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GEODB
GeoDB Business Memorandum V2.1
Decentralized Peer-to-Peer Data Sharing Ecosystem https://geodb.com
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LEGAL DISCLAIMER
READ CAREFULLY
PLEASE READ THIS ENTIRE SECTION AND DO NOT TAKE ANY
ACTIONS UNTIL YOU FINISH IT. THIS MEMORANDUM IS A SUMMARY
OF GEODB BUSINESS MODEL, TECHNOLOGY, AND BRIEF
INTRODUCTION TO GEODB BUSINESS PRINCIPLES. IF YOU ARE IN
ANY DOUBT AS TO THE ACTIONS YOU SHOULD ACQUIRE GEODB’S
TOKENS, YOU SHOULD CONSULT YOUR LEGAL, FINANCIAL, TAX OR
OTHER PROFESSIONAL ADVISOR(S) AND IMMEDIATELY NAVIGATE
AWAY FROM GEODB’S WEBSITE AND DO NOT BECOME GEODB’S
TOKEN HOLDER.
This presentation and the information provided on this presentation to readers has
been issued by GeoDB Blockchain Limited (”GeoDB"). It has been prepared solely
for informational purposes and should not be construed as an offer to buy or sell or
a solicitation of an offer to buy or sell any security or instrument or any asset or to
participate in any transaction or trading activity. The contents are based upon or
derived from information generally believed to be reliable although no
representation is made that it is accurate or complete and GeoDB accepts no
liability with regard to the reader’s reliance on it. The information contained herein
is a summary of any transaction described and is incomplete and provided for the
convenience of the reader and is subject to change without notice. This
presentation and the information contained herein is not intended to be a source
of advice or credit analysis with respect to the material presented, and the
information does not constitute investment advice. Accordingly, any decision in
connection with funds, instruments or transactions described or mentioned herein
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must be made solely on the information contained in a prospectus and no reliance
is to be placed on any other representations.
The information provided on this presentation regarding services offered by GeoDB
is not directed to any United States person or any person in the United States, any
state thereof, or any of its territories or possessions. Any type of asset or securities
described herein will not be registered under the Securities Act of 1933, as
amended (the "Securities Act"), and may not be offered or sold in the United States
or to US persons unless the securities are registered under the Securities Act, or an
exemption from the registration requirements of the Securities Act is available.
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Prices in any documentation presented are subject to change without notice and
no representation is made that any returns or valuations indicated or mentioned
would be achieved. The transaction documents (offering circulars, investment
management agreements, etc.) override any statement, claim or information in this
material.
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Any reproduction of this presentation, in whole or in part, is prohibited. The
recipient of this document may not release this material to any other person,
except to their advisors and professionals who will be assisting them in evaluating
such assets or securities or funds and for no other purpose and agrees not divulge
any such information to any other party. You are not permitted to publish, transmit,
or otherwise reproduce this presentation or information from this presentation, in
whole or in part, in any format without the express written consent of GeoDB. In
addition, you are not permitted to alter, obscure, or remove any copyright,
trademark or any other notices that are provided to you in connection with the
information.
This presentation and its content is not for distribution to retail clients, as that term
is defined under the Markets in Financial Instruments Directive (2004/39/EC); and
any assets or investments, including derivatives (if any), mentioned in this material
will not be made available by the user to any such retail customer.
Additional information on GeoDB is available upon request.
GEODB Blockchain Limited Geo Data Block Decentralized Data Sharing Ecosystem powered by Distributed Ledger Technologies Business Memorandum Version 2.1 Contact: [email protected] Web: https://GeoDB.com Updated on 15th of January 2020
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TABLE OF CONTENT
1. INTRODUCTION 10
1.1. CURRENT BIG DATA MARKET 11
1.2. WHAT DO WE WANT TO SOLVE? 14
1.3. HOW DO WE WANT TO DO IT? 16
1.4. THE GEODB SOLUTION 16
1.5. THE GEODB ENVIRONMENT 20
2. BACKGROUND 22
2.1. DISTRIBUTED LEDGER TECHNOLOGIES 22
2.1.1. PERMISSIONLESS DLT 22
2.1.2. PERMISSIONED DLT 22
2.2. BIG DATA 22
2.2.1. DATA COLLECTION 23
2.2.2. DATA STORAGE 23
2.2.3. DATA ANALYTICS 23
3. SOLUTION 25
3.1. CREATION OF THE FIRST WORLDWIDE BIG DATA ECOSYSTEM 25
3.2. GEO TOKEN VALUE GENERATION 26
3.3. GEODB BENCHMARKING. PROMOTING THE NATURAL BALANCE 27
3.4. GEODB ACQUISITION PRICING MODEL 31
3.5. REWARD SYSTEM - INCENTIVES 33
4. ARCHITECTURE 36 4.1. DATA VERIFICATION 37
4.1.1. IDENTITIES 39
4.1.2. FACILITATORS 39
4.1.3. CAPTURE 41 4.1.4. PROVISION 43
4.2. DATA ACQUISITION 43
5. TOKEN MODEL 45
5.1. BIG DATA TOKENIZATION 46
5.2. DLT FUNCTION 46
5.3. GEO TOKENS USE 47
5.4. GEO TOKEN SUPPLY & DELIVERY - REWARD SYSTEM 48
5.5. GEO TOKEN ALLOCATION 48
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5.6. GEO TOKEN VALUE CREATION STRATEGIES 49
6. ROAD MAP 51
6.1. USE OF FUNDS 52
7. GROWTH, MASS ADOPTION & PARTNERSHIPS 53
7.1. GROWTH STRATEGY 53
7.2. GEOCASH 55
7.3. GEOSUITE 56
7.4. APPSTORE 57
7.5. ECOSYSTEM PARTNERS 58
7.6. OTHER STRATEGIC USER APPS 59
8. TEAM 63
9. REFERENCES 66
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SUMMARY
“GEODB IS A DLT-BASED DATA SHARING ECOSYSTEM”
Big data is becoming one of the most valuable assets in the world. The
International Data Corporation (IDC) forecasts that worldwide revenues for big data
and business analytics solutions will reach $260 billion in 2022 with a Compound
Annual Growth Rate (CAGR) of 11.9% over the 2017-2022 forecast period [IDC.REV.18].
The big data market will continuously grow throughout the following years as
companies and corporations evolve their internal decision-making procedures into
a data analysis mechanism. Data is turning into the new high demanded tradable
asset between data creators and data buyers.
Personal data is an economic resource that we constantly share in return for
services such as instant messaging or social networks. Some of this data is handed
over consciously, like entering an email address or a telephone number; other data
is captured without us knowing about it, such as social media interactions,
locations, our online behaviour and other forms of digital data exhaust. But the
value comes when different datasets are aggregated, an individual
psycho-demographic profile is created and sold to all sorts of organisations such as
insurance companies, market researchers, consultants, digital services companies,
political organisations, etc. A multi-billion dollar data industry mostly exists to trade
& analyze personal data.
“GEODB AIMS TO COMPLETELY IMPROVE BIG DATA MARKET” Big data analysis corporations have been gaining immense traction in the last
decade, investing huge amounts of money to access and analyze consumer
information in order to improve the development of their clients’ business.
Consumers and users that have been generating all that information have been left
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out from the equation. GeoDB brings them back in the game, allowing them to
gain value of shared data.
GeoDB will build the first worldwide big data sharing ecosystem that enables users
from around the world to gain control, transparency and value from their self
generated data, while data buyers will have an opportunity to purchase verified
data in a transparent, easy and cost effective way.
Users’ data will be uploaded to a solution based on DLT directly by them or through
a third party application. Users will be rewarded with GEO - the GeoDB’s token.
Subsequently, big data buyers will send queries to the generated big data pool in
order to obtain the data paying in GEO tokens.
GEO tokens represent the value that the global market attributes to users’ data
generation, thus valuing data as a digital asset. GEO tokens will allow to buy
specific, customized and filtered worldwide data from a potential network of more
than 5 billion devices that are constantly, day after day, generating extremely
valuable data for data buyers.
“THE TIME HAS COME TO DEMOCRATIZE THE BIG DATA
MONOPOLY”
GeoDB comes to the market at a crucial time. Dozens of studies confirm that big
data will be worth trillions of dollars in the next decade. Decision-making is based
on data analysis, so the potential of a decentralized data market is absolutely huge.
On the other hand, the global decentralized data pool has to be a global, unified
and complete source of data for all levels of buyers, who will not need anymore to
track down thousands of different sources. It‘s a circular, organic, well assembled
and tokenized model in which every player is gaining a huge value.
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“GEODB WILL INITIATE FOCUSING ON LOCATION, ALREADY
BACKED UP BY A NUMBER OF LOCATION COMPANIES AND
MORE THAN 12 MILLION OF USERS” On a proof-of-concept stage, GeoDB has focused initially on location data for the
following reasons:
a) Firstly, it is the most valuable among all private users’ data.
b) Secondly, the team behind GeoDB has years of experience in the location
market, currently applying that expertise in B2C and B2B services, both from
the seller and the buyer point of view.
c) Thirdly, extracting and categorizing location data with current technology is
simple, fast and efficient.
We have already reached an agreement with several tech location companies to
join GeoDB’s ecosystem right from the start, but our plan is to expand and
gradually introduce all kinds of data into our ecosystem in order to create the most
complete and accessible data sharing ecosystem in the market.
The GeoDB’s technical roadmap can be checked in GeoDB’s technical paper.
GeoDB’s strategic partnerships with location companies mentioned above will
bring a pipeline of digital projects to be connected into our ecosystem, allowing a
big volume of end users to start uploading valuable data into the data pool, and at
the same time initiating the allocation process of GEO tokens. We expect more
than 30 million connected users shortly after launching GeoDB main net in 2020.
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1. INTRODUCTION
“THE WORLD NEEDS GEODB”
There are 7 billion people on the planet, and each one of us is totally different from
the rest. Special. Unique. We all have our own characteristics, our own way of doing
things, of going to places, of making decisions, of thinking.
Nowadays, your “you” has a digital projection. And your digital “you” is constantly
being measured, tracked down, transformed into numbers and sold out to the
highest bidder. All of us are losing control of ourselves in the digital era, and what is
worse, without our consent. We want YOU to be the only captain of your own ship.
You need to decide what exactly is being done with all the data that makes you
being you.
“YOU ARE YOUR ONLY RULER”
Firstly, if you decide to share your distinctive statistics, you should be rewarded for
it. Let us stop only third parties earning money from your own inputs.
Secondly, let us allow access to that data to almost anyone and not just giving it in
the hands of the most powerful. But always with privacy, control and transparency,
changing current procedures.
Thirdly, DLT allows to secure your data and regulate access to it in the most reliable
way. The data buyer will get access to your behavior characteristics, but not to your
personal information.
And finally, let us all put our own distinguishing data together and help each other
understand how we all operate, as one species, in order to make the place where
we live BETTER.
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We strongly believe that we can all benefit from analysing who we are and what we
do in an aggregate way. GeoDB is here to democratise the circulation of data, make
it transparent, secure and accessible by anyone, for the benefit of everyone.
1.1. CURRENT BIG DATA MARKET
Big data originally emerged as a term to describe datasets whose size is beyond
the ability of traditional databases to capture, store, manage and analyze. However,
the scope of the term has significantly expanded over the years. Big data not only
refers to data itself but also to a set of technologies to capture, store, manage and
analyze large and variable collections of data. The term is often used to refer to
predictive analytics or other methods of extracting value from data.
Despite challenges relating to privacy concerns and organizational resistance, big
data investments continue to gain momentum throughout the globe. Estimations
say that big data investments will account for billions in 2019 alone.
All data shows a clear and steady growth that will convert this market into one of
the most valuable activities throughout the globe. GeoDB intends to become an
important player in the following years, delivering accessibility, commodity and
concentration to many other participants. The all-in-one solution for data buyers
and data providers. GeoDB seeks to solve the challenges that are complicating
market activity such as no direct user compensation, privacy concerns, high costs,
trust of data sources and inefficient buying processes. A data sharing environment
with no owners in which the community will help to expand and improve
capabilities.
Let us see some figures to assess the size and behaviour of the market.
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Chart 1. Revenues for the global big data industry
Image 1. Current Big Data Market
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All of this data shows that company decision making procedures will rely mainly on
data analytics in the next decade. That is why there is a huge opportunity for the
construction of a decentralized big data marketplace, while the current market is
inefficient with numberless intermediaries.
Some estimates indicate that only 5-10% of data is being exploited. And there is a
demand, so we just have to make data accessible. DLT and tradedable tokens that
represent big data value, can become a perfect solution to overcome the
challenges that arise nowadays in the market.
Type of data used by big data solutions worldwide
The statistics show the various types of data deployed in big data solutions
worldwide, according to a survey of big data-related executives conducted by
Forbes Insight. As of that survey, 56 percent of big data projects were using
location-based data.
Chart 2. Types of data employed in big data solutions worldwide
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1.2. WHAT DO WE WANT TO SOLVE?
The match between the big data market and DLT capabilities can solve several
issues that arise when you analyze how the big data market works nowadays. We
can resume these challenges in the following points:
DATA PROVIDER ISSUES DATA CONSUMER ISSUES
1.- No direct user compensation 1.- High Costs due to intermediaries
2.- Data privacy concerns 2.- Lack of trust to Data sources
3.- Long & inefficient buying processes
DLT in combination with big data tools allows us to create a great solution that
reconciles everyone’s needs, but this is a very delicate relationship, in which exists
biases induced by traditional competitors that force us to model carefully our
environment to avoid imbalances and help participants to unlearn old concepts.
According to the theory of the balance of nature all agents depend on each other.
The predators feed on herbivores, herbivores feed on vegetables, and these grow
thanks to the nutrients left by all the previous ones upon depth. And the above
taught us an extremely important life lesson, disregarding the needs of any agent
can cause the system to collapse.
For us, a solution like GeoDB must be modeled trying to balance the needs of the
agents that interact with it, and for us, there are three clear agents, i) providers, ii)
consumers and iii) developers. Each of the above has different needs, some of
which are reflected below.
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PROVIDERS CONSUMERS DEVELOPERS
compensation trust incentives
simplicity equitativity demand
privacity adaptation freedom
autonomy integration safeguard
Table 1. Needs of GeoDB’s ecosystem agents to be solved
Data providers such as users, provide the fuel to the system, which is data, and they
need compensation to do that, they need to provide it privately and autonomously,
using simple mechanisms.
Data consumers such as data scientists of various companies, consume this
information and they need an equitable price system, they need certainty of the
veracity of the information acquired and they need mechanisms to integrate this
information with their own tools by adapting them if it is necessary.
And the ecosystem developers such as facilitators or apps using the SDK and
GeoDB appStore application creators need incentives to do that, a demand of tools
to satisfy their needs, a freedom to create any tool compatible with the rest of the
tools in the system and need of a strong protection to prevent improper use of their
developments.
We want to solve multiple problems existing in the current big data market and to
do this we rely on DLT. And we have modeled it as a balanced system with the aim
of creating a solution that will last in the long term.
We propose a simple solution for users that will compensate them for their
information and a transparent, adaptable solution for consumers that will allow
them to expand their analytics to a stage beyond the actual and under equal
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conditions. And we propose this solution in an environment that seeks to reward its
community to foster the creation of bridges between the two previous agents.
1.3. HOW DO WE WANT TO DO IT?
Today we live in an extremely complex and heterogeneous world. Millions of people
move for their daily activities and in this process they interact continuously with
their environment, generating huge amounts of data through all kinds of devices.
On the other hand, artificial intelligence algorithms are avid for information to
understand human behaviour & their environment; or research projects that need
large volumes of reliable data to discover the knowledge hidden behind the
numbers. GeoDB is the intersection of both sides. An ecosystem in which users will
have control of their information and at the same time will obtain an economic
benefit from it, collaterally helping to the development of society and science, while
data buyers will have an easy up to date access to data for a fair price.
DLT makes it possible to build this entirely new paradigm. This technology allows
us to store data in an immutable and verificable way to ensure that it has not been
manipulated and, what is more important, this immutable storage is guaranteed by
a decentralized system that makes it resilient to external interference.
1.4. THE GEODB SOLUTION
In GeoDB we want to bring fair rewarding to the users while providing easy access
not only to big data market players or corporations, but also to SME businesses,
who right now need to go under the arbitrary pricing of those companies who are
incontrol of most of the current data economy.
Our solution will undergo two main stages:
1. In the first stage the ecosystem will be dependent on a trusted federation,
operating under hybrid DLT solutions to provide transparency and
accountability.
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2. In the second stage, as the ecosystem grows, further efforts will be done to
transition to a more decentralized model.
This process can prove to be delicate, as the second stage depends on the correct
execution of the first. Solid foundations must be laid out to ensure that the
transition is doable. To achieve this, GeoDB has done a careful selection of the
needed technologies in a modular way, which means that in the future, any of
these can be substituted on better suited technologies.
In the following figure, a summarized view of the technology stacks and the way
we intend to use them is shown.
Chart 3. Blockchain solutions to be used in GeoDB’s ecosystem
The essential key for the ecosystem at the first stage is the federation. The
federation will be in charge of bootstrapping the ecosystem. First, it will act as a
gatekeeper for the user’s data, allowing the rewards and validating honest
behaviours.
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The federation will receive user data and store it to be available upon request to
buyers in exchange for GEO tokens. A user will be able to forward his information to
a GeoDB federation node. In exchange, the federation member will share and store
the provided information, signaling a reward to be given to the user. The honest
behaviour of the federation members will be observed using permissioned DLT
technologies. One example of such technology is HyperLedger Fabric, which allows
to privately reach consensus between a limited amount of self-recognized
organizations (the companies that will compose this federation), allowing to
automate and enforce B2B processes. Another essential technology will be
Ethereum platform, which will be used as the financial layer that will ensure each
member of the federation commits to their duty, through a DAO where the
members have a stake that could be taken away as compensation for malicious or
negligent activities.
Periodically, all the rewards generated will be compounded in a single block of
information, which will be uploaded in consensus with all the federation members,
by one elected member, to the Ethereum blockchain. This way, two things will be
achieved:
1. Anchor the federation internal processes to Ethereum, where auditing and
accountability can be performed easily.
2. Reduce the operational costs of uploading information to the public DLT for
all the members of the federation, both in the reward and governance
processes.
These reward blocks can then later be referenced to validate the actual emission of
the rewards.
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Chart 4. The reward mechanism through GeoDB Federation
Moreover, the user will be empowered with the ownership of his information. By
attaching specific metadata to what the user is providing to the federation, he can
signal additional parameters about the provided information that can be used later
during the purchase process. The compliance with the user preferences will be
observed between the federation members.
Once GeoDB accumulates a certain amount of user data, buyers will get genuinely
interested in purchasing the stored information. The federation will observe that
any and all purchases are done by means of the GEO token, for their own interest.
At that point, the buyers will need to first acquire GEO tokens through crypto
exchanges, users directly or GeoDB’s internal exchange tools.
As more buyers will get attracted to the platform, it will spark the beginning of an
organic cycle where the user uploads data, takes a reward in GEO tokens, and
resells those tokens to potential data buyers or other crypto holders at a market
price through crypto exchanges, establishing a fair market price for the user data,
and at the same time, protecting the token value (and the data associated with it)
by means of a federation.
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1.5. THE GEODB ENVIRONMENT
Essentially, GeoDB is a solution for the storage and commercialization of data
under a big data paradigm using DLT. We address several aspects that are often
excluded in other solutions: immutable storage of information, reward users for
providing their data, verified data and incentives adjusted to the quality of the
information.
But the big data field is huge and users’ needs are diverse. Any entity focused on
big data needs to use a wide range of tools, data sources and analysis techniques.
Therefore, we take one more step to propose a complete environment that
facilitates big data ETL and the integration of customized features, because only
then we will be able to meet the needs of real users.
Initially, our environment includes several solutions:
geoCash
An app for Android and iOS users that allows to:
● Generate and manage a wallet to use GEOs.
● Visualize the historical transactions associated with the wallet.
● Transfer smartphone information and be rewarded in GEOs.
appStore
A marketplace of data analytics & visualisation tools supported by geoSuite and
integrated in it in which transactions are carried out in GEOs.
● Developers can provide software to visualize and/or analyze datasets
purchased in GeoDB.
● Developers can provide geoSuite extensions to enable new features.
● Dataset acquirers can find tools to enhance the utility of purchased datasets.
geoSuite
A user suite that allows to:
● Generate and manage a wallet to use GEOs.
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● Generate and manage user accounts.
● Develop and deploy features.
● Buy and sell features and libraries in appStore.
● Provide capabilities to GeoDB infrastructure:
○ Install and manage features to provide capabilities to GeoDB solution.
○ Be rewarded in GEOs for providing these capabilities.
○ Real-time access to the state of the user’s nodes and GeoDB
infrastructure.
● Carry out big data analytics:
○ Install and manage features.
○ Buy datasets using GEOs.
○ Use algorithms and third-party libraries in several languages and
environments.
More applications are expected to appear and will be updated in the next versions
of the White Paper and on GeoDB's website.
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2. BACKGROUND
2.1. DISTRIBUTED LEDGER TECHNOLOGIES
There are several platforms in the DLT universe that GeoDB could use to reach its
goal. In this section, a brief comparative of the main platforms analyzed by our
team in the last months is included sorted by permission type.
2.1.1. PERMISSIONLESS DLT
Permissionless DLT are those in which anyone can join the blockchain network.
This means that anyone who joins the network can read, write or participate in it
and anyone can access the information stored in the chain. This type of blockchain
is used to bring transparency to the process.
2.1.2. PERMISSIONED DLT
Permissioned DLTs are those in which the network is controlled by an entity which
sets the rules to join the network. Therefore, not anyone can be a node. This feature
is usually used by applications that work with private information, for example, an
enterprise communication with its strategic providers.
In this category, we can find HyperLedger ecosystem, in which Fabric solution is
the most active project.
2.2. BIG DATA
The main pillar of a great data marketplace is data storage and access. In big data
solutions, the general paradigm is to provide a way of connecting several machines
to work together following a distributed paradigm. The main thing is to comply
with the 5V of big data: Velocity, Volume, Value, Variety and Veracity. In big data
pipelines, several phases have been identified, namely collection, storage and
analysis.
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2.2.1. DATA COLLECTION
In environments where the data is generated at a fast pace and a fast response
needs to be generated, single machines cannot cope with the computational
requirements. In those cases, stream processing is done following a distributed
processing approach. Apache Kafka is a prominent tool in this task. Apache Kafka is
an open-source stream processing tool that provides a high throughput,
low-latency platform for handling real-time data feeds. It provides such a platform
with a message queue managed with the publication/subscription approach,
which is implemented as a distributed transaction log. One of the key features is
the high connectivity with external systems to import and export data.
2.2.2. DATA STORAGE
Some SQL databases provide the means to distribute the data across several
machines with approaches such as data sharding. In data sharding, a big SQL table
is split into several shards that are dispatched to various machines. This approach
makes the system more resilient to faults and increases scalability in terms of
memory and processing. Some SQL databases that provide sharding capabilities
are MySQL or PostgreSQL, among others.
Another approach to increase scalability of databases is to provide data specific
databases, which are named no-SQL databases. In no-SQL databases, the design is
closer to the nature of the data being stored, therefore, there are no-SQL database
specialised on the most common types of data. Some examples them are columnar
stores, document oriented databases, key-value stores or graph databases, among
others. The most popular tools for these no-SQL databases are MongoDB for
document-oriented, HBase for columnar stores and TigerGraph for graphs.
2.2.3. DATA ANALYTICS
There are several tools to analyze data stored in big databases.
In relation to databases that work with Hadoop, Apache Hive is considered the Data
Warehouse. It facilitates consultation by providing SQL access to data stored in
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Hadoop. This way, the computation is distributed across nodes, which applies the
premise moving code is cheaper than moving data. Moreover, it provides queries
integrating the results of various databases and filesystems. It provides a SLQ-like
interface that is implicitly converted into the MapReduce, Tez or Spark jobs.
Moreover, Hive could be configured to use HDFS or S3 (or another massive cloud
storage) as datastore with a BBDD SQL that storage metadata (metastore). This
combination enables a fast access to data with the use of Tez Engine.
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3. SOLUTION
The big data market has become something huge in the last few years, especially
on the geolocation scope. Size, value and use has consistently grown through
worldwide markets and corporations are increasingly depending on data analysis
when it comes to decision making procedures. But big data still needs to improve
in several aspects. There are big challenges that need to be faced so that
participants and stakeholders can efficiently interact with each other.
GeoDB is facing all of these challenges and delivering through the power of DLT,
the solution to create a better and more efficient big data market.
One of the big objectives of GeoDB is to create trust and value within its ecosystem.
GEO token demand and movement has been specifically tailored so that long term
value comes into the market. Our GEO token holders will find a growing market,
endless possibilities within our token use cases and an emerging demand as our
big data marketplace grows in quantity, quality and visibility. Our analysis
encourages us to expect a fast increase in our GEO token market cap as soon as our
protocol is launched LIVE.
3.1. CREATION OF THE FIRST WORLDWIDE BIG DATA ECOSYSTEM
The big data market in general, and the location data market in particular is
extremely atomized. There are four different types of participants:
1.- Users - Data contributors
2.- Middle man platforms (application bringing the users) - Data collectors
3.- Data buyers or data analysts within various organizations
They all act independently without having a global strategy or a common board or
panel in which to develop their activity. They become tiny players with little
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relevance. GeoDB will connect these four parties in a unique ecosystem so that
they can interact smoothly and gain equal relevance from it:
1.- Users - Data contributors
They will participate in the benefit that their data is generating in the
market.
2.- Middle man platforms - Data collectors
They will access a platform in which they can easily and securely deploy their
users’ data. They will be rewarded not only when data is uploaded, but
everytime data is retrieved by the database buyers.
3.- All level of data buyers
They will have access to a new kind of database. A global and complete data
pool, with aggregated information, thus improving the way in which they
make decisions.
3.2. GEO TOKEN VALUE GENERATION
Since its inception, GeoDB has put all efforts in building a sustainable and
value-creator ecosystem so that token holders and stakeholders recognize that
value is constantly being generated.
GeoDB has a clear vision to build a solution that creates value to their users. We
improve current offer and open the door to a 95% of not monetized data sharing
market, bringing following advantages:
1. Data uploaders are rewarded = More available data. 2. Data is more affordable for buyers. 3. High data privacy & Security on DLT (GDPR Compliant). 4. High trust to source of data & No need to audit. 5. Highly scalable automatized model.
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We strongly expect a growing circulation of GEO tokens, a strong demand by data
acquirers and definitely a hike in GEO’s market cap. This increase of GEO tokens
value is based on the concept of the network. An early big adoption thanks to our
strategic partners, will rapidly increase data creation, and it has been solidly proven
that location data pools have huge intrinsic market value. It is easy to conclude that
as GeoDB’s data pool heats up, GEO token will promptly encapsulate that value in
its price.
Chart 5. GEO Token adoption timeline
3.3. GEODB BENCHMARKING. PROMOTING THE
NATURAL BALANCE
GeoDB aspires to be the gear to transfer to the users the fair value for their
information, guaranteeing on the other hand an equitable cost to the buyers. It is
true that the advent of the Internet has democratized access to information, but
this has not been an impediment to the creation of oligopolies where large existing
companies, using their dominant position, would leave competitors out in the dark.
With GeoDB we want to create a solution resilient to those situations, leaving
freedom for a liberalized market but establishing mechanisms that prevent buyers
from carrying out unethical practices that affect the survival of the ecosystem in
the long-term.
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In 2013, the Financial Times published an interactive calculator [IGL.COM.13] that
allows us to determine a price for our personal data based on pricing benchmarks
supplied by a data broker [MOR.PRI.13]. For simplicity, let us say that the average
cost according to that calculator is around $1.
Logically, buyers would not buy individual users’ data, as it has no value
individually. The real value lies upon large datasets with the data of millions of
users. Based on the ratio, 1 person = 1 dollar, it is easy to estimate the cost of a
dataset with the data of a million of users. But, would you sell your personal data for
$1? Ancient and Frog Design carried out a study to quantify the value of personal
data that individuals would give up in exchange for an IT service and the results are
summarized below [MOR.PRI.13].
Chart 6. Revealed value of personal data
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We expect to receive much more than $1 for our personal data and even more for
our location history. The previous study also shows that people value certain kinds
of information more highly than others. This was corroborated by Staiano. J et al. in
their 2014 paper: ‘Money Walks: A Human-Centric Study on the Economics of
Personal Mobile Data’ [STA14]: “We have found that location is the most valued
category of personally identifiable information … (and that) … bulk information is
valued much higher than individual information”. A contemporary study
significantly increased the estimated cost of users’ data. Specifically, Boston
Consulting Group estimated in 2013 that a user’s data costs about $800, and that it
would cost about $2.400 in 2020 [BIG.SEL].
THE BIG COST OF BIG DATA
Let us now turn our attention to buyers. How much they are willing to pay? A key
enabler for big data is the low-cost scalability. For example, a PetaByte (PB)
Hadoop [HAD] cluster will require between 125 and 250 nodes which costs around
$1,000,000 [FOR.BIG.12].
So, is it possible to store 1,048,576 GigaBytes (GB) for $1,000,000? It is not so easy. In
2012, Amazon carried out another study [AMA.AMA.12] on the costs associated with
data warehouses, finding expenses up to $25,000 per TeraByte (TB) annually, or
$1,000,000 by 40TB for a year ($976.56 per GB). What is behind these costs? Setup
and maintenance. While storage is more affordable every year, engineering is what
lies at the heart of the issue, having to solve challenges such as i) scrubbing
information, ii) maintaining security, iii) establishing compatibility with business
intelligence/analytics tools and iv) ongoing data movement [ATS.BIG.17].
However, a high operational cost is not problematic if the Return On Investment
(ROI) is adequate, and in this field, it is. The big data market was worth
$166,000,000,000 in 2018 [FOR.6PR.14], which provides a sense of just how much
financial capital enterprises are pouring in to data operations [SYN.QUA.17].
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But if you base your big data and analytics solutions on low-quality data, you will
see low ROI, and if the data you are storing and analyzing is full of inconsistencies,
inaccuracies or other problems, the analytics results you get will be misleading
[SYN.QUA.17]. Therefore, it is not enough to use an adequate infrastructure, but also
needed to fill it with quality data.
GEODB’S ROLE IN THE MARKET
As an innovative solution that aims to transform the commercial relationship
between users and buyers, GeoDB cannot be measured solely from a quantitative
point of view. The new paradigm that enables our solution offers multiple benefits
that allow us to solve several traditional problems elegantly:
● The use of smart contracts where ‘code is law’, guarantees the absence of
intermediation once the system has been put into operation.
● The incentive system allows the deployment of economically self-sufficient
infraestructures.
● The coexistence in an ecosystem allows us to deploy our own solutions with
which we can obtain direct economic benefits.
● The immutability of the data allows to maximize its quality.
All these aspects make it clear why our proposal can be a more adequate solution
both from a quantitative and qualitative point of view.
As for the economic benefit of users and cost for the buyers, we rely on three
mechanisms:
1. The capitalization of the value of users’ data through a digital asset, the GEO
token.
2. The definition of i) capitalization and ii) cost models based on the theory of
diffusion of innovations [WIK.DIF] to guarantee i) an emission adapted to the
demand and ii) prevent situations of abuse respectively.
3. The use of a proportional distribution of incentives in order to maintain a
constant relationship between the tokens received by the users and the
tokens spent by the buyers.
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Under this mechanism, users will receive a number of tokens adapted to the
expected diffusion of the solution. On the other hand, buyers must pay GEOs to
acquire the datasets. If the price is too high, they will not buy, which will lead to a
decrease in the price of data. This economic system will ultimately lead to a
liberalized market in which the price of the data will reflect the fair value for all of
the parties.
3.4. GEODB ACQUISITION PRICING MODEL
GeoDB pursues to open the big data market on a global scale, that is why our
pricing model aims to facilitate data acquisition to everyone, offering unique
pricing conditions.
To achieve this goal, it is vital to accurately design the cost of data acquisition in
order to maintain an equilibrium between benefits for users and costs for buyers
at all times. Therefore, we consider that it is necessary to link the cost of data
acquisition to the diffusion rate expected for GeoDB, establishing reduced prices
during first years to encourage purchases and progressively increasing them until
reaching the equilibrium point.
To estimate the diffusion of GeoDB we embrace the Theory of the diffusion of
innovations [EVE03]. Professor Everett Rogers [WIK.EVE] popularized in his book of
1962, Diffusion of Innovations, the theory with the same name which seeks to
explain how, why, and at what rate new ideas and technology spread.
The concept of diffusion on which Everett’s theory is developed was studied in 1890
by Gabriel Tarde in The Laws of Imitation [WIK.GAB]. He identifies 3 main stages
through which innovations spread: 1) Difficult beginnings, during which the idea
has to struggle within a hostile environment; 2) Exponential take-off of the idea; 3)
Logarithmic stage, corresponds to the time when the impulse of the idea gradually
slows down while, simultaneously new opponent ideas appear. The ensuing
situation stabilizes the progress of the innovation, which approaches an asymptote
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[WIK.LOG]. This diffusion model is usually modeled using sigmoidal functions
[WIK.SIG], also known as S-curves, which are widely used in fields such as artificial
neural networks, biology, biomathematics, chemistry, demography, economics,
geoscience, mathematical psychology, probability, sociology, political science,
linguistics, and statistics. The cost curve that we have defined for GeoDB will be the
following:
(b)C = M
1+( ) em0
M−m0 * − Bb f* c
● M, the maximum cost.
● m0, the minimum cost.
● b, the depth of the current block in GeoDB’s big data ledger.
● B, the number of blocks to generate before reaching M.
● fc, an adjustment factor of the steepness of the curve.
We have established the following values:
M m0 B fc
GEO 10,000 GEO 1 2,207,520 13
So we can substitute in the previous function to obtain the cost function of GeoDB.
(b)C = 10,000
1+9.999 e*− b 13*
2,207,520
Its graphic representation can be seen below:
Chart 7. Data pricing vs Time (years) in GeoDB ecosystem
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3.5. REWARD SYSTEM - INCENTIVES
The correct setting up of the incentive system is one of the most delicate issues for
the economic sustainability of GeoDB in the long-term. We have designed an
equitable incentive system adjusted to the technological penetration that we
expected in order to guarantee the interests of all the parties involved.
Our proposal is to carry out an initial distribution (preassigned tokens for sales and
team objectives) of 30% of the total supply and distribute the remaining 70% as
rewards for users and potential data buying partners.
To distribute the users’ rewards we have defined a decremental logarithmic model.
This model will be repeated in cycles of 21 years at the rate of a block every five
minutes, giving a total of 2,207,520 blocks per cycle.
The cumulative reward curve that we have defined for GeoDB will be the following:
a(b)R = 2T
1+e− Bb f* r − T
● T, the number of tokens to be rewarded.
● b, the depth of the current block in GeoDB’s big data ledger.
● B, the number of blocks to generate before reaching M.
● fr, an adjustment factor of the steepness of the curve.
T B fr
GEO 700,000,000 2,207,520 10
So if we take the whole reward pool as in the example, we can substitute in the previous function to obtain the cumulative reward function of GeoDB.
a(b) 00, 00, 00R =1+e− b 10*
2,207,520
1,400,000,000 − 7 0 0
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Its graphic representation can be seen below:
Chart 8. GEO Token reward vs time (years) example in GeoDB ecosystem
Using the previous function it is trivial to calculate the reward for a given block:
a (b) R ′ = 1971 e( b
220,752)2
12,500,000 eb
220,752
Its graphic representation can be seen below:
Chart 9. Reward per block vs Time (years) example
To distribute the rewards, we have defined a proportional distribution between
data generators and data sellers (90%) and a recycling pool (10%) to start a new
cycle once the current one is finished. Tokens allocated to data sellers will be used
to incentivize major big data partners to join GeoDB ecosystem. They will be able to
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use tokens for data purchase purposes. More exact distribution between users and
data buyers will be specified in next versions of our White Paper.
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4. ARCHITECTURE
DLT in general and blockchain technologies in particular, are being developed right
now, and this scenario causes that sometimes their benefits are exaggerated and
their limitations are ignored.
The most popular DLTs were designed to facilitate the transmission of an economic
value, and they are not conceived to store large volumes of information, in fact,
many of them implement mechanisms to discourage these uses. A traditional DLT
is not a valid infrastructure for storing data under a big data paradigm, so it is
necessary to follow alternative approaches. Our architecture has been conceived to:
● Making available private information of millions of users.
● Guaranteeing the integrity and immutability of terabytes of information.
● Resolve queries in this volume of information.
Chart 10. GeoDB as confluence
Our solution is based on a hybrid DLT architecture in which we use:
1. IOTA to collect large volumes of data while preventing traceability.
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2. An Ethereum ERC-777 token to manage the economic value.
3. HyperLedger Fabric framework for the development of the nodes of our
infrastructure.
4.1. DATA VERIFICATION
Every piece of data provided to GeoDB must be verified by a federation in order to
guarantee data quality assurance, trustworthy and ownership.
To be able to join the federation, a selection process ensuring the fitness of the
joining organization will be performed. Legally binding contracts will be signed,
and proper DAO mechanism will be used to ensure that new members comply
with their duty as initial gatekeepers of the ecosystem. The requirements to be met
in order to participate as a federation member will be detailed in further updates.
In short, the federation could be considered as an orchestrator inside the GeoDB
ecosystem, where reward methodology is based on the GEO.
From a technical point of view, its operation can be summarized as follows:
1. Each user that supplies data to GeoDB must verify it using GeoDB’s SDK and
following the provision protocol established for each kind of data:
a. Stream of data: Provision in restricted IOTA MAM channels of
verifications and provision of the information in time slots.
b. Isolated data: Provision in encrypted IOTA bundles of verifications and
individualized provision of the information.
2. When the data and its verification are supplied to the federation and it i)
validates the information, ii) stores their verifications in the ledger and iii)
stores the data in the cloud for later access.
3. Once a block is created, the rewards of the users who have contributed
information are automatically computed and a ledger with the
corresponding rewards for each user is published in the ledger of the
federation. For the calculation of the rewards, several aspects are considered:
a. Rewards in the block. The distribution curve is followed.
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b. Abstract user’s profile. Measured through the number of verifications
that this user has provided so far, the number of data types and the
number of blocks in which he has provided information.
c. Abstract user’s influence. Measured through the number of times
that their data has been used for the generation of datasets.
d. Intermediary. To distribute a part of the reward to this intermediary.
4. Periodically, an aggregate ledger with the rewards generated for users is
written in Ethereum . Using this ledger, each user can claim their reward. In 1
this stage, a rewarder node takes the job, checks that the user really
deserves the reward and executes the smart contract associated to such a
reward.
Image 2. GeoDB data verification process
1 This is not done after each block to minimize costs.
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Initially, data provision to GeoDB will only be possible using the SDK facilitated by
our company, which should be integrated by the service or application, which is
willing to allow their users to contribute information to GeoDB.
This SDK includes several libraries, which allow access to the device information
and perform actions to verify and certify it, both in the device and GeoDB’s
infrastructure.
In addition, GeoDB's SDK will integrate different scripts and utilities that will make
it easier to use for developers, from generation of the keys to the configuration of
DLT nodes.
4.1.1. IDENTITIES
For privacy reasons, it is necessary to dissociate the identity used to operate in
Ethereum of the identity used for the data provision, both for the user and for the
developer.
The approach we follow is to use elliptic curve cryptography under the same
private key but using two different elliptic curve domains. Thus, the user will have
two public keys impossible to be associated externally but managed using the
same private key.
The elliptic curve domain to be used in Ethereum is predetermined by its
infrastructure, and it is secp256k1 . In Fabric, we can use any elliptic curve domain, 2
and in our case we have opted for the one used in Monero, Edwards25519 , which is 3
birationally equivalent to Curve25519 and whose domain is optimized to carry out 4
different cryptographic operations.
4.1.2. FACILITATORS
2 https://forum.ethereum.org/discussion/comment/53/#Comment_53 3 https://monerodocs.org/cryptography/asymmetric/edwards25519/ 4 https://crypto.stackexchange.com/questions/43013/what-does-birational-equivalence-mean-in-a-cryptographic-context
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GeoDB offers two great features for data sharing services creators like data
analytics or visualization tools: i) direct compensation to their users and ii) a direct
way to monetize their solutions.
Thus, and for simplicity, we will assume that each user of our application, U, will
have his private key, Uk, and his public key, UK. Each information package to be
sent, P, will be signed with uk and will be characterized by the 3-tuple <I , sign(I,
Uk), UK>, where I is the information to be provided and sign(I, Uk) the signature of I
using Uk . 5
After that, the facilitator, F, signs with his private key, Fk, the user's package, P. So
the information provided would be a 3-tuple <P, sign(P, Fk), FK>.
If the above was a valid package, its contribution to GeoDB should get a reward.
However, we propose that the facilitator can also be compensated, thus offering an
incentive for him to consider the integration of our SDK.
In this way, a user's information package, P, becomes a 4-tuple in which the
facilitator reward percentage, R, is also included, and the signature using Uk will be
made on the 2-tuple <I, R> (sign(<I, R>, Uk)) instead of I.
5 As indicated before, the provision protocol implies the use of different keys and some additional information, but we illustrate it simplified for didactic reasons.
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Image 3. GeoDB facilitators reward mechanism
4.1.3. CAPTURE
In the last section we have talked about how a user sends a packet, P, in which his
information, I, is included in GeoDB, but we have not talked about the format of I.
I is the result of applying an asymmetric encryption function using the public key of
GeoDB to a JSON content, indicating in this content different information
according to the specifications provided by GeoDB, which is currently in the
modeling phase.
Thus, the content of I is unknown to everyone except the user, the facilitator and
GeoDB. Due to this, to certify that a dataset acquired in GeoDB contains only
information provided by users that are using the SDK facilitated by GeoDB, the
protocol requires providing a public verification of the data generated at the time
of capture to accept a package.
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To store these verifications we rely on IOTA, a DLT DAG that can be used to carry
out zero cost transactions in which to include arbitrary information. Each
transaction made to IOTA requires the realization of POW and has a small
computational cost which allows us to minimize the risk of providing false
information to GeoDB as well as reducing the risk of SPAM attacks.
In GeoDB we have two kinds of data inputs: isolated data and data streams. In the
first case we use isolated IOTA transactions to include the verification, in the
second, we use IOTA MAM channels, which, being a slightly complex mechanism to
understand for newcomers, are described succinctly below.
MAM channels are designed as message chains, allowing to publish data streams
that are only intelligible for those who own the necessary information (channel's
address, encryption key if it is used, etc). To publish no traceable streams of data,
MAM publishes each message to a different address, but it uses verbose
information that points to the next message. MAM channels are usually exemplified
as a one way road, so when you enter the channel, you can read the next messages,
but not the previous ones.
Each message in a MAM channel is stored in a bundle, which includes two sections,
signature section and MAM section. Signature is used to MAM’s ownership and thus
its validity checking. MAM section stores an actual masked message.
Chart 11. MAM channel data stream
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To simplify the interaction with IOTA, each information stored in MAM channels is
formatted using JSON due to IOTA libs include several functions to ease the use of
MAM channels with this type of format. The modeling of the information is
currently being carried out and the fields that will need to be included in this JSON
will be derived from the above.
The timestamp is obtained from the MAM bundle message and the user id is
indicated by the user, so it will not be necessary to include them in any case.
4.1.4. PROVISION
We must consider that absolutely all of the above is carried out without the
intervention of GeoDB.
The previous steps only describe how the information and its verification should be
prepared. Any user who provides information to GeoDB following the indicated
format will get a reward.
GeoDB will verify that the protocol has been carried out in accordance with the
specification, and in this case, it will store the user's data in GCP, it will store the
verifications in the ledger, and it will issue a reward to the user and to the facilitator.
4.2. DATA ACQUISITION
To understand how information acquisition works, it is necessary to understand
some details. We will consider that:
● GeoDB has multiple data, dx.
● Using an injective non-bijective function, h, it is possible to generate a
unique value for each dx, h(dx) = vx.
○ It is possible to discern a subgroup of these functions denominated as
cryptographically secure hash functions.
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○ In GeoDB we use the most known and tested cryptographically secure
hash function, SHA-256 . 6
● Each time a dx is provided to GeoDB vx is computed and stored in our DLT.
● Using verified data, GeoDB can compute verified datasets, D, which integrate
a set of data and a set of verifications.
Being the maximum cost for a dataset fixed, when a user acquires information in
GeoDB, the price of D is determined by the percentage of the verifications included
in D with respect to the total verifications stored in GeoDB.
Regardless of queries supported, the acquisition protocol is as follows:
1. Peter is a user who wants to acquire a dataset of verified information from
GeoDB. He generates an identity for this acquisition, y, and launches a query.
2. For Peter's query, GeoDB generates a response indicating i) the amount of
data available and ii) a sample of D encrypted using y public key, Ky.
3. If Peter is interested in D he makes the payment in GEO tokens. This
payment is blocked and cannot be received by GeoDB until D is provided.
4. When Peter makes the payment for D, GeoDB:
1. Generates D.
2. Encrypts D using Peter's public key for this purchase, Ky.
3. Generates a unique result, R, composed by the encrypted D and the
verifications of D, R = {encrypt(D), verifications(D)}.
4. Stores R in a distributed immutable storage. We are currently
experimenting with IPFS and Swarm.
5. Provides the link to R to Peter.
5. Using the above, anyone can know the volume of data acquired by Peter, but
only Peter can know D.
6. If Peter discovered that the content of D does not match the query or that D
contains unverified information, he could block the payment releasing the
unique private key for this purchase, ky.
6 https://en.wikipedia.org/wiki/SHA-2
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5. TOKEN MODEL
GeoDB is building a structure in which the exchange of value between
stakeholders is based on the creation of its own token, the GEO token. GEO token
represents the market value of big data in GeoDB’s marketplace.
GeoDB uses an ERC-777 utility token, GEO token (GEO) to allow the whole system
to work, on the one hand as the channel of value exchange, and on the other hand
to incentivize all of the stakeholders that make it all work together.
To express GEO units one of the following rules must be followed:
● Using the code ‘GEO’. The code ‘GEO’ is followed by a hard space and the
amount. GEO 200.
● Using the sign ‘G’. The amount is followed by the sign 'G' without space.
200G.
GEO token monetary policy
1. SUPPLY: Limited and capped to 1 billion tokens.
2. REWARDS: they will be issued along blocks. Blocks will be emitted each 5
minutes, although network variables might have an influence over the block
time. Blocks will be reflected in the Ethereum blockchain.
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3. INITIAL ALLOCATION: Development, deployment funding and reward of the
team.
4. TOKEN TYPE: Virtual Financial Asset (Maltese Regulation).
5. UTILITY: Token is inseparable from the network.
GEO token sale overall scheme
TOTAL TOKEN SUPPLY: GEO 1,000,000,000
TOKEN REWARD SUPPLY: GEO 700,000,000
TOKEN PREASSIGNED SUPPLY: GEO 300,000,000
5.1. BIG DATA TOKENIZATION
The recent Facebook-Cambridge Analytica data scandal [WIK.FCADS] has put on
the table several uncomfortable questions, and the companies that until now have
been profiting from the user data for free, now know that citizens demand more
transparency [COI.BLO.18, REC.FAC.18].
All the above led to a change in the control of the user’s data, and for the first time
in history, users will gain value from their data. GEO tokens will act as a tradable
asset between data contributors (users) and data analysts (big data companies and
corporations). GEO tokens will transfer the value that companies are willing to pay
for data directly to data contributors and data collectors. Tokenization of the
process makes it easy and secure for all the players to interact.
5.2. DLT FUNCTION
Centralized systems and traditional databases are adequate in many applications
and situations. However, sustainability and trustworthiness are limited with those
technologies. At the same time, the big data market lacks visibility, transparency
and security. From the perspective of sector transformation in sharing, stocking,
trading data and information and digital infrastructure creation, the answer was
definitely to utilize a distributed ledger. From a broad perspective, it allows:
1. Innovative community interaction across applications and players.
2. Provide 3rd party liquidity.
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3. Enhanced efficiency due to elimination of intermediaries.
4. Enhanced security due to immutability of data.
5. Economically self-sufficient infrastructures.
6. History of transactions and prediction of transactions.
7. Easy transferability of value.
8. Resilience to external interference.
9. Long-term sustainability.
Big data requires a decentralized delivery system to match the interests of all
players. We are building a decentralized solution for now and into the future where
the big data grid will function and optimize itself, even under extreme conditions.
Scalability beyond country borders is more important than short-term pragmatism,
as scalability brings more value to the system. Universal access and a one place
data provider built over a robust system is more important than a short-term
solution. Our platform is scalable through DLT beyond country borders and
continents, and GEO tokens will become the virtual utility of a new era in the big
data decentralized market.
5.3. GEO TOKENS USE
One of the main differences of GeoDB’s solution compared to other solutions is that
we do not aspire to compete, but to promote an integrated big data ecosystem. We
believe that DLT solutions should be adapted to the specific needs of each
situation, and therefore, the interconnection between distributed ledgers will be
increasingly common and necessary.
Our ambition is to create a hub of big data applications in which GEO tokens will be
the fuel to move the economic value. GEO token represents the economic value of
an amount of data, and consequently, users will receive GEOs based on the number
of data that they contribute to GeoDB. Every day, each user connected to the
platform will upload data generated directly or through third party applications
that interact with GeoDB.
Users who obtain tokens can choose between several options:
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1. Exchange them for discounts and coupons from our partners.
2. Use them in our worldwide open network of digital connected platforms.
3. Internally transfer GEO tokens between platform users.
4. Sell them in external exchanges.
5. Sell them to the wholesale internal market of companies and corporations
that are interested in buying information from GeoDB’s data pool.
5.4. GEO TOKEN SUPPLY & DELIVERY - REWARD SYSTEM
There will be a total token supply of 1,000,000,000. 300,000,000 will be preassigned,
(200,000,000 to complete our token sale and 100,000,000 as a reserve for the
company & Team). More info on the process can be found below.
5.5. GEO TOKEN ALLOCATION
The distribution of GEO tokens has been specifically designed to incentivize the
founding team, GeoDB’s initial investors and solution participants to build a
scalable and sustainable ecosystem in the long term. 70% allocation for
participants shows the commitment of founders and team members with the
positive and successful outcome of the project. GEO token allocation has been set
as follows:
1. 70% - Ecosystem emission
Data buyers and users (especially, data uploaders) will get a reward based
on their participation on the ecosystem, ensuring an organic cycle of value
exchange for data buyers, data sellers, and all kind of entities in between.
2. 20% - GeoDB’s investors - Token sale.
Allowing the development, funding operations, partnerships, achieving
mass adoption, gaining customers and building the community.
3. 10% - Company & Founding team.
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To incentivize GeoDB’s team, founders and strategic partners.
5.6. GEO TOKEN VALUE CREATION STRATEGIES
In GeoDB we care about our token holders, that is why we will implement a
number of protection strategies that will control GEO token supply available at the
markets. Nevertheless, it is within our business model where the true value
generation process for GEO tokens strengthens up.
1. Staking for federation members
To be able to join the federation, a selection process ensuring the fitness of
the joining organization will be performed. Legally binding contracts will be
signed, and proper DAO mechanism will be used to ensure that new
members comply with their duty as initial gatekeepers of the ecosystem.
The required stake and the requirements to be met in order to participate as
a federation member will be detailed in further updates to this document.
2. Other network actors
As the ecosystem progresses and additional steps are taken towards the
decentralized big data market, new roles could be added to ensure the
correct functioning of the platform. The game-theoretic context that this
implies will be studied in due time.
3. Lock-ups
Lockups apply to both vested and unvested tokens. This will be done
according to the GeoDB legal contracts.
GeoDB will set up lockup periods for GEO tokens bought in our several funding
stages.
GEO tokens that are freely distributed in our token offering process will have the
following lock-ups:
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1. First & Second Private Round investors - 18 months after token
exchange listing in september 2019. First monthly vesting period
expected in June 2020.
2. Founders Vesting Schedule - 24 months after token exchange listing
in september 2019. First monthly vesting period expected in June
2020.
3. Team Vesting Schedule
a. Key Executives - Vested Tokens - 18 Months after token
exchange listing with equal % cliffs every 3 months.
b. Non Key Executives - Vested Tokens - 12 Months after token
exchange listing with equal % cliffs every 3 months.
Non vested tokens will be lost if team members decide to leave the
company.
4. Advisors - 18 Months after token exchange listing and then equal %
cliffs every 3 months.
5. Strategic Partners - 12 Months after token exchange listing and then
equal % cliffs every 3 months.
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6. ROAD MAP 2018
Founding of GeoDB
Team formation
First partnerships in EU market
GeoSuite prototype development
Hard cap on seed round
2019 H1
Development of test net is finished on 50%
# of users of Apps agreed to connect to GeoDB is 12M+
Hard cap on private investment round
2019 H2
Expansion to Asian market
Initial Exchange Offering
Listing to 2 leading crypto exchanges
Launch of test net
2020 H1
Launch of main net & GeoSuite
Listing to top 3 CMC exchange
Expansion to US market
Initial Ecosystem Transactions - Organic Traffic
2020 H2
Permissionless storage
Improved data sharing environment
GeoDB App Store
Two initial Strategic Partnerships Closed
1m Active GEO Token Wallets Reached
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Successful Launch of Ecommerce Loyalty Module
2021
Permissionless analytics
100+ Connected Third Party Apps to the ecosystem
50+ Data connected clients to the ecosystem
10+ Proprietary Apps Launched
Successful Launch of Media Companies Module
6.1. USE OF FUNDS
Funds raised during the contribution period will be used solely for the development
and benefit of the GeoDB’s platform. A budget has been outlined below:
Chart 12. Invested funds allocation
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7. GROWTH, MASS ADOPTION & PARTNERSHIPS
GeoDB will achieve accelerated growth thanks to its user reward approach and its
initial strategic partners which will bring a massive user base since the inception of
the solution. We are not asking for new behaviours in users. They will continue
using their usual apps & platforms in the same way, but they will be rewarded by
the system on a daily basis. Word Of Mouth (WOM) within platforms will allow rapid
growth and engagement between users.
This, added to our developers proximity strategy, in which they will gain a strong
monetization stream for their products, will mean a massive connection to the
solution by worldwide platforms.
7.1. GROWTH STRATEGY
GeoDB growth strategy will be initially based in four areas: 1) Data pool creation, 2)
Building data demand, 3) Interconnection of features and 4) Monetization of
community developments:
1. Data pool creation:
Rapid user adoption to accelerate data storage. More data, more value for
data buyers. The bigger the data pool becomes, the easier it is to build up
momentum in the demand size. GeoDB will run acquisition strategies both
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on the user side and the platform side. Marketing, communication and PR
campaigns to gain visibility in the market.
2. Building data demand:
Higher data demand will increase value generation for users and platform
developers. The bigger the demand, the bigger the rewards for users and
data collectors. To generate data demand, GeoDB will seek further strategic
partnerships with data mining & analytics companies initially and secondly
running acquisition campaigns in the market to build up momentum around
our decentralized data sharing ecosystem.
3. Interconnection of features:
We offer GeoDB in a complete environment in which the interconnection
between DTL solutions, big data Extraction, Transformation and Loading
(ETL) solutions and other tools is easy and transparent. Any user, whether he
is passionate about DLT, a data scientist or a developer, will find in our
environment an optimal solution for his needs. Whether it is necessary to
interact with our solution, use other tools or develop new products, our
environment makes his work easier.
4. Monetization of community developments:
GeoDB provides a decentralized marketplace of applications. This feature will
bring developers attention to GeoDB, where they can provide new
components to extend ETL functionality or entire new software and
monetize it. In the app marketplace, developers can provide for example
widely used analysis tools or new ways of visualising datasets. Data scientists
can take advantage of these pieces increasing the usability of GeoDB for
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them, and can also monetize their developments if the functionality they
need is not available.
7.2. GEOCASH
GeoDB will launch its own data collector app, geoCash, that will allow users to
share data with GeoDB while being rewarded with GEO tokens on a daily basis.
geoCash has already been designed and will be developed shortly within the
company’s general development road map. Basic screens of the product UX flow
are shown below:
Simplicity and usefulness are the core assets of geoCash. The company will develop
growth strategies based on ASO optimisation, digital PR activities and paid
acquisition tools, looking to gain viral momentum in the market and becoming one
of the most accepted wallet apps in the market. geoCash intends to grow crypto
culture in a massive way.
The test version of GeoCash can be downloaded in Google PlayStore
https://play.google.com/store/apps/details?id=com.geodb.geocash&hl=es_419
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7.3. GEOSUITE
geoSuite is an Eclipse E4 RCP [ECL.RCP] application that integrates several features
developed following an OSGi modular architecture [OSG]. This architecture allows
to add and manage features transparently, which results in a living environment
that evolves to meet the needs of its users. Additionally, we use Eclipse Rich Client
Platform technology, or Eclipse RCP, which has been developed under an OSGi
architecture and provides several open source components of high quality and
actively maintained with which develop advanced features in a simple way
[ARC.RCP.10, ECL.ARC].
Thanks to these technologies, geoSuite exposes several features that postulate it as
a tool to be included in the toolbox of GeoDB users, data scientists and anyone
interested in DLT technologies, since it allows to:
● Access GeoDB’s data sharing ecosystem easily.
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● Integrate any functionality necessary to interoperate with different
technologies whether they are data sources, web services, third-party
software or other DLTs.
● Encourage community participation in the development of geoSuite
compatible modules in order to increase the available features.
● Follow a rolling release [WIK.ROL] development model in which the user can
always stay updated without effort.
geoSuite is a versatile solution that provides a wide range of features, which are
subdivided into three general categories:
Core functionalities
Allows to adapt the suite to users’ needs and include features such as accounts
management, appStore access or activation and deactivation of features among
others.
GeoDB infrastructure
Allows to provide GeoDB’s infrastructure capabilities. With these features the users
can obtain statistical information about GeoDB, use custom modules to provide
additional functionality or deploy their own nodes and DLTs using modules
developed for the suite.
Big data analytics
Allows to buy location information datasets, execute algorithms and software
libraries developed in the same suite, use third-party tools to enrich the information
or integrate other software to carry out a customized analysis.
7.4. APPSTORE
appStore is a marketplace in which the users can sell their analytical and
visualization tools, libraries or any other asset and earn GEOs. geoSuite provides
assisting tools to sell and purchase assets to participate in it, however anyone can
develop a custom client to interact with its interface.
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7.5. ECOSYSTEM PARTNERS
GeoDB has secured a substantially big initial reach for its pool data generation
procedures, closing a strategic partnership with Wave Location Technologies that
will connect its several apps and future developed products to the solution from
the initial moment in which the network is launched:
1. Wave Application - www.waveapplication.com
2. Wola Maps - www.wolamaps.com
3. Sister - www.joinsister.com
4. Trazer - www.trazer.live
5. Wola Schools - www.wolaschools.com/en/
Thanks to these partnerships, GeoDB will automatically gain more than 12 millions
users worldwide achieving high data generation, visibility and GEO token WOM.
Wave and Wola Maps will integrate GEO wallets into their products, which are
ready to be connected to GeoDB to generate data and initiate the daily reward
system. We have attached basic screens of both apps UX flow with GEO wallet
integration. On the demand side we have successfully closed several initial
partnerships with big data companies:
1.- AboutGoods (https://aboutgoods-company.com/) will join forces with GeoDB in
order to improve the data they are collecting from retail buyers’ receipts to analyze
products they are buying.
2.- Nisgo (https://www.nisgo.com/) is a professional big data industry player which
is trading and analyzing location data, which is later used in industries like real
estate and others. They will be buying location data sets from GeoDB and also
introducing different analytical tools for GeoDB data buyers.
3.- Rate&Grade (https://www.rateandgrade.com) is a company that provides its
customers real time feedback through Business Intelligence dashboards that allow
for more simple and agile decision making.
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4.- Datalytics (https://www.datalytics.com) A company born in 2007 in Argentina,
currently present in several countries across Latam, always with a clear purpose:
generate strategic alliances with organizations so they can make intelligent
decisions based on data.
Datalytics develop solutions with clients with the vision of bringing companies to
the concept of information as the most relevant asset of the century.
Therefore it's a perfect match for GeoDB. They have a multidisciplinary team, which
includes computer engineers, designers, IT systems analysts, economists, business
administrators, and actuaries.
Through creativity, wit, and experience they accelerate and catalyze data analytics
projects
5.- Flame Analytics (https://flameanalytics.com) Company with more than 10 years
experience in Big Data, Retail, Consultancy and Data Engineering. Headquarters in
Spain and Florida. More than 20 different products to offer data solutions to Malls,
Hotels, Retail, Restaurants, Transportation
7.6. OTHER STRATEGIC USER APPS
GeoDB ecosystem will initially count on other tool apps with which users will be
able to access GeoDB reward system. These apps will be developed by GeoDB’s
team & will bring visibility to the solution, data, growth, usage, WOM and size.
Thanks to our partnership strategy, crypto culture will rapidly expand in a
worldwide scope, and GEO wallets will gain a fast mass adoption becoming an
expanded payment tool. GEO tokens adoption by users around the world will build
market demand and increase market cap value. These are some of GeoDB’s initial
apps portfolio:
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2.- Trazer: Build your own world travel map.
3.- WaWa: Move yourself and never forget to hydrate yourself.
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8. TEAM
GeoDB solves market challenges and inefficiencies through a complex platform,
which requires a combination of active players, scalable speed and storage,
tokenization, blockchain, financing, market trading, big data supply knowledge,
and experience. The GeoDB team synergizes this essential mix of expertise to
create a new generation of a utility company.
TEAM MEMBERS
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9. REFERENCES
AMA.AMA.12
https://aws.amazon.com/es/blogs/aws/amazon-redshift-the-new-aws-data-warehouse/
ARC.RCP.10
http://web.archive.org/web/20100307050224/eclipsercp.org/book/chapters/RCP_Foreward2.p
df
ATS.BIG.17
https://www.atscale.com/blog/big-data-cost
BIG.SEL
https://big.exchange/sellers
COI.BLO.18
https://www.coinspeaker.com/2018/02/17/blockchains-role-war-user-data/
ECL.ARC
https://wiki.eclipse.org/Eclipse4/RCP/Architectural_Overview
ECL.RCP
https://wiki.eclipse.org/Rich_Client_Platform
ENG.FAC.18
https://www.engadget.com/2018/04/30/facebook-cambridge-analytica-data-royalties/
EVE03
Rogers, Everett (16 August 2003). Diffusion of Innovations, 5th Edition. Simon and
Schuster. ISBN 978-0-7432-5823-4
FOR.6PR.14
https://www.statista.com/statistics/551501/worldwide-big-data-business-analytics-reven
ue/
FOR.BIG.12
https://www.forbes.com/sites/ciocentral/2012/04/16/the-big-cost-of-big-data
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HAD
http://hadoop.apache.org/
IDC.REV.18
https://www.idc.com/getdoc.jsp?containerId=prUS44215218
IGL.COM.13
http://ig-legacy.ft.com/content/f0b6edc0-d342-11e2-b3ff-00144feab7de#axzz5MudwqLJm
INV.HOW.18
https://www.investopedia.com/tech/how-much-can-facebook-potentially-make-selling-your-
data/
MED.TOK.17
https://medium.com/@wmougayar/tokenomics-a-business-guide-to-token-usage-utility-and-v
alue-b19242053416
MOR.PRI.13
http://www.more-with-mobile.com/2013/06/prices-and-value-of-consumer-data.html
NYT.USE.18
https://www.nytimes.com/2018/03/06/business/economy/user-data-pay.html
OSG
https://www.osgi.org/
REC.FAC.18
https://www.recode.net/2018/5/8/17329696/facebook-blockchain-crypocurrency-david-marcu
s-crypto-messenger-app
STA14
Staiano et al. Money Walks: A Human-Centric Study on the Economics of Personal Mobile
Data ( https://arxiv.org/pdf/1407.0566.pdf )
STA.FOR.18
https://www.statista.com/statistics/254266/global-big-data-market-forecast/
SYN.QUA.17
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http://blog.syncsort.com/2017/03/big-data/quality-data-big-data-worth/
WAV
https://www.waveapplication.com/
WIK.DIF
https://en.wikipedia.org/wiki/Diffusion_of_innovations
WIK.EVE
https://en.wikipedia.org/wiki/Everett_Rogers
WIK.FCADS
https://en.wikipedia.org/wiki/Facebook%E2%80%93Cambridge_Analytica_data_scandal
WIK.GAB
https://en.wikipedia.org/wiki/Gabriel_Tarde
WIK.LOG
https://en.wikipedia.org/wiki/Logistic_function
WIK.ROL
https://en.wikipedia.org/wiki/Rolling_release
WIK.SIG
https://en.wikipedia.org/wiki/Sigmoid_function
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