Gap analysis: Difference between revisions

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Added table summarising the identified gaps in WS1
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*The next step is to increase knowledge on IT specific terms, i.e. to understand what the difference is between different '''[https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5404340 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".  
*The next step is to increase knowledge on IT specific terms, i.e. to understand what the difference is between different '''[https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5404340 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 '''[https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 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.
*It is useful to supply consortium members with read aheads and watch aheads on metadata to prepare the '''[https://energydata.onlyoffice.eu/Products/Files/doceditor.aspx?fileid=5296590 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.
= Identified gaps after Workshop 1 (02/06/2020 – 04/06/2020) =
{| class="wikitable"
|+ style="caption-side:bottom; color:#000000;"|''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.''
|-
! General Issue!! Specific Issues!! Results !! Solutions
|-
| Privacy issues and expected disadvantages
||
* Not publishing data due to privacy concerns (sensitive data)
* UC2: In case of distribution network data this is relevant
* Data publishing could lead to potential market disadvantages/competition
* …
|| No data published at all
|| (?)
|-
| 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
|| Explicitly show licenses for different data, actively encourage licensing
|-
| 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
|| (?)
|-
| Metadata range||
* Different field require different metadata (potentially very specific)
* UC3: additional metadata for applications of materials
|| Data are less useful for the specific field
|| (?)
|-
| Linking issues
||
* Missing identifiers on websites
* No linking to source documents and related publications (for contextual knowledge)
* Identifier not in downloaded data files
* Possibly 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.
|| (?)
|-
| Quality of data
||
* No qualitative assessment of the data itself (which may be limited)
* When the data is collected from different and high number of sources, its reliability decreases
* UC1:
** multiplicity and scattered nature of data sources (households, industries, utility companies, municipalities)
** lack of data availability for time-series
|| Makes research more difficult
|| (?)
|-
| Conducting FAIR assessments
||
* 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, uncomplete or not intuitive for humans
* Authentication details (user registration login / good or bad, clarify)
||
* Assessment is uncertain (human assessment may need more clarification and understanding)
* Makes research more time-intensive
|| (?)
|+Food complements
|}
= Potential Databases in connection with SmartCities =
* [https://smartcities-infosystem.eu/ Smart Cities Information System]
* [https://www.eumayors.eu/ Covenant of Mayors Database]
* [https://www.kaggle.com/search?q=energy BigData]

Revision as of 08:51, 15 June 2020


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.


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.
General Issue Specific Issues Results Solutions
Privacy issues and expected disadvantages
  • Not publishing data due to privacy concerns (sensitive data)
  • UC2: In case of distribution network data this is relevant
  • Data publishing could lead to potential market disadvantages/competition
No data published at all (?)
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 Explicitly show licenses for different data, actively encourage licensing
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 (?)
Metadata range
  • Different field require different metadata (potentially very specific)
  • UC3: additional metadata for applications of materials
Data are less useful for the specific field (?)
Linking issues
  • Missing identifiers on websites
  • No linking to source documents and related publications (for contextual knowledge)
  • Identifier not in downloaded data files
  • Possibly 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.
(?)
Quality of data
  • No qualitative assessment of the data itself (which may be limited)
  • When the data is collected from different and high number of sources, its reliability decreases
  • UC1:
    • multiplicity and scattered nature of data sources (households, industries, utility companies, municipalities)
    • lack of data availability for time-series
Makes research more difficult (?)
Conducting FAIR assessments
  • 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, uncomplete or not intuitive for humans
  • Authentication details (user registration login / good or bad, clarify)
  • Assessment is uncertain (human assessment may need more clarification and understanding)
  • Makes research more time-intensive
(?)
Food complements


Potential Databases in connection with SmartCities