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2 Research Data Infrastructures and Engineering Metadata
2.2 Research Data Infrastructures
Research data infrastructures enable the data to become findable and accessible (the
FA in FAIR), whereas semantic standards enable the interoperability and reusability
(the IR in FAIR). Hence, research data infrastructures are the second crucial pillar
for FAIR data technology as both parts are inseparable for semantic interoperability
in materials modelling. Research data infrastructures resemble to repositories as
they ensure enriching data with metadata, long-term preservation and open-access
availability for the scientific community. Moreover, the data infrastructures serve as
the link between the data and the community, and therefore play a significant role in
science.
This section is organized as follows. First, the requirements and functions for
data infrastructures are explained in detail in Sect. 2.2.1. Then, generic architectural
key characteristics are discussed in Sect. 2.2.2. Moreover, examples of research data
infrastructures relevant for materials modelling are highlighted in Sect. 2.2.3.
2.2.1 Requirements and Functions
Data infrastructures in materials modelling should, besides the typical data management tasks of storing, sharing and enabling FAIR data, support the specific research
by integrating open simulation codes, analytics tools and the management of the
scientific workflow [11]. This means that a data infrastructure goes beyond mere
archival repositories. However, the core of all data infrastructures is an archive with
repositoral functions. The OAIS Reference Model (ISO 14721) can give an orientation how such a core may look like [12], and the following functionality was derived
from this framework:
• Data Ingest Functionalities how to ingest data have to be defined and implemented.
This includes the design of an appropriate user interface and integration in the
workflow.
• Data Preservation and Archiving Originally split into two functionalities in
the OAIS framework, for our purpose of defining functionalities for materials
modelling, merging them into one is sufficient. This functionality should ensure
permanent storage of the ingested data. Data preservation resembles to bitstream
preservation on this layer.
• Data Management This functionality corresponds to metadata management and
linking the data objects according to metadata information.
• Administration This functionality includes not only administrative tasks, but also
policy management and AAI.
2 Research Data Infrastructures and Engineering Metadata
2.2 Research Data Infrastructures
Research data infrastructures enable the data to become findable and accessible (the
FA in FAIR), whereas semantic standards enable the interoperability and reusability
(the IR in FAIR). Hence, research data infrastructures are the second crucial pillar
for FAIR data technology as both parts are inseparable for semantic interoperability
in materials modelling. Research data infrastructures resemble to repositories as
they ensure enriching data with metadata, long-term preservation and open-access
availability for the scientific community. Moreover, the data infrastructures serve as
the link between the data and the community, and therefore play a significant role in
science.
This section is organized as follows. First, the requirements and functions for
data infrastructures are explained in detail in Sect. 2.2.1. Then, generic architectural
key characteristics are discussed in Sect. 2.2.2. Moreover, examples of research data
infrastructures relevant for materials modelling are highlighted in Sect. 2.2.3.
2.2.1 Requirements and Functions
Data infrastructures in materials modelling should, besides the typical data management tasks of storing, sharing and enabling FAIR data, support the specific research
by integrating open simulation codes, analytics tools and the management of the
scientific workflow [11]. This means that a data infrastructure goes beyond mere
archival repositories. However, the core of all data infrastructures is an archive with
repositoral functions. The OAIS Reference Model (ISO 14721) can give an orientation how such a core may look like [12], and the following functionality was derived
from this framework:
• Data Ingest Functionalities how to ingest data have to be defined and implemented.
This includes the design of an appropriate user interface and integration in the
workflow.
• Data Preservation and Archiving Originally split into two functionalities in
the OAIS framework, for our purpose of defining functionalities for materials
modelling, merging them into one is sufficient. This functionality should ensure
permanent storage of the ingested data. Data preservation resembles to bitstream
preservation on this layer.
• Data Management This functionality corresponds to metadata management and
linking the data objects according to metadata information.
• Administration This functionality includes not only administrative tasks, but also
policy management and AAI.