially o e w i e wi h (*/x)
o
o A andom code is gi en o each da a subjec . E.g. Fa me 51, Fa me 07, Fa me 04, ...
o
• Agg ega e da a (e.g. a e age, sum, ...). Ne e igu es om less han 5 a ms. (See Table 6)
• Raw da ase o be dele ed.
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Pseudonymisa ion (See Table 2 o annex sec ion)
• Di ec iden i ie s (name, add ess, phone numbe , email add ess, ...) om aw da ase a e eplaced
by a pseudonym using:
o Sequen ial coun e : a sequen ial numbe (and possibly a p e ix) is used as a
pseudonym. E.g. a me 01, a me 02, a me 03, ... (See Table 4)
o
o Random Numbe Gene a o : a andom numbe (and possibly a p e ix) is used as a
pseudonym.
• C ea e sepa a e key ile con aining a link be ween analysis da a and pe sonal da a based on
pseudonym. (See Table 3 o annex sec ion)
• The aw da ase is p e e ably dele ed (o has se e ely es ic ed access). The esea che
p e e ably pe o ms analyses on he pseudonymised da a (= analysis da a). The analysis da a a e
es ic ed o au ho ised esea che s who need he da a o conduc he s udy o which he da a
we e ob ained. The key ile has highly es ic ed access (= iden i ying da a).
• A he end o he s udy - e.g. i pseudonymised da a should no be kep as pa o ollow-up
esea ch - i is easy o anonymise he pseudonymised da a. Change he pseudonym by a andom
code and pe manen ly dele e he aw da ase - i no al eady done - and he key ile. (See Table
5)
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Table 1: Raw da a
Names a me s
Email add ess
Housing ype Eas e n
bunnies
A e age numbe o
Eas e eggs pe Eas e
bunny pe yea
Noah Pee e s
n.pee e s@ elehoo.com
En iched cage
461
A hu Janssens
ajanssen[email p o ec ed]m
Ou doo sys em
409
Louis Maes
[email protected]
Ou doo sys em
380
Oli ia Jacobs
[email protected]
V ije ui loop
355
Emma Willems
emmaW@g ele.com
V ije ui loop
340
Louise Dubois
Ldubois@ elemail.com
En iched cage
392
…
…
…
Table 2: Key ile (= iden i ica ion de ails)
Pseudonym
Names a me s
Email add ess
Fa me 01
Noah Pee e s
n.pee e s@ elehoo.com
Fa me 02
A hu Janssens
ajanssen[email p o ec ed]m
Fa me 03
Louis Maes
[email protected]
Fa me 04
Oli ia Jacobs
[email protected]
Fa me 05
Emma Willems
emmaW@g ele.com
Fa me 06
Louise Dubois
Ldubois@ elemail.com
…
…
…
Table 3: Pseudonymised da a (=analysis da a). Based on pseudonym and key ile, he a me can be e-iden i ied
Pseudonym
Housing ype Eas e n bunnies
A e age numbe o Eas e
eggs pe Eas e bunny pe
yea
Fa me 01
En iched cage
461
Fa me 02
Ou doo sys em
409
Fa me 03
Ou doo sys em
380
Fa me 04
O ganic sys em
355
Fa me 05
O ganic sys em
340
Fa me 06
En iched cage
392
…
…
Random code
Housing ype Eas e n bunnies
A e age numbe o Eas e
eggs pe Eas e bunny pe
yea
Fa me 51
En iched cage
461
Fa me 07
Ou doo sys em
409
Fa me 04
Ou doo sys em
380
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Da ase wi h di ec and indi ec iden i ie s
Anonymise
Remo ing iden i ie s om da a
o Iden i ie s a e emo ed (e.g. omi columns in Excel).
o
o Iden i ie s a e masked: o e w i e ully o pa ially wi h '*' o 'X'.
o
o A andom code is gi en o each pe son in ol ed. (E.g. Fa me 51, Fa me 07, Fa me 04,
...)
O
• Gene alising da a: he e, he da a become less p ecise, speci ic o he in ended pu pose o
scien i ic esea ch. I he e is oo much loss o in o ma ion in unc ion o in ended pu pose, hen
anonymising is no he app op ia e secu i y measu e and you should pseudonymise he da ase .
Fo example:
o Replacing a yea o bi h wi h an age o age ange
o Replace a loca ion (e.g. municipali y business sea ) wi h a less p ecise loca ion (e.g.
p o ince, ag icul u al egion, ... business sea )
o Replacing a speci ic a m ype (e.g. specialised g eenhouse ege able a ms) wi h a less
speci ic a m ype (e.g. specialised ho icul u al a m)
O
• Se ing uppe and lowe limi s: g oup alues o da a abo e o below ce ain limi s o a oid ha
da a subjec s can be iden i ied based on ou lie s. Fo example
o Age ange: '65 yea s and abo e' and he age ange: 'less han 35 yea s’
o Class o business size o '<25,000 eu os' and business size o '>=500,000 eu os’
O
• Da a pe u ba ion: ounding, adding noise, eplacing eal alues wi h simula ion alues o g oup
a e ages ounding nume ic alues and da es. The deg ee o alue change de e mines
anonymisa ion. When da a accu acy is essen ial, da a pe u ba ion should no be applied.
O
• Agg ega e da a (a e age, sum, ...). Ne e igu es om less han 5 companies.
The aw da ase a e emo ed.
To e i y ha quali a i e da a has been p ope ly anonymised, you can e.g. ead he anonymous epo om
he da a subjec 's poin o iew o ha e he anonymous epo ead by he da a subjec . I he e a e no mo e
links o he da a subjec , he GDPR no longe applies.
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Pseudonymisa ion
• Di ec iden i ie s (name, add ess, phone numbe , email add ess, ...) om aw da ase a e
eplaced by a pseudonym.
• C ea e a sepa a e key ile con aining a link be ween analysis da a and pe sonal da a based on he
pseudonym.
• As a unc ion o in ended pu pose o scien i ic esea ch
o Sepa a e indi ec iden i ie s om analysis da a and add o he key ile o
o Do no sepa a e indi ec iden i ie s om analysis da a because hey a e o
necessa y impo ance o he analysis o he da ase and in conside a ion o he
in ended pu pose:
▪ Gene alise: in his p ocess, he da a become less p ecise, speci ic. (Possibly
no desi ed in he con ex o esea ch.) Fo example:
✓ Replacing a da e o bi h wi h an age o age ange
✓ Replacing an add ess o place o business wi h a less speci ic
loca ion: e.g. municipali y o p o ince o ag icul u al egion, ... in
which he place o business is loca ed
✓ Replacing a speci ic a m ype (e.g. specialised g eenhouse
ege able a ms) wi h a less speci ic a m ype (e.g. specialised
ho icul u al a m)
O
▪ Se ing uppe and lowe limi s: g oup alues o da a abo e o below ce ain
limi s o a oid ha da a subjec s can be iden i ied based on ou lie s. (May no
be desi able in he con ex o esea ch.) Fo example:
✓ Age class: '65 yea s and abo e' and he age class: 'less han 35
yea s’
✓ Class business size o '<25,000 eu os' and business size o
'>=500,000 eu os’
▪ Da a pe u ba ion: ounding, adding noise, eplacing eal alues wi h
simula ion alues o g oup a e aging ounding nume ic alues and da es.
When da a accu acy is essen ial, pe u ba ion should no be applied.
• When pseudonymising/anonymising ansc ip s, he abo e echniques can also be used.
Subs i u ions can be indica ed wi h squa e b acke s e.g. [Fa me 01] has a specialised Eas e
bunny a m in [Limbu g] and says ha keeping Eas e bunnies in ee ange is be e o animal
wel a e. [Fa me 02] has a specialised Eas e bunny a m in [Wes Flande s] and says ha keeping
Eas e bunnies in en iched cage is less labou in ensi e.
• The aw da ase is p e e ably dele ed (o has se e ely es ic ed access). The esea che
p e e ably pe o ms analyses on he pseudonymised da a (= analysis da a). The analysis da a a e
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es ic ed o au ho ised esea che s who need he da a o conduc he s udy o which he da a
we e ob ained. The key ile has highly es ic ed access (= iden i ying da a).
• A he end o he s udy - e.g. i pseudonymised da a should no be kep in he con ex o ollow-up
esea ch - you can conside - i possible/i desi able - anonymising he pseudonymised da a. F om
he poin o iew o he da a subjec , conside whe he he da a subjec is e-iden i iable om he
pseudonymised da a.
o I e-iden i iable, he da ase is no su icien ly pseudonymised. GDPR legisla ion
con inues o apply. Da a mus be dele ed a he end o he s udy, unless he da a
subjec has gi en pe mission o he pe sonal da a o be e ained o possible ollow-
up esea ch.
o I no e-iden i iable, hen he da ase is su icien ly pseudonymised. Change he
pseudonym by a andom code. Pe manen ly dele e he aw da ase - i no al eady
done - and he key ile. The GDPR legisla ion no longe applies o anonymous da a.
The anonymised da a may be e ained o ollow-up esea ch bu can no longe be
linked o speci ic indi iduals/ i ms. Longi udinal esea ch a company le el is he e o e
no possible wi h anonymised da a.
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7.3 Annex 3: Templa e in o ma ion shee and in o med consen
INFORMATION SHEET
Dea pa icipan ,
You a e in i ed o olun a ily pa icipa e in BREADCRUMB’s esea ch ac i i y, "Ti le o S udy”. Be o e you
ag ee o pa icipa e in his s udy, i is impo an ha you ead his in o ma ion o m ca e ully. I any hing is no
clea , please do no hesi a e o ask ques ions, con ac in o ma ion can be ound a he bo om o his documen .
Pu pose o he p ojec
BREADCRUMB aims o p o ide an empi ical e idence-based unde s anding and pu pose o ood ma ke ing
s anda ds, along wi h hei in luence on he gene a ion o ood was e (FW). I s goal is o sugges in e en ions
ha s ike a balance be ween he aim o FW educ ion and o he s anda ds- ela ed objec i es, while assis ing
ood chain pa icipan s in maximizing he comme cial iabili y o less- han-op imal ood p oduc s.
To achie e hese goals, he p ojec will add ess 16 case s udies in i e di e en ood commodi ies ( ui &
ege able, mea , eggs, ce eals, and ish).
P ocess desc ip ion: Wha happens nex ?
B ie ly desc ibe he esea ch ac i i y (e.g., su ey, in e iew, obse a ion, e c.), and he pu poses o da a
collec ion and da a p ocessing. Use he example below, as pe case o ac i i y, and adjus he ex acco dingly.
Ou pu pose wi h he [name he ac i i y, i.e., su ey, in e iew, obse a ion] is o gain mo e de ailed in o ma ion
and deepe insigh in o [include he e he objec i es o he ac i i y]
Fo his pu pose, he ollowing pe sonal da a will be collec ed: [e.g., gende , age, email, loca ion da a, e c.]
Wha does pa icipa ion in ol e o you?
Desc ibe he me hods (online/pape -based su ey, in e iew, obse a ion, e c.), wha ype o in o ma ion will
be collec ed and how he in o ma ion will be eco ded (elec onically, on pape , sound/ ideo eco ding), also
including he expec ed du a ion o he ac i i y. Use he example below, as pe case o ac i i y, and adjus he
ex acco dingly.
I you chose o ake pa in he esea ch ac i i y, his will in ol e ha you [ ill in an online su ey, answe o
some ques ions o an in e iew, e c.]. You pa icipa ion is expec ed o las app oxima ely [add he e he
Templa e: In o ma ion Shee o BREADCRUMB
This is a empla e o in o med consen when collec ing and p ocessing pe sonal
da a in BREADCRUMB. I can be used o su eys, obse a ion, in e iews, sound
eco ding, e c. When you p o ide you own ex , please, use clea and simple
language, headings, and bulle poin s, ac i e (no passi e) language, and a oid
o eign wo ds.
Please change all ex ma ke in yellow.
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du a ion - XX hou s/minu es]. The [su ey, in e iew, e c.] includes ques ions abou [desc ibe he mos
impo an ques ions/ opics]. You answe s will be eco ded [elec onically, using pen and pape , sound
eco ding, e c.].
Fo he case o in e iews, please also add he ollowing ex as is: In case ansla ion be ween di e en
languages is needed, he in e iew may las a li le longe . I you pe mi , he in e iew will be eco ded. I you
a e no com o able wi h sound eco ding, de ailed no es will be aken.”
You pa icipa ion in his s udy is olun a y, and you ha e he igh o wi hd aw a any ime wi hou penal y. I
in ol es pa icipa ing in in-dep h in e iews, su eys, and ocus g oup in e iews o ga he insigh s and
pe spec i es ela ed o ood ma ke ing s anda ds and ood was e p e en ion in a ious sec o s F ui &
ege able, mea , eggs, ce eals, and ish.
Po en ial bene i s o isks o pa icipa ion
You in ol emen con ibu es o ad ancing scien i ic unde s anding, de eloping e idence-based solu ions o
comba ood was e, and bene i ing socie y. The e a e no di ec bene i s om you pa icipa ion and he e a e
no o eseeable isks in he pa icipa ion.
Pa icipa ion is olun a y
You pa icipa ion is comple ely olun a y, and he e will be no nega i e consequences o declining o
pa icipa e o wi hd awing om he s udy a any ime. You ha e he igh o e use o answe any ques ions
you a e uncom o able wi h o o skip any sec ions. I you chose o pa icipa e, you can wi hd aw you consen
a any ime wi hou gi ing a eason. The e will be no nega i e consequences o you i you chose no o
pa icipa e o la e decide o wi hd aw. A e wi hd awal you da a will be dele ed.
Con iden iali y
You iden i y and esponses will emain con iden ial. Only he esea che and au ho ized pe sonnel will ha e
access o he da a collec ed du ing he s udy. You pe sonal in o ma ion will be s o ed secu ely and will no be
disclosed o anyone ou side o he esea ch eam wi hou you explici consen .
The p ojec will end in Decembe 2026. All p ojec da a will be s o ed only o he minimum pe iod equi ed o
comple e he esea ch ac i i ies, which is XX mon hs/yea s, and acco ding o he accoun ing ules ha apply
unde Ho izon 2020, no longe han i e yea s om he end o he p ojec , when i will be dele ed.
Con ac in o ma ion
I you ha e ques ions o conce ns abou he p ojec BREADCRUMB, o wan o exe cise you igh s, con ac
ou Da a P o ec ion O ice : [inse name o he da a p o ec ion o ice a he ins i u ion esponsible o he da a
collec ion]
Kind ega ds,
Responsible o da a collec ion (DPO)
[Signa u e]
CONSENT FORM
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Selec ing “I Ag ee” below indica es ha :
- You ha e ecei ed and ead he in o ma ion in he BREADCRUMB In o ma ion shee ;
- You unde s and he p ocedu es desc ibed abo e and he expec ed du a ion o he s o age o he
da a;
- You ha e been gi en he oppo uni y o ask ques ions;
- You olun a ily ag ee o pa icipa e, and you a e ee o wi hd aw a any ime wi hou gi ing a
eason and wi hou consequences;
- You unde s and ha you pe sonal in o ma ion will be ea ed and handled in acco dance wi h he
p o isions o he EU Gene al Da a P o ec ion Regula ion (Reg. 2016/679);
- You a e a leas 18 yea s o age.
o I Ag ee
Pa icipan 's Signa u e: _________________________ Da e: _______________
Resea che 's Signa u e: _________________________ Da e: _______________
