summer school

OPEN SCIENCE

"Open science is the movement to make scientific research, data and dissemination accessible to all levels of an inquiring society"FOSTER consortium

Researchers benefit from Open Science in different ways: * Increased visibility: citations, mentions in social and other media * Increased credits: references to publications, data and methods, awards for openness * Increased funding: rewards for openness, awards for clear definitions of copyright/proprietary rights * Improved networking: new opportunities (From: Open Science and Research Initiative, 2014).

But the effects go beyond research: teachers also benefit by integrating the available knowledge directly in their courses and when companies have access to the latest scientific ideas, they can build on these.

https://www.tudelft.nl/en/open-science

OPEN DATA

Data is open if it can be freely accessed, used, modified and shared by anyone for any purpose - subject only, at most, to requirements to provide attribution and/or share-alike.

5 STAR OPEN DATA

make your data available on the Web (whatever format) under an open license

make it available as structured data (e.g., Excel instead of image scan of a table)

make it available in a non-proprietary open format (e.g., CSV instead of Excel)

use URIs to denote things, so that people can point at your data

link your data to other data to provide context

RESEARCH DATA

Research data and records are defined as the recorded information (regardless of the form or the media in which they may exist) necessary to support or validate a research project’s observations, findings or outputs

Examples of research data: Digital texts or digital copies of test Spreadsheets Audio, video Computer Aided Design (CAD) Waveforms Statistics (SPSS, SAS) Databases Geographic Information Systems (GIS) and spatial data Digital copies of images Matlab files Computer code Protein or genetic sequences Artistic products Web files

RESEARCH DATA

FAIR

SHOULD BE... FINDABLE: discoverable with metadata, identifiable and locatable by means of a standard identification mechanism ACCESSIBLE: openly available as the default INTEROPERABLE: exchangeble between researchers, institutions, organisations, countries, etc. and compliant with available (open) software applications REUSABLE: licensed to permit the widest re-use possible

CAN BE... RAW DATA: data that have been collected or generated in the course of research, but have not been analysed or manipulated yet. PRIMARY DATA: data that have been collected in the first person through direct observation, recording, measurement.

HOW FAIR ARE YOUR DATA?

HOW REUSABLE ARE YOUR DATA?

METADATA

Data about data: data providing information about one or more aspects of the data and it is used to summarize basic information about data, which can make easier to track and work with specific data.

Metadata should at least specify:

DESCRIPTIVE METADATA

• an identifier (a DOI),
• a creator (the name and affiliation of the main researchers involved in producing the dataset),
• a title (the name or title by which the dataset is known),
• a publisher (the name of the entity that holds the dataset),
• a publication date (the year when the dataset was or will be made publicly available) and the type of resource you are describing.

TECHNICALMETADATA

STRUCTURAL METADATA

ADMINISTRATIVE METADATA

HERE SOME EXAMPLES OF METADATA SCHEMAS

http://www.ucl.ac.uk/library/research-support/research-data/best-practices/guides/creating

DATA MANAGING

WHY IS IMPORTANT TO MANAGE RESEARCH DATA?

To ensure research integrity and validation of results.

To increase research efficiency

To facilitate data security and minimise the risk of data loss

To ensure wider dissemination and increased impact.

To enable research continuity through secondary data use.

To ensure compliance with a funding agency’s requirements.

http://libguides.ucd.ie/data/why_manage

DATA MANAGING

HOW TO ORGANISE RESEARCH DATA?

Structure research data

Collect research data

Name research data

Pay attention to file formats

Annotate research data using metadata

DATA MANAGING

DATA MANAGEMENT PLAN

DMP provides information on:

BENEFITS OF A DMP

Data that will be generated

improves the EFFICIENCY of your workhelps you to STRUCTURE your research output increases LONGEVITY of your research enables LARGE-SCALE exploration in future gathers ALL information in ONE place

How to ensure curation, preservation and sustainability

What part of data will be open and how

What should I include in my DMP?

DATA MANAGING

DATA MANAGEMENT PLAN

FUNDER'S REQUIREMENTS

More and more funders are asking researchers to submit a DMP as part of their grant applications. Check if this is one of your's funder requirements

HORIZON2020 (the European funding program for research and innovation) states that participating projects are required to provide a DMP that indicates what data will be open. Read also 'Guidelines on data management in Horizon 2020'.

DATA MANAGING

HOW TO MANAGE PRIVACY, SENSITIVE AND PERSONAL DATA

WHAT TO DO?

Research data may contain information about living, identifiable individuals, or other information that is sensitive, for example about criminal justice or national security.

Before collecting data: prepare informed consent, information about research, data sharing and preservation After collecting data: protect identities, anonymisation regulate access where needed

You are responsible for ensuring your handling of all this information is secure and complies with the law.

What about GDPR?

You will find useful information about keeping your data secure in the following Guide on Storing and preserving data. Information on research integrity and on research ethics is also available.

DATA PRESERVATION

Basic aspects of DATA CURATION activities in the preservation of research data

Think about what will happen to data after the end of a project, where they will be stored, for how long, and how to make them accessible in the long term.

Decide what will be made available, from raw data to final outputs.

Choose formats on the basis of the future use of the data. Formats will become obsolete over time, and you should plan for this. You should also bear in mind, however, that the risk of obsolescence will depend on the software.

Keep a track of any metadata change or new version of your dataset.

DATA PRESERVATION

Data Storage

&

Security

DATA SECURITY refers to keeping your data safe. This means both: - ensuring that data are not lost, and that they are kept free from corruption. - controlling access to your data as appropriate – ensuring that no one who shouldn’t be able to see your data can. This may be achieved in a variety of ways, including physical security (e.g. storing data in a locked room), password protection of files, and encryption.

DATA STORAGE refers to where and how you keep your data. It involves both: - file formats (for example, deciding between options such as plain text, rich text, or proprietary formats) - media for physical storage of data (for example, hard-drives, CD-Roms, networked storage and servers, etc.)

6 STEPS TO STORE YOUR DATA IN A SECURE MANNER

CHECK IF YOUR DATAARE PROPERLY STORED

DATA PRESERVATION

HOW to preserve research data

Preservation actions should ensure that data remains * AUTHENTIC * RELIABLE * USABLE * UNDERSTANDABLE * ACCESSIBLE while maintaining its integrity. Actions include: - data cleaning - validation - assigning preservation metadata ensuring acceptable data structures or file formats.

Think about preservation AT THE START of your research project – the data you will be working with, the digital outputs that will be produced, where they will be stored, in what way and for how long.

CHECK IF YOUR DATA ARE PROPERLY PRESERVED

DATA PRESERVATION

WHERE to preserve research data

Preservation is often achieved by depositing the digital material in an archive (repository) during the project, or shortly afterwards. WHY TO DEPOSIT DATA IN AN ARCHIVE? TO GUARANTEE LONG-TERM PRESERVATION: this is for reusing data. TO FACILITATE INTEROPERABILITY: in order to be able to compare and combine data sets with each other, it is important that metadata are assigned consistently and that metadata standards and data formats are used. TO FACILITATE A DATA CITATION NETWORK: Being able to cite data and link data and literature leads to more transparency in academic science and furthers scientific integrity.

Well, which data archive best fits me?

The White Paper 'Sustaining Domain Repositories for Digital Data' describes the roles of data archives in detail.

DATA PRESERVATION

WHO cares about data preservation?

the best way to improve the impact of your research

DATA SHARING

AND DATA CITATION

How to cite?

Who produced the dataset (creator or author)? The title of the dataset? Which is the unique identifier of the dataset (DOI or a link to the dataset if it is online)? When was published the dataset? What is its version number? When the dataset was accessed? Who is the distributor of the dataset?

Data citation refers to the practice of providing a reference to data in the same way as researchers routinely provide a bibliographic reference to outputs such as journal articles, reports and conference papers.

How to be cited?

For data products to be uniquely identifiable and attributable to their data creators two types of identifiers are recommended:

ORCID: a persistent author identifier

DOI: a persistent identifier (PID) to your dataset

the best way to improve the impact of your research

DATA SHARING

AND DATA CITATION

Why share?

* Increases the academic profile of researchers, by ensuring credit is given to data as a research output in its own right Increases the impact and visibility of research * Complies with many funders' requirements, including making best use of investment by avoiding replication * Allows data to be independently validated and tested * Leads to new collaborations and partnerships * Provides great resources for education and training

There are many motivations to share research data. Many funders view them as a public good that should be shared with the academic community and beyond.

How to share?

Deposit in an archive

Submit your data to a journal

As open as possible, as closed as necessary

Informal sharing

ROLES AND RESPONSIBILITIES

Who will be responsible for data management?

FUNDING BODIES

ARCHIVES

RESEARCHERS

INSTITUTIONS

REGULATORY RESPONSIBILITIES

ASSOCIATIONS

PUBLISHERS

A. De Robbio – Gestire i dati di ricerca: nuove prospettive di collaborazione e integrazione, Milano 2017

ROLES AND RESPONSIBILITIES

Who will support open data and open science?

EOSC

OPEN

SCIENCE

CLOUD

EUROPEAN

EOSC cannot be built exclusively in and for Europe, as research and innovation are global. Europe, being inherently federated, is in a strong

Open is referred to accessibility underproper and well defined conditions, reminding that not all data and tools can be open.

Science includes the arts and humanities. Science Cloud infrastructure should support not only innovative scientific research but also societal

The term cloud refers to commons of data, software, standards, expertise and policy related to data-driven science and innovation.

position to lead this

innovation and

initiative.

productivity.