**_TOMOCON Data Management Plan_ **

#  Data summary

**Provide a summary of the data addressing the following issues:**

  * **State the purpose of the data collection/generation**

  

  * **Explain the relation to the objectives of the project**

  

  * **Specify the types and formats of data generated/collected**

  

  * **Specify if existing data is being re-used (if any)**

  

  * **Specify the origin of the data**

  

  * **State the expected size of the data (if known)**

  

  * **Outline the data utility: To whom will it be useful**

  

Data within TOMOCON is generated via experimental studies and numerical multi-
physics simulation of exemplary industrial processes. The data serves the
following purposes with the TOMOCON project:

  1. Data is being generated to enhance the understanding of fundamental physical and chemical sub-processes in an industrial process scenario. This concerns transport of momentum, mass and energy in diverse fluid-flow dominated processes, propagation of electromagnetic fields or sound fields as well as kinetics of processes like crystallization. 

  

  2. Data is being used to simulate and assess the performance and interplay of tomographic sensors and control systems in given industrial process model scenarios. 

  

  

The TOMOCON project considers exemplarily the following industrial processes
as model processes for the demonstration of the new technologies: Continuous
steel casting, batch crystallization, inline fluid separation and microwave
drying of porous products.

Data being generated typically represents adequately sampled four-dimensional
physical parameter fields and is complemented by data for geometry
specifications (e.g. CAD files) and boundary as well as initial conditions. It
originates from the following sources:

  1. Numerical simulation data originates from the computational calculation of physical field quantities with specific commercial or proprietary simulation codes. 

  

  2. Experimental data is digitized measurement data from specific sensors and instrumentation, e.g. for temperature, pressure, flow rate or filling-level, and from particle image velocimetry, high-speed video imaging, infrared thermography or diverse tomographic imaging techniques. 

  

  

It is expected that data being produced within the TOMOCON project is
essentially new data as it is based on novel methods, technologies and sub-
models.

By its nature the data being generated within TOMOCON will be of large size
(typically tens of megabytes to few gigabytes per data set) and of diverse and
often proprietary digital formats and encoding.

TOMOCON partners will share data in order to commonly develop new models,
sensors and process control systems. Moreover, some of the data may be of
interest for other scientists’ groups to use them for code validation and own
sensor or model developments.

The latter is subject of this data management plan and further referred to as
TOMOCON Open Access Data. TOMOCON Open Access Data shall undergo a dedicated
quality assurance before publication.

#  FAIR data

**2.1. Making data findable, including provisions for metadata:**

  * **Outline the discoverability of data (metadata provision)**

  

  * **Outline the identifiability of data and refer to standard identification mechanism. Do you make use of persistent and unique identifiers such as Digital Object Identifiers?**

  

  * **Outline naming conventions used**

  

  * **Outline the approach towards search keyword**

  

  * **Outline the approach for clear versioning**

  

  * **Specify standards for metadata creation (if any). If there are no standards in your discipline describe what metadata will be created and how**

  

TOMOCON Open Access Data will be made accessible by a unique digital object
identifier.

Significant metadata will be provided to ensure discoverability and
identifiability. Generally metadata provision follows the DataCite Metadata
Scheme. Provision of specific metadata beyond that scheme is in the
responsibility of the individual partners. However, the following type of
metadata is suggested:

_Numerical data:_ Software and version used for data generation; input data
including boundary conditions and numerical grid; methods of simulation time
step control; used submodels e.g. for turbulence, kinetics, heat transfer
etc.; digital output data format.

_Experimental data:_ Description of the experimental setup; reference to
geometry data, boundary conditions, specifications of relevant materials and
fluids; instrumentation and their specifications (sampling rate, operational
limits, accuracy/uncertainties).

Naming of data has to be done in a way that is most clearly indicating the
type of data and the general background of its generation (e.g. experimental
vs. numerical, type of experiment, related industrial application, purpose of
the study).

**2.2. Making data openly accessible:**

  * **Specify which data will be made openly available? If some data is kept closed provide rationale for doing so**

  

  * **Specify how the data will be made available**

  

  * **Specify what methods or software tools are needed to access the data? Is documentation about the software needed to access the data included? Is it possible to include the relevant software (e.g. in open source code)?**

  

  * **Specify where the data and associated metadata, documentation and code are deposited**

  

  * **Specify how access will be provided in case there are any restrictions**

  

Making open access data accessible is in the responsibility of the individual
partners. Many partners have their own institutional data repositories with
specific procedures and access rules. If partners have no own repository they
may either use public repositories, such as for example the Zenodo repository
at CERN, or repositories of other TOMOCON partners. For the latter HZDR as the
Coordinator will offer its RODARE repository. As other platforms HZDR's RODARE
is interconnected to research data harvesters like OpenAire of the EU to
ensure most efficient retrievability of data.

**2.3. Making data interoperable:**

  * **Assess the interoperability of your data. Specify what data and metadata vocabularies, standards or methodologies you will follow to facilitate interoperability.**

  

  * **Specify whether you will be using standard vocabulary for all data types present in your data set, to allow inter-disciplinary interoperability? If not, will you provide mapping to more commonly used ontologies?**

  

Alignment with standardized ontologies, such as DCAT Data Catalog Vocabulary
is strongly encouraged.

**2.4. Increase data re-use (through clarifying licenses):**

  * **Specify how the data will be licenced to permit the widest re-use possible**

  

  * **Specify when the data will be made available for re-use. If applicable, specify why and for what period a data embargo is needed**

  

  * **Specify whether the data produced and/or used in the project is useable by third parties, in particular after the end of the project? If the re-use of some data is restricted, explain why**

  

  * **Describe data quality assurance processes**

  

  * **Specify the length of time for which the data will remain re-usable**

  

TOMOCON Open Access Data is public and recommended to be licensed according to

Creative Commons Attribution 4.0 International (CC BY 4.0). For public
software licenses GPLv3 is recommended. Embargo periods of up to 12 months may
be imposed to restrict the use of data within the TOMOCON consortium.

#  Allocation of resources

**Explain the allocation of resources, addressing the following issues:**

  * **Estimate the costs for making your data FAIR. Describe how you intend to cover these costs**

  

  * **Clearly identify responsibilities for data management in your project**

  

  * **Describe costs and potential value of long-term preservation**

  

TOMOCON Open Access Data data will be stored in repositories bound to the FAIR
principles. Costs incurring to the partners in form of labour expenditure for
preparing the data publication is covered by the EU funding. It is expected
that costs in form of labour expenditure after the funding period will be
minimal (e.g. by any kind of updating) and can be born by the respective
partners via their institutional funding. The responsibility for data
management is with the individual principal investigators of the research
groups where the data has been produced.

#  Data security

**Address data recovery as well as secure storage and transfer of sensitive
data**

It is expected that the chosen institutional and public data repositories
provide an adequate frame for secure data storage and recovery. No personal
data will be stored with TOMOCON Open Access Data sets.

#  Ethical aspects

**To be covered in the context of the ethics review, ethics section of DoA and
ethics deliverables. Include references and related technical aspects if not
covered by the former**

There are no ethics issues with TOMOCON data according to the DoA. All work
including data generation will follow best practice guidelines of the EU and
the existing national rules.