#  Executive Summary

##  Objectives

EMHASIS should establish rules on data property, sharing and right of the
first use, including necessary metadata for fair sharing in accordance to the
EU policy of open data within the data management plan. This involves the
property of data, duration of confidentiality for data involving private
companies, principles that address consortium agreements in EU or national
projects and of novel methods and techniques.

##  Main results

An operational Data Management Plan (DMP) is currently implemented within the
related EPPN2020 project providing transnational Access and addressing data
management. Within EMPHASIS a DMP which can serve as a template for further
partner activities will be elaborated to reduce the loss of data and increase
the availability and reusability of data according to the legal and ethical
standards. In general plant phenotyping data are generated during the research
process, that are used for it, or that are the result of the research process
and may occur in different media types and formats (as numerical data, images,
documents, texts etc.) during the data life cycle. The metadata in this
context are important for the re-use of research data ensuring also the
possible verification of research results by third parties addressed by
Minimum Information on Plant Phenotyping Experiments (MIAPPE). In general
research data should be published and EMPHASIS will strongly encourage that
data should be published in a way that access to these data is enabled and
possible, e.g. via a web interface or a citable data publication.

Research activities between two or multiple partners will be supported by
agreements including data management issues, currently a template of such an
agreement is used within the EPPN2020 projects and will be adapted for
EMPHASIS.

#  The goal of the Data Management Plan

A Data Management Plan (DMP) describes the management of datasets generated
and processed during and after the use of EMPHASIS services such as access to
plant phenotyping facilities to perform dedicated experiments. As EMPHASIS
goes beyond a simple H2020 project, there are specific requirements and
sustainability issues that need to be addressed. This DMP shall develop a
general framework to help manage data, meet funder requirements, and
facilitate multiple use of data by the scientific community. As such, the DMP
ranges from data acquisition to the evaluation, processing up to archiving and
publication of the data, where appropriate. The goal is to make these data
“findable, accessible, interoperable and reusable” (FAIR), which is becoming
increasingly important in many research projects, requiring a proof of
structured data management embedded in a sound data policy during and after
completion of a research project. Specifically, the ERC Scientific Council
recommends to “ _all its funded researchers that they follow best practice by
retaining files of all the research data they have produced and used during
the course of their work, and that they be prepared to share these data with
other researchers whenever they are not bound by copyright restrictions,
confidentiality requirements, or contractual clauses.”_ 1  As such a DMP
should:

  * reduce the risk of data loss 

  

  * make data available and reusable 

  

  * promote the implementation of ethical standards and principles of Good Scientific Practice 

  

  * create legal certainty 

  

  * improve data exchange within research groups 

  

Practical implementation of a DMP in plant phenotyping and as such highly
relevant for EMPHASIS has been performed in the I3 project EPPN2020:
_https://eppn2020.plantphenotyping.eu/Data_Policy_

#  Data description

The general aim is that data are interoperable between platforms and that
querying mechanisms are standardized. All platforms will collect data in such
a way that this is eventually possible, and tools will be progressively
deployed in the project sites. The scientific managers of phenotyping
facilities shall be responsible for managing the data and ensure that the DMP
is carried out.

Research data, in very general terms, refer to all data that are generated
during the research process, that are used for it, or that are the result of
the research process. Depending on the specific research question and methods
used, data are generated, obtained or collected, observed, simulated, derived,
validated, processed, analysed, published and finally archived. These data
therefore may occur in different media types and formats, the aggregation and
quality of these data depends on the stage in the life cycle of the data.

Specifically, data collected in phenotyping experiments can be numerical data,
images, documents, texts or manual measurements. The data need to be
complemented by metadata that describe the research data. This may include
includes authorship, contact data, time of creation, it defines the data
formats used and contains the context that led to the data. Additionally,
metadata should include settings of experimental sensors or instruments,
environmental conditions, comments, and measurement uncertainties etc. The
metadata is essential for the re-use of research data ensuring also the
possible verification of research results by third parties.

In plant phenotyping the Minimum Information About a Plant Phenotyping
Experiment (MIAPPE) comprises both a conceptual checklist of metadata required
to adequately describe a plant phenotyping experiment, and software to
validate, store and disseminate MIAPPE-compliant data.  2  Within EMPHASIS, we
strongly encourage to follow the recommendations outlined in MIAPPE.

Examples of data categories and sources that need to be managed in a
phenotyping experiment are:

  * Resource description: information of genotype, seed, accession 

  

  * Facilities: installations, sensors, cameras, conveyors and specific devices 

  

  * Trait recovery work-flows: sensor and image analysis methods and software tools used to extract traits from raw image and other data 

  

  * Phenotypic data at plant or population level, e.g., image-based traits, phenological stages, manual measurements 

  

  * Environmental conditions as collected by sensors (e.g. soil water status, air temperature or evaporative demand) 

  

  * Date and description of management events (e.g. irrigation, pruning, sampling) and of observations (e.g. plant disease, accidents) 

  

  * Characteristics of experiments e.g. design, protocol and organisation 

  

#  Data publication

Basic utilisation of research data is a publication, specifically in the
academic context. Data are exploited and published by the scientists
responsible for them, unless there are substantial grounds for not doing so.
This first use of data is usually a publication in a specific journal, the
extent and duration of the first exploitation can be determined in the DMP and
the end of the first exploitation phase should be context-dependent and
justified. For example within the EPPN2020 project, “data will be published
whenever possible, and made available either after publication or at the
latest three years after the last day of the experiment.”  3

Within EMPHASIS we will strongly encourage that data should be published in a
way that access to these data is enabled and possible, e.g., via a web
interface or a citable data publication. An important technical tool for
publishing research data is a data repository, a server service on which data
can be uploaded by the data creators. This data should get a worldwide unique
identifier (e.g.

a DOI) and can be searched and downloaded. There is a number of different
repositories e.g.:

  * topic specific repository (esp. for plant science and phenotyping), e.g. e!DAL  4 

  

  * generic repository, e.g. zenodo  5  , dryad  6 

  

#  Legal status of data

Research data may have an intellectual level of creation worth of protection.
In order to ensure legal certainty, it should always be assumed that
protection is important, i.e. that usage and exploitation rights are clarified
contractually with external partners. EMPHASIS will strongly support the
establishment of contractual agreements in research projects to ensure fair
exploitation of data. Currently, there is e a template for an agreement for
bilateral project within the I3 project EPPN2020 to be used within the
Transnational Access and to clearly define the roles as well as rules for data
use and reuse by the access provider and user.