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title: 'CHALLENGES:'

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DATA ECONOMY CHALLENGES - an outline 
https://hackernoon.com/the-fundamental-problem-of-the-data-economy-nobody-is-talking-about-dfcaa31546c1
- the data economy in the EU alone had a value €300 billion in 2016 and is projected to more than double by 2020 reaching €739 billion [European Commission, source]
- Globally, it is estimated that better access to data can help unlock at least $3–5 trillion in global economic value [McKinsey] — that represents an increase of 2–5% of the gross world product!
# CHALLENGES: 
## Most data exists in unrefined (or unstructured) form and it is non-trivial to convert it into structured data, the format needed for use in software.

## Data owners use incompatible data models to structure their data which is kept in isolated silos although often sought-after by others.

## No one has figured out how to price and exchange data efficiently yet. 

!!! The issue with data is that creating an open marketplace for it presents a unique set of challenges as it is an intangible non-rival asset unlike virtually all things which are commercially traded today.
Once data has been acquired it can be shared with another party for free which creates a paradox in the traditional scarcity-based methods for pricing resources. 

the DATA MARKETPLACE PARADIGM allows for:

! Crowdsourcing: by making self-serve data selling a reality, they provide the solution to move away from inaccurate/expensive single-source data.
! Aligned incentives: data owners/collectors directly benefit from keeping data in structured form and making it available to others.
! Standardization: by design, a marketplace defines a common data model and interface for buyers and sellers to exchange data.
! Fairness: instead of a having a central authority pricing data, providers can set their own prices while consumers can choose who they buy from. 

THREE KEY QUESTONS: 
- data assetization 
- data owenership 
- data monetization 

OCEAN PROTOCOL's in-White paper listed challenges:

● How do we make data available for use by AI, without losing control of the data (data
escapes)? More generally, how do we resolve the tension between wanting more data for better AI models, with the individual right to privacy?

● How do we incentivize putting data in the commons? This is actually a re-statement of the
classic paradox “information wants to be free, and expensive.” The physics of bits make it
nearly free to copy and spread. Yet the right information in the right place changes your life.
Can we address this? Can it reward relevant data over spam?

● How can the system not only self-sustain but actually improve over the decades, without
guidance by a centralized actor?

● How do we spread the benefits and control of this ecosystem?