Questions About Token Collaboratives

[jlwaugh]

Adapted from Stefaan G. Verhulst's blog post about "Data Collaboratives"

From a research perspective, the following questions need to be addressed more systematically if we are to further sustainable growth and quality development of impactful token collaboratives:

What different types of token sharing exist, and what are the pros and cons of each type?

What kind of token collaborative is better suited for what kind of token use or demand?

What sorts of incentives and value propositions lead businesses and nonprofits to decide to share their assets?

What factors must token owners weigh in making the decision to share?

What are the risks of sharing tokens compared to the benefits, and how should token providers mitigate these risks?

In particular, what are the risks to privacy and of unauthorized disclosures, and what specific steps — technical and otherwise — can be taken to minimize those risks?

What governance frameworks are needed to leverage the potential and mitigate the risks of token collaboratives?

What sorts of token sharing solutions are best suited to maximize the public value of private assets?

What are the respective roles — the relative benefits and disadvantages — of each mechanism for token sharing?

[jlwaugh]

© 2020 MIT Sloan Center for Information Systems Research

[jlwaugh]

Token Collaboratives

making, sharing and/or using crypto for a good purpose

Data => Token(s)

Token Sharing

S1 - Type of Token

tokens for natural persons, legal persons, or natural phenomena

Characteristic of natural persons is further divided into:

1. consumer tokens – created or “minted” about people’s activities without their knowledge
2. user-generated tokens – created and shared by users intentionally / explicitly
3. volunteer tokens – created, shared, and used on behalf of volunteers

S2 - Content of Token

• images
• characters
• numbers
• transactions*
• behavior**
• locations
• nature
• meta

*Tokenized transaction data concerns people’s activities in a commercial setting as a customer.

**Tokenized behavioral data, on the other hand, concerns people’s actions in a non-commercial situation.

S3 - Administrative Level Associated with Token

specific or not?

S4 - Diversity of Token Providers

• one provider
• several providers from the same industry
• several providers from different industries

S5 - Facilitation

• self-facilitated (direct contact with the user without an intermediary)
• intermediary with token-related functions (an intermediary may pre-process tokens or provide a technology solution for sharing)
• intermediary with organizational functions (an intermediary may play a coordinating role ensuring participation)

S6 - Degree of Access to Token

• real-time direct access to creating tokens
• direct access to exchanging tokens
• access to modified or enriched tokens (derivatives)
• access to the outcomes of processed tokens
• free tokens, openly shared

Token Usage

U1 - Target User Group

• academic
• commercial
• governmental
• non-profit
• citizens

U2 - User Selection

• agreement basis (e.g. users of the token selected based on partnership agreements with their respective institutions)
• application basis (e.g. users of the token selected based on individual applications)
• open (e.g. not requiring any specific selection procedure)

U3 - Research or Policy Problem

• specified, e.g. by requesting a research proposal
• unspecified, e.g. by sharing token for any type of innovative usage

U4 - Incentive for Token Usage

• tangible (e.g. monetary reward)
• intangible (e.g. to break new ground in science)

U5 - Continuity of Collaboration

• on demand (e.g. token shared when it is requested)
• event-based (e.g. token shared in the framework of a competition or other event)
• continuous (e.g. token shared continuously as it becomes available)

U6 - Outcome

• policy intervention
• token science and engineering
• token-driven innovation

Policy intervention is further divided into sub-characteristics:

1. prediction and alerts
2. needs-based planning
3. capacity building
4. monitoring

U7 - Collaboration Among Token Users

• one user
• self-selected analysis by several users
• collaborative analysis by several users

U8 - Purpose of Use

• primary (i.e. token is used for the purpose for which it was created)
• secondary (i.e. token is used for the purpose which is similar to the one for which it was created)
• tertiary (i.e. token is used for a different purpose than for which it was created)
• end use (i.e. token is processed and the result is used by end users)

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Data Collaboratives as a New Frontier of Cross-Sector Partnerships in the Age of Open Data: Taxonomy Development

"Our taxonomy scratched the surface of this emerging ecosystem, and future research can provide more understanding with regard to a number of issues. These include, but are not limited to, impact of [token] collaboratives, influential factors, incentives for sharing, governance processes, risk mitigation strategies, and supply-demand matching infrastructures."
-- Iryna Susha, Marijn Janssen, and Stefaan Verhulst