BoF meeting title
BoF on Data properties as Economic Goods (Remote Access Instructions)
Meeting room: Okavango 2
Collaborative session notes:
Short introduction describing the scope of the group and if any previous activities
The fact that data has a value is commonly recognised. However, data value is different from those associated with the consumable goods. There is a number of initiatives to create data markets and data exchange services.
Existing business model of paid or commercial data(sets) services such as archive are based rather on services subscription fee. Quality of datasets is in many cases assessed by independent certification body or based on peer review by expert. Such model is useful for specific use cases but doesn’t provided consistent model to make data an economic goods and enable data commoditisation.
Interest to make best use of research data resulted in formulation of the FAIR (Findable – Accessible – Interoperable – Reusable) data principles which are widely supported by industry and business.
However emerging data driven technologies and economy facilitate interest to making data a new economic value (data commoditisation) and consequently identification of the new properties of data as economic goods. The following properties are leveraging FAIR data properties and defined as STREAM for industrial and commoditised data
Other properties to be considered and necessary for defining workable business and operational models: nonrival nature of data, data ownership, data quality, measurable use of data, privacy, integrity, and provenance.
The BoF topic was proposed as a result of discussions in ongoing projects and initiatives focused on industry digitalisation and digital skills in which the BoF proposers are involved (such as MATES project, DL4LD project, International Data Spaces Association, others).
Additional links to informative material related to the group
FAIR Data Initiative - https://www.dtls.nl/fair-data/
Industrial Data Space Reference Architecture, Version 2.0 - https://www.internationaldataspaces.org/wp-content/uploads/2018/04/InternationalDataSpacesAssociation_ReferenzArchitecture2.0.pdf
Position paper: Data as Economic Goods: Definitions, Properties, Challenges, Enabling Technologies for Future Data Markets, by Yuri Demchenko, Wouter Los, Cees de Laat,. To appear in ITU Journal: ICT Discoveries, Special Issue “Data for Goods”, December 2018 - http://www.uazone.org/demch/papers/itu2018-2-data-economic-goods-v04.pdf
RDA12 Poster "Bringing Data to Market: Data Properties as economic goods" - http://www.uazone.org/demch/posters/rda12poster29-Data-economic-goods-ma...
DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), DAMA International, July 2017.
1) Gather individuals interested in defining set of properties that are related to data as economical goods
2) compile initial agreed set of data properties and validate currently denoted STREAM properties
3) Identify key actions to further research topics and coordination actions
4) Understand community support in creating a new WG on Data properties as Economic Goods (DEG) (that should be short lived) and find volunteers to serve as chairs for a potential WG
5) Identify set of document to be produced by the prospective WG, in particular STREAM-like properties definition and overview of business models for research data and commoditised data trading and exchange
1. Introduction and BoF goals
2. Overview of existing activities, initiatives and available resources on defining economic value of data and future data markets (Yuri Demchenko, UvA)
2.1. FAIR data principles adoption in industry and business (TBD)
2.2. Industrial Data Spaces model by International Data Spaces Association (TBC, Fraunhoffer ISST, DE)
2.3. Contribution and statements from BoF audience (open list)
3. Discussion of the future market demand and identified STREAM properties
4. Discussion of possible activities and contributors (WG/IG vs information document)
5. Conclusion and next steps forward (in case of community support)
Data producers, data owners, data repositories operators.
RDM and Big Data researchers, data driven projects representatives
Interest and endorsement also received from exisitng RDA IGs and WGs.
No special preparation needed.
Group chair serving as contact person: Yuri Demchenko
Type of meeting: Informative meeting
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