Gap analysis

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This is the page for the gap analysis.

Tacit knowledge "FAIRification and opening of low carbon energy research data"


Consortium members can add any time, they feel that something is important to note even though it is not mentioned in a standard deliverable. In other words, this page collects uncodified, tacit knowledge. It will help us later to compile suggestions and lessons learned. This kind of knowledge is collected two-fold:

  1. Anytime if someone feels that this should be noted. Please write down: Issue, Date, Author (could also be "anonymous"), the issue described in a few words or maximal lines>
  2. During the final day of workshops

Learning process:

  • People are hesitant to adopt new IT technologies, this is even the case among researchers heavily relying on data, algorithms and collaborative online software (e.g., R, platforms, online conferencing, HPC, ...). The effort to encourage change is not to underestimate. Reasons are several, notably, lack of time and uncertainty about potential benefit as well as overall risk aversion preferences. EERAdata is using the online software "Only Office" to facilitate collaboration (in particular also during the Covid-19 period).


FAIR and open criteria:

  • Consortium members have a fair understanding of what FAIR/O is, but there is little knowledge and/or technical experience on how to approach the FAIRification and opening. All, however, share the view that we are at a critical point in time, where we need to implement these criteria. 
  • To deepen knowledge about FAIR/O criteria, it is useful to test the criteria on a database one is familiar with. For this purpose (and to start brainstorming about the platform), AIT has developed a questionnaire for application in the use cases.

Metadata:

  • A good starting point is to think about metadata and to look into existing metadata concepts in one's field. The first step is to understand that also metadata need to adhere to the FAIR/O principles.
  • The next step is to increase knowledge on IT specific terms, i.e. to understand what the difference is between different metadata frameworks (taxonomy, thesaurus, ontology) as well as classification of metadata (high-level, medium-level, low-level OR administrative, structural and descriptive metadata).  WP 2 being in charge of aligning approaches between use cases, participates in all use case kickoffs to bring everybody on the same page. The presentation is linked with "metadata frameworks".
  • It is useful to supply consortium members with read aheads and watch aheads on metadata to prepare the first EERAdata workshop. The workshop starts applications and discussions in the use cases break out sessions (and bringing insights back to the plenary), using selected databases.

FAIR Guiding Principles

This table shows the FAIR guiding principles described by Wilkinson et al., 2016.
To be Findable
  • F1. (meta)data are assigned a globally unique and persistent identifier
  • F2. data are described with rich metadata (defined by R1 below)
  • F3. metadata clearly and explicitly include the identifier of the data it describes
  • F4. (meta)data are registered or indexed in a searchable resource
To be Accessible
  • A1. (meta)data are retrievable by their identifier using a standardized communications protocol
    • A1.1 the protocol is open, free, and universally implementable
    • A1.2 the protocol allows for an authentication and authorization procedure, where necessary
  • A2. metadata are accessible, even when the data are no longer available
To be Interoperable
  • I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
  • I2. (meta)data use vocabularies that follow FAIR principles
  • I3. (meta)data include qualified references to other (meta)data
To be Reusable
  • R1. meta(data) are richly described with a plurality of accurate and relevant attributes
  • R1.1. (meta)data are released with a clear and accessible data usage license
  • R1.2. (meta)data are associated with detailed provenance
  • R1.3. (meta)data meet domain-relevant community standards

Identified gaps after Workshop 1 (02/06/2020 – 04/06/2020)

This table shows a summary of the specific issues that were identified in Workshop 1. The aim was to categorise different issues to get a better understanding of how to tackle these challenges.
FAIR/O Specific FAIR/O Gaps Gaps for energy domain Use case specific gaps Consequences for researchers
F F2 Metadata scope Different fields require different metadata (potentially very specific) UC3: lack of additional metadata for applications of materials Data are less useful for the specific field
F F1/F3 Identifiers
  • Missing identifiers on websites
  • Identifier not in downloaded data files
Makes research more difficult.
I I2 Taxonomy/ontology/common vocabulary and language issues
  • Lack of standardisation
  • Heterogeneous data makes standardisation hard
  • No vocabulary documentation on websites
  • Words used for same term in other languages may differ
  • Databases in other languages than English
Research costs more time
I I3 References to other (meta)data
  • No linking to source documents and related publications (for contextual knowledge)
  • Possible need for links to other fields
UC3: link between microscopic and macroscopic materials (e.g., turbine blades)
  • Data cannot be connected to the source
  • Makes research more difficult.
R R1.1 Licensing
  • No licenses available may mean the data is not reusable for the researcher
  • Licenses not clear and accessible
  • Obtaining licenses may result in more effort and costs
Data potentially not reusable
R R1.2 Reliability and provenance of data When the data is collected from different and high number of sources, its reliability decreases Data potentially not reusable
O Privacy concerns and expected disadvantages Not publishing data due to privacy concerns (sensitive data) UC2: In case of distribution network data this is relevant Data not accessible
Other Conducting FAIR assessments
  • No qualitative assessment of the data itself (which may be limited)
  • Discrepancies between results conducted by humans versus machines
  • Sometimes not even DC standards are met
  • Metadata is not updated
  • Lacking encryption of websites (https)
  • Problems assessing whether metadata will be available after data is unavailable
  • Interface design/layout may be unclear, incomplete or not intuitive for humans
  • Authentication details (user registration login / good or bad, clarify)
  • UC1 lack of data availability for time-series
  • Assessment is uncertain (human assessment may need more clarification and understanding)
  • Makes research more time-intensive

ARDC Options

The following table shows all options for each question of the self-assessment tool provided by the Australian Research Data Commons (ARDC). The tool's questions are in accordance with the publication by Wilkinson et al., 2016 .


Findable Accessible Interoperable Reusable
F1. (meta)data are assigned a globally unique and persistent identifier F2. data are described with rich metadata (defined by R1 below) F3. metadata clearly and explicitly include the identifier of the data it describes F4. (meta)data are registered or indexed in a searchable resource A1. (meta)data are retrievable by their identifier using a standardized communications protocol A1.1 the protocol is open, free, and universally implementable and A1.2 the protocol allows for an authentication and authorization procedure, where necessary A2. metadata are accessible, even when the data are no longer available I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (meta)data use vocabularies that follow FAIR principles I3. (meta)data include qualified references to other (meta)data R1.1. (meta)data are released with a clear and accessible data usage license R1.2. (meta)data are associated with detailed provenance R1.3. (meta)data meet domain-relevant community standards
Does the dataset have any identifiers assigned? Is the dataset identifier included in all metadata records/files describing the data? How is the data described with metadata? What type of repository or registry is the metadata record in? How accessible is the data? Is the data available online without requiring specialised protocols or tools once access has been approved? Will the metadata record be available even if the data is no longer available? What (file) format(s) is the data available in? What best describes the types of vocabularies/ontologies/tagging schemas used to define the data elements? How is the metadata linked to other data and metadata (to enhance context and clearly indicate relationships)? Which of the following best describes the license/usage rights attached to the data? How much provenance information has been captured to facilitate data reuse?
Globally unique, citable and persistant (e.g. DOI, PURL, ARK or Handle) Yes Comprehensively (see suggestion) using a recognised, formal machine-readable metadata schema Data is in one place but discoverable through several registries Publicly accessible Standard web service API (e.g. OGC) Yes In a structured, open standard, machine-readable format Standardised open and universal using resolvable global identifiers linking to explainations Meadata is represented in a machine readable format, e.g. in a linked data format such as Resource Description Framework (RDF) Standard machine-readable license (e.g. Creative Commons) Fully recorded in a machine-readable format
Web adress (URL) No Comprehensively, but in a text-based, non-standard format Generalist public repository Fully accessible to person who meet explicitly stated conditions, e.g. ethics approval for sensitive data Non-standard web service (e.g. OpenAPI/Swagger/informal API) No In a structured, open standard, non-machine-readable format Standardised vocabularies/ontologies/schema without global identifiers The metadata record includes URI links to related metadata, data and definitions Standard text based license Fully recorded in a text format
Local identifier Brief title and description Domain-specific repository A de-identified / modified subset of the data is publicly accessible File download from online location Unsure Mostly in a proprietary format No standards have been applied in the description of data elements There are no links to other metadata Non-standard machine-readably license (clearly indicating under what conditions the data may be reused) Partially recorded
No identifier The data is not described Local institutional repository Embaged access after a specific date By individual arrangement Data elements not described Non-standard text-based license No provenance information is recorded
The data is not described in any repository Unspecified conditional access e.g. contact the data custodian for access No access to data No license
Access to metadata only
No access to data or metadata


Dublin Core

The DCMI Metadata Terms lists the current set of the Dublin Core vocabulary. Source: Dublin Core Metadata Initiative
1 abstract 11 contributor 21 extent 31 isReplacedBy 41 publisher 51 tableOfContents
2 accessRights 12 coverage 22 format 32 isRequiredBy 42 references 52 temporal
3 accrualMethod 13 created 23 hasFormat 33 issued 43 relation 53 title
4 accrualPeriodicity 14 creator 24 hasPart 34 isVersionOf 44 replaces 54 type
5 accrualPolicy 15 date 25 hasVersion 35 language 45 requires 55 valid
6 alternative 16 dateAccepted 26 identifier 36 license 46 rights
7 audience 17 dateCopyrighted 27 instructionalMethod 37 mediator 47 rightsHolder
8 available 18 dateSubmitted 28 isFormatOf 38 medium 48 source
9 bibliographicCitation 19 description 29 isPartOf 39 modified 49 spatial
10 conformsTo 20 educationLevel 30 isReferencedBy 40 provenance 50 subject


Metadata Category Types according to NISO

There are three main types of metadata:

  • Descriptive metadata describes a resource for purposes such as discovery and identification. It can include elements such as title, abstract, author, and keywords.
  • Structural metadata indicates how compound objects are put together, for example, how pages are ordered to form chapters.
  • Administrative metadata provides information to help manage a resource, such as when and how it was created, file type and other technical information, and who can access it. There are several subsets of administrative data; two that sometimes are listed as separate metadata types are:
    • Rights management meta-data, which deals with intellectual property rights,and
    • Preservation metadata, which contains information needed to archive and preserve a resource.


Simple Dublin Core Elements. 15 DC elements with their (shortened) official definitions and examples.
DC element name DC definition (DCMI) Example (Energy Domain) Category (determined with the aid of NISO)
Title A name given to the resource Outdoor monitoring of a hybrid micro-CPV solar panel with integrated micro-tracking and diffuse capture Descriptive
Subject The topic of the resource concentrator photovoltaics; CPV; rooftop photovoltaics; integrated tracking Descriptive
Description An account of the resource Dataset from the outdoor characterization of a B Series module from Insolight at the rooftop of the Instituto de Energía Solar - Universidad Politécnica de Madrid. …. Descriptive
Creator An entity primarily responsible for making the resource Stephen Askins; Gaël Nardin Descriptive
Publisher An entity responsible for making the resource available Stephen Askins Descriptive
Contributor An entity responsible for making contributions to the resource Stephen Askins Descriptive
Date A point or period of time associated with an event in the lifecycle of the resource 2019-07-23; Date will be associated with the creation or availability of the resource. Administrative
Type The nature or genre of the resource info:eu-repo/semantics/other; dataset Descriptive
Format The file format, physical medium, or dimensions of the resource image Structural
Identifier An unambiguous reference to the resource within a given context https://zenodo.org/record/3346823; 10.5281/zenodo.3346823; oai:zenodo.org:3346823 Descriptive
Source A related resource from which the described resource is derived RC607.A26W574 1996 [where "RC607.A26W574 1996" is the call number of the print version of the resource, from which the present version was scanned] Descriptive
Language A language of the resource eng Descriptive
Relation A related resource info:eu-repo/grantAgreement/EC/H2020/787289/ Descriptive
Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant 1995-1996; Madrid, Spain Descriptive
Rights Information about rights held in and over the resource info:eu-repo/semantics/openAccess; https://creativecommons.org/licenses/by/4.0/legalcode Administrative



Non-DC elements
Non-DC element name Definition Energy domain interpretation Example Category
Number of users Is there any information on the number of accesses or users Impact/Exploitation
Number of scientific publications where data is cited/used Is there any information on the number of citations/uses Impact/Exploitation
Curation activities (is the versioning ongoing) Update, maintainance Impact/Exploitation


Attempting to put a value on Impact/Exploitation:

  • ENTSO-E: Found 172 results in Advanced Search (ALL) in Web of Science (WoSc) (16/06/2020). Citations of all these search result add up to 714. This however does not mean, that all search results really explicitly used data from ENTSO-E. Some (for sure, for some were found) only mentioned it saying they adoped workflow etc. from the site.
  • SMARD: Found 82 results in Advanced Search (ALL=(SMARD)) in Web of Science (WoSc) (16/06/2020). However: SMARD is also an acronym for Spinal muscular atrophy with respiratory distress (SMARD). This somewhat complicates results and needs some further discussion. All 82 search results accumumlated 2359 citations themselves.


Additional Elements for Energy Domain (Proposal from August)
Date of availability Since wenn is the database available
Information on the number of user (if yes add the number otherwise no)
Number of scientific publications where data is cited/mentioned Check "web of science"
Curation activities Is there versioning and on-going development