Data as oil, infrastructure or asset? Three metaphors of data as economic value
| Pages | 28-43 |
| Date | 04 November 2019 |
| Published date | 04 November 2019 |
| DOI | https://doi.org/10.1108/JICES-04-2019-0044 |
| Author | Jan Michael Nolin |
| Subject Matter | Information & knowledge management |
Data as oil, infrastructure or
asset? Three metaphors of data as
economic value
Jan Michael Nolin
Swedish school of Library and Information Science,
University of Borås, Borås, Sweden
Abstract
Purpose –Principled discussionson the economic value of data are frequentlypursued through metaphors.
This study aims to explore three influentialmetaphors for talking about the economic value of data: data are
the new oil, dataas infrastructure and data as an asset.
Design/methodology/approach –With the help of conceptual metaphor theory, various meanings
surrounding the three metaphorsare explored. Meanings clarified or hidden through various metaphors are
identified.Specific emphasis is placed on the economic value of ownershipof data.
Findings –In discussionson data as economic resource, the three differentmetaphors are used for separate
purposes. The most used metaphor,data are the new oil, communicates that ownership of data couldlead to
great wealth. However, withdata as infrastructure data have no intrinsic value. Therefore, profits generated
from data resources belong to those processingthe data, not those owning it. The data as an asset metaphor
can be used to convinceorganizational leadership that they owndata of great value.
Originality/value –This is the first scholarly investigationof metaphors communicating economic value
of data. More studiesin this area appear urgent, given the power of such metaphors, as well as the increasing
importanceof data in economics.
Keywords Metaphors, Behavioral surplus, Data as asset, Data as economic value,
Data as infrastructure, Data are the new oil
Paper type Research paper
Introduction
Is there an economic value in owning data? Shouldpeople be reimbursed when they provide
data for purposes of data-driveninnovation? Should the data economy only yield profits for
those who process data, not for thoseowning it? Those attempting to articulate the economic
value of data have found that data are a slippery and difficult concept. When closely
inspected, multitudes ofimplicit meanings emerge. This means that an exceptionally vague
concept is becoming increasingly vital for policy discussions on “digital economy,”“data
economy”and “data market”(EuropeanCommission, 2017).
Many have taken data for granted as an easily grasped, almost intuitive notion.
Increasingly, such simplistic approaches appear unsustainable as data now appear in
discussions on financial investments. The current article isolates one crucial aspect:
articulation of data as of economic value through metaphors. A distinction will be made
regarding the differentvalues of data for research, computing and economy.
In situations where people are forced to deal with abstract notions, they often turn to
metaphors (Lakoff and Johnson, 2008). Three influential metaphors are focused in this
article: “data as the new oil”(or DINO; Palmer, 2006), “data as infrastructure”(or DIN;
OECD, 2015) and “data as an asset”(or DAS; Khatri and Brown, 2010).DINO,DIN and DAS
JICES
18,1
28
Received10 April 2019
Revised20 August 2019
Accepted16 September 2019
Journalof Information,
Communicationand Ethics in
Society
Vol.18 No. 1, 2020
pp. 28-43
© Emerald Publishing Limited
1477-996X
DOI 10.1108/JICES-04-2019-0044
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1477-996X.htm
are successful but contested, and quite different, attempts at talking about the economic
value of data.
There have been several previous reflectionson metaphoric use of data in contemporary
discussions. Markham (2013) discusses reductionist metaphors of human experiences as
data. Nafus (2016) notes a variety of metaphors allowing human attributes for data. Of
particular interest has been the use of big data as a metaphor, focusing on a wide range
of metaphors. Awati and Shum (2017) identify metaphors of big data as articulating issues
of surveillance, food, resource, space, industry and liquids. Similarly, Puschmann and
Burgess (2014) focus on two contrasting metaphors of big data: as a force of nature to be
controlled or as nourishmentto be consumed.
The next section suppliesa background to data as unregulated, i.e. as a resource that has
neither been targeted by governments nor by standard-setting licensing systems such as
have been the case for open content (Creative Commons)and open software (General Public
License). After presentation of method, three different ways of talking about data as a
resource will be presented. Following this, a conceptual metaphor theory (Lakoff and
Johnson, 2008) is introducedas an analytical approach to the three different metaphors. The
main part of the paper focuses scrutiny of the three metaphors, what becomes highlighted
and hidden. The concludingdiscussion is explicitly concernedwith the issue of ownership of
data.
Data as unregulated resource
The current article focuses on metaphors in the area of data as a resource. Implicitly or
explicitly, metaphors about data as a resource serveto clarify economic value. If data are a
resource for business ventures, there are basic legal and commercial issues regarding the
economic value of data. The conventional business procedure is that resources required for
production of goods are bought. Means of production and raw material are thereafter
processed into something of greater value, which can be sold with a profit. However, in the
data economy, the raw resource hasbeen taken for granted to be mostly free for commercial
exploitation.
In recent years, there has been a rich critical discussion on data as a taken-for-granted
freely availableresource from perspectives such as digital labor (Fuchs,2015), reinvention of
capitalism (Mayer-Schönberger and Ramge, 2018), platform society (van Dijck et al.,2018)
and surveillance capitalism (Zuboff, 2019). The concept of behavioral surplus has been
suggested by Zuboff (2019) as a way to understand how companies such as Google and
Facebook have extracted valuefrom various traces of online activities, with the explicit aim
of improving services to users. However, the extracted data have additionalvalue to that of
improving on services. Behavioral surplus has, therefore, been used to create highly
profitable applicationsin a variety of markets.
Data are not the only “free”resource that has developed within the digital economy.
Rather, three distinct “open”categories can be identified: data, content and code (Nolin,
2018). In the late 1990s and early 2000s, open content became regulatedthrough the Creative
Commons license system and opensoftware through a variety of licensing systems such as
the Open Source License and GeneralPublic License. These systems, put in place by strong
transparency movements rather than governments, created frameworks for understanding
authorship, ownership,procedures for reuse and possible commercial exploitation.However,
open data remain unregulatedand issues of ownership unsettled. By implication, this means
that data as a raw resourcehave not been seen as having any economic value. Zuboff (2019)
points to this lack of acknowledgment of data as value leading to a major economic shift,
allowing a new form of capitalism to develop. In addition, representatives of “surveillance
Data as
economic
value
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