Ethics Committee

Advisory functions, research, investigation, promotion and dissemination in ethics (art. 25 of the Ethical Code for the University):

• Prof. Agar Brugiavini - Curriculum
• Prof. Daniela Meneghini - Curriculum
• Dr. Michela Del Bono - Curriculum
• Dr. Esterita Vanin - Curriculum
• Dr. Alessandro Bernes - privacy, data protection and law expert - Curriculum
• Dr. Stefano Calzavara, computer science expert - Curriculum
• Prof. Lucetta Scaraffia, research ethics expert 
• Dr. Chiara Da Villa, expert in Data Management
• Dr. Silvia Zabeo, euro-planning expert - Curriculum
• Mr. Cesare Bulegato, appointed representative by the Student Representatives Assembly 
• Dr. Rachele Svetlana Bassan, appointed representative by the Doctoral Students Council - Curriculum

The Subcommittee is composed by:

• prof. Agar Brugiavini (President);
• dott. Alessandro Bernes (expert member in privacy, protection of personal data and legal matters);
• dott. Stefano Calzavara (expert member in computer science);
• prof. Lucetta Scaraffia (expert member in research ethics);
• dott. Chiara Da Villa (expert member in Data Management);
• dott. Silvia Zabeo (expert member in European projects).

The DMP is a tool that allows researchers to plan the collection, storage, description and disclosure of their research data and metadata from the very beginning of their activity; it therefore represents a reference framework for responsible management of the data collected and produced, according to FAIR best practices:
Findable - Accessible - Interoperable - Reusable / Replicable.

The management of research data is a very complex process, but if set correctly from the beginning on the basis of a Data Management Plan (in the form of a tool) it can be easier, since it allows the researcher to plan synthetically (in the initial version) and gradually in more detail (subsequent versions) the research phases: planning, creation, organisation, sharing and security.

In fact, the DMP represents the entire life cycle of data, allowing its traceability, availability, authenticity, citability, appropriate storage and adherence to clear legal parameters and appropriate security standards. The DMP is considered in all respects by the European Commission to be a mandatory living document and deliverable, to be drafted within 6 months of the approval of the project and its conclusion.

The DMP, as:

• living document can have several versions
• deliverable must be accompanied by a "unique identifier", a sort of barcode assigned automatically (in the form of a handle) upon loading on the trusted repository
• machine actionable it must be transformable as a PDF to be read by computers as well.

Researchers who are beneficiaries of all funded research projects that collect or generate open data in which ethical or privacy issues emerge in relation to computerised data management must draw up the Data Management Plan (DMP).

In order to:

• increase the impact of research: making data available to other researchers means increasing the knowledge and relevance of your research
• save time: drafting the DMP in time allows you to plan your needs, define the costs incurred during the research, saving time and subsequently resources
• protect data: storing your research data in "trusted repositories" (Zenodo or others identifiable in re3data) safeguards your work and your time
• maintain data integrity: the DMP helps planning how to manage and document the life cycle of the data produced during the research for their future availability and use
• comply with the requests of the funders: many agencies require the filing of data (and related metadata) as an integral part of the funded research project
• promote new discoveries: exposing your data and sharing it with other researchers can lead to the development of new research, as well as helping projects that are not funded
• support open access: your open access data is valuable to the scientific community
• access data processed by other researchers: the open sharing of information allows you to see what other researchers have done

Name	Symbol	You can	You cannot	You must
Attribution		use, modify, distribute		Mention the author, indicate the changes
Share alike		use, modify, distribute		Mention the author, indicate the changes, use the same license
No derivatives		use, distribute	modify	Mention the author
Non commercial		use, modify, distribute	use for commercial purposes	Cite the author, indicate the changes
Non commercial-Share alike		use, modify, distribute	use for commercial purposes	Cite the author, indicate the changes, use the same license
Non commercial-No derivatives		use, distribute	modify, use for commercial purposes	Mention the author

The Creative Commons (CC) licenses allow you to communicate in a simple and standardised way which rights the author of the work reserves and which he/she renounces for the benefit of users.

Three actors are involved in the usability of the publications:

• author vs editor (in the case of copyright. For more information, see the page on Copyright)
• author vs reader (in the case of open access and Creative Commons licenses).

The latter specify to the reader how they can use the materials freely made available by the publisher and what rights are granted to them.
Creative Commons licenses combine an image with the specific right.

CC licenses are periodically updated and universally used to share content on the internet because they are easy to understand and graphically identified.
For further information, visit CreativeCommons.

Not all data can be opened; even just a subset of data can be made open.

The European Commission provides for the possibility of exercising the opt-out if the following conditions are met:

• in case of need for data protection for possible economic exploitation

• in case of incompatibility with data protection for security reasons

• in case of incompatibility with the protection obligations of sensitive data
• in the event that making the data open is a risk for the achievement of the main objective of the project
• other legitimate reasons to describe and justify

The DMP mainly concerns the following aspects:

1. Data summary
   This section describes the data that may be collected, stored, produced, reused and disseminated during the research: knowing exactly and precisely the type of data, the Research Ethics Subcommittee will be able to formulate an opinion on the technical, organisational and security measures that the project will have to adopt and whether these are adequate for data management. The information presented here will also help other researchers understand the data.
   Please note that not all research data should be considered personal data.
2. FAIR Data
   This section presents the measures to ensure that the data is:
   • Findable = equipped with unique identifiers, keywords, metadata standards and other practices that optimise their identification and reuse;
   • Accessible = deposited in certified and reliable digital platforms for long-term storage; accessible as data (including open access), with access protocols and any restrictions; accompanied by rich metadata that allow their discoverability. In the event that certain data or metadata cannot be shared, adequate justification is required.
   • Interoperable = described using vocabularies, standards, formats or methodologies that will allow their exchange, reuse and interoperability.
   • Re-usable = therefore the researcher will provide information on the required documentation (e.g., explanatory methodology, codes, variables).

3. Other research outputs
   This section deals with the management of other research products generated/reused in the course of the project (e.g., software, models, new materials) and, where appropriate, details their compliance with FAIR principles.
4. Allocation of resources
   This section discusses the costs associated with compliance with FAIR principles and accountability in data management.
5. Data security
   It is the most important section for research projects that collect personal data.
   It deals with security, storage and conservation, data recovery. 
6. Ethics
   In this section the researcher presents all ethical or legal issues that may have an impact on data sharing. Also, when the research uses personal data, refer to aspects such as informed consent.
7. Other issues
   Indicate whether other data management procedures or practices are relevant to the project.

Data is almost never separated from metadata.
Metadata describes data containing specific information such as type, length, text description and other features.
Considering the scope of data (document files, images, videos, etc.) and their exponential increase, it is not surprising that understanding and managing metadata has become a priority.

Metadata serves a variety of purposes, one of the most common being resource discovery for example:

1. Facilitate interoperability and integrate resources.
   Using metadata to describe resources allows humans and machines to understand it. This allows for more effective interoperability, i.e., how data is exchanged between many systems with heterogeneous operating platforms, data structures and interfaces.
2. Facilitate digital identification through standard numbers that uniquely identify the asset defined by the metadata.
   Combining metadata with sets of unique data identifiers enables differentiation of objects and resources.
3. Protect resources and their future accessibility.
   We know the problem of data longevity, the fragility of digital information and its susceptibility to corruption or alteration. For the purposes of archiving and conservation, metadata are required to trace the origin of the object and describe its physical features and behaviour, so that it can be replicated by technologies in the future.

To preserve and store data and related metadata, researchers can use various platforms:

• for temporary and secure archiving, you can use the Google Drive space associated with each University account. This space can be used for any type of data, with the exception of those with explicit limitations on the storage location
• for the definitive deposit of data and metadata you can use a repository after verifying in re3data that it is certified as reliable and compatible with the main standards: Zenodo, Trustworthy Digital Repository, Data Seal of Approval, Nestor Seal, ISO (the latest standard is No. 16363, produced in 2012), ICSU-WDS
• for the definitive deposit of publications, you can use the ARCA (Ca' Foscari Research Archive) publication platform, which provides for the harvesting of metadata towards OpenAIRE according to FAIR best practices.
• for the deposit of the DMP in a machine actionable format, ARCA automatically assigns a persistent identifier

Social platforms such as Academia.edu or Researchgate are not trusted repositories.