**ELENA**

Low energy **ELE** ctron driven chemistry for the advantage of emerging **NA**
no-fabrication methods

**Data Management Plan**

**ORDP – Open Research Data Pilot**

March 31  st  2017 (M06)
#  DATA collection and storage

ELENA is a research and training based project that will develop new research
data through the conduct of 15 collaborative PhD research projects. There are
three broad categories of data that will be acquired during the period of the
grant:

  1. Data derived from laboratory based instruments. 

  

  2. Data derived from theoretical studies, computational models and simulations. (iii) Data from commercial facilities. 

  

  

Each of these categories has its own types of data, different reduction
procedures and archiving requirements.

Categories (i) and (ii) are predominantly expected to provide fundamental data
that may be published in open access publications whilst data derived in the
third category using commercial instrumentation may be subject to some
restrictions due to commercial sensitivities and IPR issues.

_Data derived from laboratory based instruments;_ There are many different
types of data generated by the wide range of laboratory instruments available
across the ELENA Consortium all have their own associated, often written in-
house, data reduction and processing pipelines, but the raw data are always
preserved and archived.

Raw data from the instruments are produced as ASCII files. These are usually
read into a spreadsheet program, such as Excel, for reduction, from where they
are transferred into plotting or other display software (SigmaPlot etc.). The
exception to this protocol occurs when specialist control software associated
with the instrument takes in raw data and reduces it internally. The raw data
however, are still available for off-line manipulation. Software is generally
Excel, or other proprietary software that can read ASCII files. Because the
raw data are ASCII files, there are no issues associated with reading them.
Raw data are stored on the PC that controls each instrument. These are
regularly backed up to host server systems. Data processing is only applied to
copies of the raw files.

Records of all analyses are preserved by a combination of written and
computer-generated records for each instrument. There is usually no
proprietary period associated with data derived from laboratory-based
instrumentation. Data are preserved for a minimum period as required by local
protocols, indeed the raw data are usually preserved indefinitely, even after
staff/PDRA/students have left the host institution. During the ELENA project a
summary of such protocols for each Institution will be assembled and a guide
to good practice prepared between the partners.

There is usually a large amount of context information associated with any
specific measurement and therefore data that have value to others are
generally those that have been reduced through, e.g. background corrections,
calibration factors and standardisation and have a raft of supporting
information. Documentation of the data reduction processes and relevant
contextual information is usually maintained alongside the data, as text
files. Such reduced data are stored by individuals on their desktop PC and
usually automatically backed up to an institutional server system.

_Data derived from theoretical studies, computational models and simulations._
Data derived from theoretical studies, computational models and simulations
follows many of the same procedures as that derived from laboratory
instrumentation. Such data is often generated on dedicated workstations
accessing institutional computing services though data may also be generated
through access to larger external computational facilities (super computers
and cloud based services). Such studies may lead to generation of large
amounts of metadata and many generations of models, simulations and
theoretical formalisms not all of which are traditionally archived rather
records are maintained of the input data that allow for recreation of such
models, simulations and theoretical formalisms.

Product data are stored either directly on the PC/workstation that initiates
the theoretical study, computational models or simulations but duplicates are
commonly stored on the accesses computational facility (cluster,
supercomputer). These are regularly backed up by server systems. Relevant
contextual information is usually maintained alongside the data e.g. as text
files. There is usually no proprietary period associated with data derived
from theoretical, computational models and simulations. Data are preserved for
a minimum period as required by local protocols, indeed the raw data are
usually preserved indefinitely, even after staff/PDRA/students have left the
host institution. During the ELENA project a summary of such protocols for
each Institution will be assembled and a guide to good practice prepared
between the partners.

When new programmes are written and or derived these are also archived both on
the PC/Workstation and the enabling facility (Cluster/supercomputer). It is a
requirement of most institutions that relevant contextual information is
maintained alongside the programmes together with any source software.
Similarly, where data is produced using different versions/generations of
software older (replaced/upgraded) versions of such software are often
archived. Protocols for sharing good practice in archiving software and
programmes as well as the data produced will be discussed within the ELENA
consortium.

As for laboratory derived ‘raw’ data generated data may be subsequently
analysed by being into a spreadsheet program, such as Excel from where they
are transferred into plotting or other display software (SigmaPlot etc.).
Processed data are stored on the PC/workstation on which analysis is
performed. These data are regularly backed up to host server systems.

_Data from commercial facilities_ Whilst data management procedures for data
collected on commercial instrumentation are similar to those described above
for laboratory instrumentation and theoretical studies, computational models
and simulations it is recognised that commercial companies may develop their
own software and data analysis tools that are not openly available. Similarly
collected and derived data may by commercially sensitive subject to IPR and/or
subject to proprietary periods. Protocols and procedures for access, storing
and disseminating such data will be outlined where necessary/appropriate in
ESR projects including secondments.

#  DATA Access

The ELENA project shall facilitate open access to all of its generated data
except where there are commercially sensitive and IPR declared issues. This is
in accord with the ELENA dissemination and outreach plan and the ELENA
Memorandum of Understanding for the ‘Promotion of commercial exploitation’ of
results.

Data will be published throughout recognised publications including Journals,
conference abstracts, proceedings, reviews and books. These published data are
anticipated to be analysed, reduced, product data and, where practical, will
be produced in accordance with open access protocols. Such data may also be
stored in Consortium member’s repositories (several members having on-line
repositories of published work where freely-available records of all published
work, including unformatted versions of manuscripts prior to final publication
are downloadable. In addition, the ELENA Website _https://elena-eu.org_ will
build a publicly available data repository that will list tables of data that
have been published (including on-line supporting material), linking to the
published articles.

The raw data will not be directly accessible without prior request, because
each set of data has its own custom-designed pipeline of reduction,
calibration and standardisation but the consortium may provide raw and
processed data to interested parties upon reasonable request.

One of the issues that has faced curation and archiving of reduced data is
keeping a record of the processing of raw data, especially if it has been
acquired as part of a collaboration or consortium and may therefore be
generated in several different institutions. Procedures for collating such
reduced data on the basis of named ESR projects will be explored during the
ELENA project.

_Data Sharing._ Data (raw and processed) may be reused for further research
and analysis upon satisfying criteria agreed by the members. Data transfer
between consortium partners to further conduct of ESR projects and to further
secondments and training is expected. In the event of any concerns or declared
conflicts of interest between members the ELENA Supervisory Board shall be
responsible for resolution of such issues in accord with managerial process as
declared in the Grant Agreement

#  DATA Management resources

##  Support for Data Management

At the present time, the ELENA project does not provide any additional
resources for data management and access as these are included as part of the
ELENA consortia members’ infrastructure. Each of the ELENA consortia members
are developing their Research Data Management capabilities in line with new
procedures and protocols for data management being enacted at national and
international level for example many are based on guidelines established by
the Digital Curation Centre; _http://www.dcc.ac.uk/_ ). Several members
(particularly HEIs) have a dedicated Research Data Manager who advises their
staff and students.

As part of their training, ELENA ESR students will be lectured on _Research
Data Management_ and part of such training will involves completion of a Data
Management Plan (DMP), again following the guidance developed by the Digital
Curation Centre

( _https://dmponline.dcc.ac.uk/_ ).

#  DATA Security

All raw data is secured on PC/Workstations/Cluster/Supercomputer data archives
which are regularly backed up according to Host institutional and facility
data management protocols and processes. In many cases, raw data are preserved
indefinitely, even after staff/PDRA/students have left the institution, indeed
many of the consortium institutions ensure that when a member of staff, PDRA
or a student leaves, their data have been archived and curated appropriately
and this will be detailed to ELENA employed ESRs. Written records (laboratory
notebooks, online notebooks etc) are maintained in institutional repositories
and nominated managerial staff (e.g. Directors of Research) have access to all
datasets maintained on the department and university servers.

Analysed, published data is both archived by the publishers and also in
Institutional repositories and databases as described in 2 above ensuring long
term data curation and storage.

#  ETHICAL ASPECTS

None of the data to be collected and or analysed in the ELENA programme is
subject to any ethical issues as defined in the Grant agreement.