1. Building a Blockchain-based Reputation
Infrastructure for Open Research. Case study:
the EERIS Network
Victor HOLOTESCU, PhD Student,
Andrei TERNAUCIUC, PhD
Radu VASIU, PhD
Politehnica University of Timișoara, Romania
ICCMAE 2022: The 2nd International Conference on Computational Methods and Applications in Engineering
May 7-8, 2021
Carmen HOLOTESCU, PhD
”Ioan Slavici” University of Timișoara, Romania
Cosmin CIORANU, PhD
UEFISCDI, Bucharest, Romania

2. 1. EERIS Network description. Scope of the project
2. Reputation and Open Research
3. Blockchain-based Reputation Infrastructure for Open Research: design and
implementation
4. Piloting
5. Performance analysis
6. Modelling the Reputation factor
7. Conclusions and Future Work
References
Content

3. Scope: Development of a Reputation
Mechanism for Research Infrastructures,
integrated with EERIS
Project “Increasing the capacity of the
RDI system to respond to global
challenges. Strengthening the
anticipatory capacity for evidence-based
public policy making - SIPOCA 592”,
UEFISCDI.
EERIS.eu: Engage in the European Research
Infrastructures System
- developed and hosted by the Executive Agency for
Higher Education, Research, Development and
Innovation Funding (UEFISCDI)
- a booking gate where specialists and companies can
engage with public and private European research
infrastructures in order to carry out research, by
interacting with services, equipment and experts.
1. EERIS Network description. Scope of the
project

4. Reputation is the recognition by other
people/entities of some characteristic
or ability (Merriam-Webster
dictionary);
Few attributes are more important to
identity and trust than reputation
(Arun and Carmichael, 2017);
Reputation could be seen as a global
perception of an entity's behavior
based on the trust established by the
other entities in a system.
In order to guarantee an objective measurement of
reputation, a reputation management system has to be
designed:
- a possible approach is to establish a central authority to act
as the agent of trust, but such a solution does not eradicate
the root cause of mistrust
- another approach: a distributed reputation system based on
Blockchain; to measure an individual’s or an institution’s
propensity to do what they promise, data tracked for past
performance on a Blockchain could be used, while access to
the data on a Blockchain becomes a new verifiable basis for
reputation, which can visibly demonstrate trustworthiness to
their potential clients and partners.
2.1. Reputation
The Blockchain is a type of Distributed Ledger Technology (DLT), an append-only chain-like data
structure, made out of signed and timestamped blocks that contain the transactions (Holotescu
and Vasiu, 2020).

5. 2.2. Open Research
Our approach follows the principles of Open Research/Science recently defined by UNESCO
Recommendations on Open Science, European Union's Open Science policy, and Open Science
Knowledge Hub Romania.
UNESCO Recommendations on Open Science, published in November 2021:
“Open science increases scientific collaborations and sharing of information for the benefits of
science and society; also opens the processes of scientific knowledge creation, evaluation and
communication to societal actors beyond the traditional scientific community.”
Blockchain and Open Data share similar principles such as the promotion of transparency,
equality in information knowledge and access, as well as the reorganisation of data exchange
between a number of parties (data.europa.eu, 2018).
The decentralization brought by Blockchain enables researchers to build their own open
ecosystem for research data, metadata, and communication that follows the philosophy of
open research, thus everyone can openly participate, collaborate, and contribute to science.
The results of these activities, such as research data, processes, studies, and methods, are
freely available so that they can be reused and reproduced (Leible et al., 2019).

6. The implemented reputation mechanism aims to increase openness, impact, and technology
transfer of research infrastructures (RIs) and is designed not only to measure reputation, but also
to make it more visible and, above all, to provide an ecosystem for its growth.
The reputation mechanism designed and implemented consists of a Blockchain (Hyperledger
Fabric) infrastructure for EERIS - EERIS Blockchain Infrastructure (EBI), which communicates with
the platform through an API (Application Programming Interface).
The reputation factor will result by weighting the dynamics of the RI data stored on the
Blockchain, over time.
3. Blockchain-based Reputation Infrastructure
for Open Research: design and implementation

7. Proposed solution
The aim of the project is to create a reputation system which can be integrated with the
current EERIS platform without the need to redesign or revamp the whole platform, thus a
set of APIs which can be integrated with the current platform was proposed in 2 steps:
1. Integrate existing functionality on the platform with the designed Blockchain system to
build dynamism through the traceability of the activities of each RI based on which the
reputation is build.
2. Integrate certifications of data contributed through collaborations of the RIs and
multiparty contracts.
The storage of data (1) / interaction (2, 3, 4) of the research infrastructures (RI) on
Blockchain ensures:
1. immutability, transparency, traceability and audit of
data / collaborations stored for each RI at certain
periods of time or when changes appear for the
number of experts, equipment, services, and visits;
thus, the dynamics of each RI are retained
2. registration and dynamics of contracts for
technology transfer with other RIs and third parties
3. openness of research by publishing open data sets
for reuse in other projects by other RIs, entities
4. copyright protection / certification / licensing /
notarization – by storing certificates for articles,
data, projects, open educational resources, training,
internships, milestones, etc.

8. EERIS Blockchain Infrastructure (EBI)
- The PoC network consist of 2
organizations, each having their
own Certificate Authorities,
Peers, Orderers;
- The network runs a RAFT
ordering service and a channel
containing 2 chaincodes for the
RIs and separately for
certificates is being used.
- A service exposing endpoints
for interacting with the network
as well as managing identities
and IPFS pinning.

9. EERIS Reputation
Mechanism
Swagger has been used to describe the
APIs.
To further showcase the functionalities
a dashboard interface has been built.

10. The implemented EERIS Blockchain Infrastructure (EBI) was presented, analyzed and piloted with
representatives of three universities:
a) Politehnica University of Timișoara (UPT) - Lecturer Dr. Vlad Mihăescu, Director of the Center
for Innovation and Technology Transfer – for creating and tracing a technology transfer
contract between the center and a company;
b) West University of Timișoara (UVT) - Lecturer Dr. Cristian Cira, coordinator of the
Postgraduate Program “Entrepreneurship in Blockchain” – for storage and verification of a
document on Blockchain, respectively of the certificate of completion of the postgraduate
program;
c) “Vasile Goldiș” University of Arad (UVVG) - Assoc. Prof. Antoanela Naaji, Director of the
International Relations Department – for storage and open access to technical or medical
research data for participants in international webinars.
The piloting has demonstrated the interest of the universities for the new EERIS facilities issued
by EBI and that they would be included in the current activities, for contracts with third parties,
research projects for open access to research data, programs for which the certificates of
completion are stored on the Blockchain.
4. Piloting

11. Fig.a.1. User ‘Center for Innovation and Technology Transfer’ is active
4.a Technology transfer contract between
the center and a company

12. Fig.a.2. Creating a contract/collaboration

13. Fig.a.3. Contract is stored on Blockchain, the file is stored on IPFS
Fig. a.4. Contracts of a RI

14. Fig.a.5. Partner company approves the contract
Fig.a.6. Collaboration history; any change
requires the approval of the other parties

15. 5. Performance analysis
Performance metrics for the primary functions of the chaincodes
Network runtime metrics

16. • Existing resources: number of researchers,
equipment, services offered
• Information update: first and latest update
• Impact on visitors: message threads, total
number of visits, latest visit
𝑹𝒆𝒑𝒖𝒕𝒂𝒕𝒊𝒐𝒏
= 𝑲! ∗ 𝑵𝑹 + 𝑲# ∗ 𝑵𝑬 + 𝑲% ∗ 𝑵𝑺 + 𝑲' ∗ 𝑫𝑹 − 𝑲( ∗ 𝑫𝑼
+ 𝑲* ∗ 𝑵𝑽 − 𝑲, ∗ 𝑫𝑽 + 𝑲- ∗ 𝑵𝑴𝑺 + 𝑵𝑴𝑹
Example 1:
• Resources: 10 researchers, 10 pieces of equipment, 10 different services
offered
• Updates: added to platform – 10 years ago, latest update – 1 year ago
• Impact: 100 visits since creation, latest visit one month ago, 10 received
messages, 10 responding messages
• If all coefficients have the value 1, total:
• Resources = 1*10 + 1*10 + 1*10 = 30
• Updates = 1*120 – 1*12 = 108
• Impact = 1*100 – 1*1 +1*(10+10) = 119
• Reputation total = 257
6.1. Modelling the Reputation factor – initial
version

17. 𝑹𝒆𝒑𝒖𝒕𝒂𝒕𝒊𝒐𝒏
= 𝑲! ∗ 𝑵𝑹 + 𝑲# ∗ 𝑵𝑬 + 𝑲% ∗ 𝑵𝑺 + 𝑲' ∗ 𝑵() + 𝑲* ∗ 𝑵𝑶𝑫𝑫 + 𝑲-
∗ 𝑫𝑹 − 𝑲. ∗ 𝑫𝑼 + 𝑲0 ∗ 𝑵𝑽 − 𝑲0 ∗ 𝑫𝑽 + 𝑲!2 ∗ 𝑵𝑴𝑺 + 𝑵𝑴𝑹
+ 1
𝒊5!
𝑵𝒐.𝒐𝒇 𝒄𝒐𝒍𝒍𝒂𝒃𝒐𝒓𝒂𝒕𝒊𝒐𝒏𝒔
𝑲!𝟏 ∗ 𝑽𝒊 + 𝑲!# ∗ 𝑫𝑪𝒐𝒍_𝒊 + 𝑲!% ∗ 𝑵𝑬𝒗𝒊
• Existing resources: number of researchers,
equipment, services offered, data sets
(available and downloaded)
• Information update: first and latest update
• Impact on visitors: message threads, total
number of visits, latest visit
• Collaborations: value (interval) for contract,
duration of collaboration, rating of the
beneficiary/beneficiaries for the
Example 2:
• Resources: 10 researchers, 10 pieces of equipment, 10 different services offered,
10 open data sets available, 5 data sets downloaded
• Updates: added to platform – 10 years ago, latest update – 1 year ago
• Impact: 100 visits since creation, latest visit one month ago, 10 received
messages, 10 responding messages
• Collaborations:
• Contract 1: 5000 Euro, 12 Months, final rating: 4/5
• Contract 2: 15000 Euro, 24 Months, final rating: 3/5
• If all coefficients have the value 1, total:
• Resources = 1*10 + 1*10 + 1*10 + 1*10 + 1*5 = 45
• Updates = 1*120 – 1*12 = 108
• Impact = 1*100 – 1*1 +1*(10+10) = 119
• Collaborations = (10-3 * 5000 + 1 * 12 + 20 * 4) + (10-3 * 15000 + 1*24 + 20 * 3) = 97
+ 99 = 198
• Reputation total = 455
6.2. Modelling the Reputation factor –
updated version

18. The implemented reputation mechanism aims to increase openness, impact, and technology transfer of
research infrastructures (RIs) and is designed not only to measure reputation, but also to make it more visible
and, above all, to provide an ecosystem for its growth.
The EBI infrastructure is flexible and extensible, to which all or only a part of the research infrastructure (RIs)
can be connected, for piloting and familiarization. EBI could also be installed for individual or groups of
research or academic institutions.
EBI ensures the immutability, traceability, and audibility of RI data. In this way, the stored open research data
meets the principle of FAIR (Findable, Accessible, Interoperable, and Re-usable), and data storage and
management being performed according to the principle of TRUST (Transparency, Responsibility, User focus,
Sustainability, and Technology) (Lin et al ., 2020).
Future work requires a more extensive performance analysis based on a set of different network settings and
distribution of nodes.
Also, the implemented system can ensure open access to the scientific results (including data) of the RI, and in
the future, the mechanisms could be used also for the evaluation, classification, ranking, financing, and
matching partners.
For further expanding the network and bridging the information into other applications (eg. Brainmap – online
community for researchers), a SSI management system needs to be integrated for sharing identities across
platforms (eg. TrustID, Hyperledger Aries).
The activities towards open research/data on EERIS could contribute to the scientific portfolios of the
academics/researchers and be taken into account for promotion.
7. Conclusions and future work

19. Arun, J., & Carmichael, A. (2017). Trust me: digital identity on blockchain. IBM Institute for Business Value.
EU’s Open Science Policy. (2020). https://ec.europa.eu/info/research-and-innovation/strategy/strategy-2020-
2024/our-digital-future/open-science_en.
data.europa.eu. (2018). Open Data and Blockchain: a match made in heaven?
https://data.europa.eu/de/datastories/open-data-and-blockchain-match-made-heaven.
Holotescu, V., & Vasiu, R. (2020). Challenges and Emerging Solutions for Public Blockchains. BRAIN. Broad
Research in Artificial Intelligence and Neuroscience, 11(1), 58-83.
Leible, S., Schlager, S., Schubotz, M., & Gipp, B. (2019). A review on blockchain technology and blockchain
projects fostering open science. Frontiers in Blockchain, 16.
Lin et al. (2020). The TRUST Principles for Digital Repositories. Scientific Data 7(1).
Open Science Knowledge Hub Romania. (2021). https://uefiscdi.gov.ro/open-science-hub.
UNESCO Recommendations for Open Research (2021). https://en.unesco.org/science-sustainable-future/open-
science/recommendation.
References

20. Thank you!
ICCMAE 2022: The 2nd International Conference on Computational Methods and Applications in Engineering
May 7-8, 2021