VALUE: Progressing the economics of source data

I will discuss briefly here how the fuel of any big data system, source data, can receive the needed attention, from an economic modelling perspective.

Interested readers are referred to:

http://www.amazon.com/Data-Economics-Towards-Market-Places-ebook/dp/B00QD7LMO2

Naturally, big data systems are engineered as Information Technology solutions, with the associated cost engineering, on a project by project basis. My assumption is that as big data becomes pervasive, the re-use of data and sharing across multiple use ranges, will make a lot of sense, and let the suppliers and users benefit from economies of scale and critical mass effects.

QUESTION 1: THE VALUE of data

The first question to ask is about the value: are these data I am using of value? What is the value of the data I have extracted? What would be the value of additional data, and where could I get them?

Economists following in the steps of Adam Smith distinguish two types of value:

• the value of use
• the exchange value

Obviously, a good which you need for a certain purpose, has a use value to you. If you are thirsty, you need water, for instance.

As for the exchange value, this is a good which you can sell, or buy, because it is traded, and comes with a price on a market. For instance cocoa was an asset used as money in Precolombian civilisation of Latin America. The classical example is diamond.

For data, let us give examples in each of these two categories of value:

-Use value

An automated system, supervised from a Control Room (say a train network, an electrical grid, a telecommunication network) uses for its own purpose industrial data. This data has an obvious use value, however the data owners seem to be little keen on releasing such data, even for a price, to third parties. This data use case is perceived to fit under a dominant "value of use" and not any identified "exchange value" yet.

-Exchange value

An entertainment content such as a movie, materialises (virtually :) ) as a file, which is a data-set. It has an exchange value: rights are sold to cinemas, TV channels, and end users, for viewing this content. In package media form (Bluray, DVD), it can be resold even, by consumers.

Naturally there are many more questions regarding "big data economics" and leading "towards data market places". The following book I have published recently on Amazon/Kindle Editions addresses some...

http://www.amazon.com/Data-Economics-Towards-Market-Places-ebook/dp/B00QD7LMO2

Debate on the Economics of Data, at TELECOM PARIS workshop on 12 January 2015

Here is a summary of the lively Debate on the Economics of Data hosted by Telecom Paris university on 12 January:

Industrial data?
Currently industrial data are part of closed systems, and the suppliers and users of such systems are very protective about sharing with third parties.
However, some intents are being made.

Luxury data?
Some data can be seen as Giffen good, where high price is expected and desired as part of the value proposition (luxury car, etc). Some "gem" data exist.
High value financial information is part of this category.
Beyond any open economy, State Security data has a somewhat comparable exclusive status.

Key sectors?
Business intelligence is a very active market for big data solutions already.
Health Care and Care for the ageing population is an other area, where big data solutions could:
-support the people in care
-support the carers
especially in the Ambient Assisted Living framework.

Data management?
This is a key question. In particular ensuring that data owners keep control of multiple, possibly cascaded use.

Big data economics, 

Workshop at Telecom Paris Tech, 

12-1-2015, 

Paris, France

Event
100+ registered attendees
Introduction by Patrick Duvaut, director of research at Telecom Paris-Tech
Presentation by Renaud Di Francesco
Speech by Pierre-Jean Benghozi
Participation of Yves Poilane, director of Telecom Paris-Tech




Presentation summary

The scope of big data, is broader than business intelligence, and extending towards:
-real world to digital, analytics AND decision, feedback to real world
-real time

A change in needed technology portfolio is happening, beyond NoSQL and search technologies, with other technologiues determining success:
-signal processing
-maximum likelihood decision methods
-optimal control
-real time system engineering

The digital economy relies on three pillars, two of which have identified pricing schemes and economic mechanisms:
-software
-network
however, the third one, data, does not always have recognised value, and economic mechanisms.
For instance, what is the price of an electrocardiogramme as usable data? What is the price of my geographic position?

Nevertheless in some sectors and categories, data can have pricing schemes and economic mechanisms:
-content (e.g. movie) industry
-news
-loyalty schemes
-etc...

Starting from these chartered territories of big data, one can start considering adapted economic schemes for new data categories, which are not yet priced and covered by economic schemes.

The software licensing scheme offers a starting framework for data contracts, which cover rights on data.
The enforcement of rights is helped by Digital Right Management systems granting authorised access to the data.
The target for a data economy to work efficiently is the development of data market places, where data collectors, data owners, data users, and data processors, meet as data offer has to meet data demand.
The raw material or commodity market places established for physical goods give a reference framework from which data market places can be derived.
Moreover, in some categories, digital data market places are already in operation. For instance Getty Images buys and sells pictures, which are a special case of data.

DATA economics: risks of pricing to ZERO

Commodities were targets of wars, of many kinds including colonial ones. This was infortunate. Today the economics of commodities is structured into commodity trading and their associated market places.
This was the physical world, and still is...

NOW comes the digital world, and the ubiquitous digital part of any economic activity in any sector...
The new commodity is DATA, or more precisely SOURCE DATA.

Recognise with me that an easy but complete model of the DIGITAL ECONOMY builds on three pillars: software, networks, and data.

https://www.xing.com/communities/posts/digital-economy-how-does-it-work-1009091263

Software is valued, so are Networks, but what about the raw data, the source of sources?
Take the case of consumers using a widely spread digital environment: they want their maps and guidance, their calendars, and written or visual communication anywhere anytime. To get this basic requirement of today's life (digital, partly digital at least) they give away their data, which are a precious input for others to make lots of money with it.
Unrefined oil is not as precious as refined oil from the gas/petrol station, but is oil free? And oil comes from the ground, not from people themselves. So why should DATA be free to those making money with it?

Remember this horrible global economic activity headquartered in Bristol, UK? Free manpower exported to the New World. Shame on mankind to have allowed for it.

Free is and should always be suspect unless it's transparently auditable, as in CBPP (commons based peer production as wikipedia). Otherwise "make it free for me" is at the source of this untransparent integrated economy which ruled Sicily, the birth place of my grandfather, for too long.

In technical terms, set a Lagrange multiplier (price can be seen as one) to zero, and the constraint which could also have revealed opportunities in economic terms, disappears.
Here is a scheme showing how the "give me your data for free" scheme works in the Digital Economy.

https://www.xing.com/communities/groups/big-data-economics-c6b9-1073836

NOW, here is a first intent to see how to price more systematically data, and progress to wards data market places as the physical economy did when it created commodity trading, and their associated market places.
This book has been published last month. It builds on use cases and data categories which have a price and economic schemes, to suggest new ways to address data pricing, using, ecosystems, etc.

http://www.amazon.com/Data-Economics-Towards-Market-Places-ebook/dp/B00QD7LMO2

XING: starting a big data economics group

Big Data Economics: THE BOOK

This book addresses the economics of Big Data, beyond a project by project cost analysis.

The fuel or input of any Big Data system is source data. In many cases of current use of Big Data, excepting Open Data, the data is obtained for one single purpose, and used by a single organisation, because of the likely absence of an open and transparent market where such data can be purchased or sold. Our objective is to analyse the objects, agents, and mechanisms at play for source data within the Big Data context, and give an economic perspective rather than an Information Technology engineering perspective to Big Data.

The nature of data will be discussed, as a good which is digital rather than material, can be replicated at virtually no cost, and is not burnt or consumed in any irreversible way by its being used in a computation.

Requirements for exchange mechanisms of source data, and associated rights of use, will be discussed, with rules for transfer and use, control retention or not by originating owner, privacy and other basic requirements and constraints on data access.

Pricing and contract requirements for categories of data rights will be described, and illustrated on a few examples.