Wikibits - A Blockchain - based Solution - driven Wiki

  • Wiki: Community-based Knowledge Platform

    There is a growing appreciation of the centrality of user involvement as a contributor to information and knowledge. The role of the users in the era of the Internet and blockchain is changing. Wikibits is exploring the potential for increased evidence-based solution and participation of the community in provide such evidence and solutions and for expediting improvements in innovations. Wikibits’ information infrastructure has the potential to support a faster, higher-quality, more effective information-solution system. By offering users and consumers unprecedented access to information and community evaluations, Wikibits will directly impact user knowledge and solution-based product development.



    One of the best-known applications of blockchain is the crypto-currency Bitcoin[1, 2]. Through a famous white paper [1] published in October 2008, Bitcoin was proposed by the unidentified person or persons “Satoshi Nakamoto”. In the following year, the open-source Bitcoin implementation was released [2]. According to the US Treasury, as a peer-to-peer digital currency without a central administrator, Bitcoin is categorized as a decentralized virtual currency [3]. Bitcoin has the unofficial ISO-4217 currency code XBT, which is used by organizations and companies such as Bloomberg [4] and XE [5]. The unit of Bitcoin is BTC. Currently, Bitcoin has the highest total market value among >1,000 various crypto-currencies currently being used

    Alternative Blockchain Technologies and Blockchain Applications beyond the Financial Domain

    After Bitcoin, many other crypto-currencies, such as Ethereum [7-9], Ripple [10, 11], Dash [12, 13], Litecoin [14, 15], and Monero were developed [16, 17]. Additionally, several alternative blockchains (or “altchains”) have been proposed (such as Colored Coins [18] and Sidechains [19]) and are considered to be blockchain 1.0 technologies [20]. Several alternative protocols to the proof-of-work have also been proposed, such as proof-of-stake, where the node with oldest coins can create a new block [21-23]; proof-of-burn, where the node willing to “burn” or destroy the largest number of coins, by sending it to a “NULL” address, can create a new block [24, 25]; and proof-of-elapsed-time, where the node with the shortest wait time verified by the trusted execution environment can create a new block [26, 27].
    Although blockchain was originally designed as a crypto-currency, it can also regarded as a new form of the distributed database or ledger, as arbitrary data can be stored in the metadata of the transactions. Since 2014, the original Bitcoin blockchain only supported 80 bytes of metadata [28-31], but other blockchain implementations support larger sizes. For example, MultiChain [29] supports metadata with adjustable size, and BigchainDB [28] has no hard limit on metadata size. A blockchain-based distributed ledger is also known as blockchain 2.0 [20], including the new technologies of “smart properties” and “smart contracts” [7-9, 18, 19, 32-35]. The former refers to the digital properties with ownership controlled by blockchain, and the latter refers to the computer programs designed to manage smart properties. One of the most well-known smart property/contract systems is Ethereum [7-9], which is a decentralized platform for smart contracts [7, 9]. Ethereum as a crypto-currency itself also has the second- largest market cap as of date of writing [6]. Microsoft adopted Ethereum as the core of its new Blockchain-as-a-Service on the Azure cloud computing environment [36].

    Benefits of Blockchain Compared to Traditional Distributed Databases

    Figure 1. Comparison of the Distributed Network Topologies

    Figure 1. (A) Centralized network topology, which creates a single-point-of-failure (the central intermediary). If the central intermediary is down or attacked, the entire network stops working. (B) Decentralized network topology, which does not contain single-point-of-failure. If one of the nodes, such as Node 1, is down or attacked, the rest of the network can still operate normally. (C) Blockchain, decentralized and transparent, there exists a distributed timestamp mechanism, the double-spending problem can be solved on such a decentralized network.
    To better understand why blockchain distributed ledger technology may be feasible for Wikibits, we describe the key benefits or comparative advantages of block-chain [28, 29, 37-39] by comparing it with the traditional distributed database management system (DDBMS) [40, 41], such as Structured Query Language (SQL)-based systems like Oracle [42] and NoSQL-based systems like Apache Cassandra [43].
    The first key benefit of blockchain is decentralized management. DDBMSs are logically centralized-managed while blockchain is a peer-to-peer, decentralized database management system [29, 37, 38]. Therefore, blockchain is suitable for applications where independently managed users wish to collaborate with one another without ceding control to a central management intermediary [29, 39] (i.e. Wikibits).
    The second key benefit is the immutable audit trail. DDBMSs support create, read, update, and delete functions like all database systems, while blockchain only supports create and read functions [28]. Thus, blockchain is suitable as an unchangeable ledger to record critical information (e.g., intellectual property and copyright claims).

    The third is data provenance. On DDBMS, the ownership of digital assets can be modified by the system administrator, while on blockchain, the ownership can only be changed by the owner, following the cryptographic protocols [28]. Also, the origins of the assets are traceable (i.e., the sources or the data and records can be confirmed)[28], increasing the reusability of verified data (e.g., for copyright claims)[44].
    The fourth benefit is both robustness and availability. Although DDBMS and blockchain are based on distributed technology and thus do not suffer from single-point-of-failure, it would be costly for DDBMS to achieve the high level of data redundancy blockchain does (i.e., each node has a whole copy of whole historical data records) [38]. Thus, blockchain is suitable when the preservation and continuous availability of records (e.g., proven solutions) are important.
    The final key benefit of blockchain is related to the improved security and privacy using cryptographic algorithms. For example, Bitcoin blockchain utilizes the 256-bit Secure Hash Algorithm (SHA-256), a cryptographic hash function defined in the US Federal Information Processing Standards 186-4, published by the National Institute of Standards and Technology [45], as the cryptographic hash function in the hash-chain that the proof-of-work algorithm runs on [46]. SHA-256 is also used to generate user addresses for privacy/anonymity improvement (i.e., each user is represented by a hash value in-stead of a real identity, such as an IP address). Furthermore, Bitcoin blockchain exploits the 256-bit Elliptic Curve Digital Signature Algorithm, an asymmetric cryptography algorithm defined in the US Federal Information Processing Standards 180-4 [47], to generate and verify high-security-level public and private keys as digital signatures, and thus ensures ownership of the digital assets, as with intellectual properties and copyrights [48].
    To summarize, the key benefits for adopting blockchain technology for a solution-driven wiki include: (1) decentralized manageme


    General description
    An essential component of a solution-driven wiki is the capacity for constant improvement: to take advantage of new tools and methods and to improve approaches to gathering and evaluating evidence. As technology advances and the ability to accumulate large quantities of information increases, new opportunities will emerge to develop evidence on the effectiveness of solutions, including on daily tasks, consumer purchase behavior, and scientific research including the advances in technology and healthcare. Wikibits will serve as the bridge between information sharing and addressing problems through blockchain. With the help of the community, Wikibits will overcome the challenge of piecing together evidence from the vast sea of information and determine what is best for each circumstance based on community inputs. Wikibits gives a new perspective to a proven information gathering paradigm that is more solution driven. Based on the concepts of direct rewards for contributions, new methodologies such as mathematical modeling, Bayesian statistics, and decision modeling and new database management based on blockchain technology will also expand our capacity to assess and disseminate solutions.

    Engaging the community is necessary for our expansion—including the use of Wikibits token as incentives and mediating an appropriate balance between user inputs and access to meaningful solutions. Wikibits will make new streams of data available for easing the burden of daily task, for impacting research domains and to drive innovation. By linking data systems, blockchain and crypto-currency, Wikibits have the potential to rapidly accelerate the generation and evaluation of solutions. Furthermore, this could be a powerful source of innovation and refinement of information development, thereby increasing the value of information by providing meaningful solutions and/or treatments tailored for specific circumstances and individuals.
    Finally, Wikibits aim to reduce the time gap between when a solution is needed and when a decision must be made. Decisions are made every day in the context of a certain inference gap—the gap between what is known by the user and what evidence is required to make the decision. Users implicitly or explicitly fill in where their knowledge falls short through traditional means of search engine, knowledge bases and tutorials. Wikibits can help to narrow this gap, increasing real-time access to knowledge constructed on community inputs and evaluations. This creates evidence with quantifiable solution relevant to everyday needs. As such, by bringing information, evidence and solution into much closer alignment, Wikibits can help address the expanding universe of information, with a growing need for solutions that are accurate and verified, can meet the daily needs of individual, researchers and organizations alike.

    Table 1. Wikibits Differences

    Table 1. The table illustrates several examples of efforts that of using Wikibits as a practical means of both generating, applying and rewarding community-based solutions.

    Beyond Daily Tasks

    With the adoption and use of Wikibits, hypothesis-driven research utilizing existing community based input can answer a variety of questions not currently feasible due to significant overhead cost in areas such as best antibody for experiments, medical device safety and pharmacovigilance.
    Capturing and utilizing data generated by the community offers the opportunity to bring research and information into closer alignment and propagate a cycle of learning that can enhance both the rigor and the relevance of evidence. Community based input is to play a more fundamental role in the generation and application of evidence on drug effectiveness, product safety and analytic changes that are needed in daily environment. Some considerations included strengthening feedback loops between research and information to refine research questions and improve research hypothesis generation and relevance, improving the structure and management of information both to support better decisions and to provide quality data to users and researchers alike, facilitating “built-in” study design, defining appropriate levels of evidence needed that might help accelerate innovation.

     Linking Information and Solutions: Reduce Fatigue and Drive Commerce

    Finding solutions is currently a multistep process involving searching, reading and evaluating. This in turn could lead to lost time, increased expenses, undesired outcomes, and information fatigue. Having information, solution and evaluation available at a single place can now become a reality with Wikibits. This will also offer the potential for co

    Compensation mechanism

    Wikibits Token


    Wikibits Token Distribution Mechanisms

    1 billion Wikibits Tokens will be reserved to distribute to the community for their contributions over the period of 50 years. As of date of writing, Wikipedia has been online for over 17 years with over 5 million articles, we felt the community ought to at least expect a similar growth rate.

    The token distributed to the individual contributors will be directly proportional to their contribution (i.e. the more one contributes the more they will receive), but inversely proportional to the entire community input (i.e. the more inputs received from the community for the month, everyone will receive a smaller percentage of the total token distributed for the month, even though in absolute terms, one may have contributed more inputs than the previous month). Community inputs will be tabulated at the end of each month. A set number of Wikibits tokens will be rewarded to all contributors for their valuable inputs. Each individual contributor will receive a percentage of the monthly Wikibits token reward based on their percentage of contribution in relation to the entire community contributions. Figure 3 illustrate the simulate growth rate of Wikibits user inputs in relation to the proposed tokens available for contributions. Breakpoint refers to the point when user inputs overtakes the rate of tokens distributed. Disclaimer: this is a simulated graph of token rewards vs user inputs, the actual rate could vary significantly as we adjust to real user data.
    In addition to the usual compensation mechanism, Wikibits will hold monthly campaigns that is geared toward innovations, pressing issues that can be addresses through our portal (i.e. epidemic disease, natural calamities and current geopolitical issues) or areas sponsored by other organizations. These monthly campaigns will allow contributors to earn tokens at a higher than normal rate for their inputs.

    Wikibits Token’s main functions

    The initial WIKI token based on Ethereum ERC20 token standard will serve the primary purpose of a compensation medium for our contributors. As the Wikichain (see section 4.3) develops and matures, the initial contributors will be able to redeem their WIKI ERC20 token with Wikibits coin at a 1:1 ratio. At this stage, Wikicoin will take on secondary characteristics of storing metadata and usher an ecosystem for miners to process transactions, creating a solution-driven wiki for the blockchain.

    Wikibits Business Plan


    Monthly Revenue Allocation

    Wikibits will generate revenue through smart advertisements. Monthly revenue allocation is illustrated in Figure 5. Additionally, 10% of revenue will be allocated to Wikibits Foundation, a non-for-profit organization.

    Wikibits Roadmap

    Wikibits will consist of both front and back end developments. The frontend development consist of Wikibits site beta, mobile app launch, Wikibits Foundation (non-for-profit) establishment and Wikibit site launch. The propose timeline for these products and services are illustrated. The backend development consists of data mining, NLP and machine learning pipeline development and Wikichain development. All of which will commence upon beta site launch as the data and infrastructure needed will only occur after user inputs.

    Wikibits Initial Coin Offering (ICO)

    Participate in Wikibits’ ICO to sponsor Wikibits development
    Wikibits’ token symbol will be WIKI. The initial WIKI tokens are based on Ethereum ERC20 token standard. A total of 1.5 billion will be issued. 250 million WIKI tokens will be available for ICO. For complete breakdown of WIKI token allocation, see section 3.1.
    The Wikibits ICO starts on Febuary 15th, 2018 and continues until March 31st, 2018 or until tokens sell out, whichever comes first. Ethereum and credit card will be accepted. The rate of WIKI will be as follows:

    *Participation in the Wikibits ICO means you are sponsoring the development of the Wikibits, a solution-driven wiki for the blockchain. Wikibits LLC does not and cannot promise any guaranteed returns for ICO participants.
    *WIKI token cannot be construed as security since it does not reflect the ownership of Wikibits LLC. legal entity.
    *Wikibits is not associated with Wikipedia.

    Wikibits ICO allocation

    All funds received from the ICO will be used to for the operations of Wikibits LLC and the breakdown is illustrated below.
    The complete breakdown is as follows:

    40% - Product Development
    Developing a user friendly and robust product that can be utilized for daily tasks as well as stand up to the rigor of scientific testing and commercial applications.
    25% - Marketing
    To rapidly expand market share for logarithmic growth of our user base.
    20% - Operations
    The cost related to server maintenance, customer service, office space and equipment.
    10% - Legal
    The cost for legal compliance and accounting and establishing Wikibits Foundation.
    5% - Wikibits Foundation
    5% of ICO will be allocated to Wikibits Foundation, a non-for-profit organization aimed to assist the financial burdens of education and research. See section 6 for more details.

    Wikibits Team

    Warren Wang (Founder, U.S.) During his tenure at the National Institutes of Health, Warren conducted research to enhance the quality of life for individuals. Warren's research leveraged big data to improve outcome measures. Warren was also Senior Development Consultant with Oral Valley Instruments and the co-founder of S&Y Trading Company.

    Zasim Siddiqui (Co-founder, U.S.) Zasim’s prior experiences include business and customer relations management. Zasim also received his M.S. in Management from the University of Texas in Dallas. Zasim’s current project involves multi-centered collaboration research using big data to support outcome-driven decisions.
    Sara Viernes-Chisler (Executive Director, U.S.) Dr. Viernes-Chisler is a licensed dentist in the United States and the current Co-chair of the dental committee for the ACPA. Her expertise extends beyond the dental domain in product development, personnel and business management including the development of MedRegister and CDS systems.

    Dev Panchal (Marketing Director, U.S.) Deval has been working as Systems Engineer for United Technologies Corporation engaged in market feedback analysis, product design, advertising, and social media marketing. Dev is also the co-owner of Hour Room, Escape Games in San Diego, California where he is currently the Head of Marketing.

    Gary Wu (Director of Finance, China) Gary has ten years of expertise in finance risk management and business intelligence analytics. Gary is currently Risk Manager at Webank, with the largest shareholder being Tencent Group. Gary was also the manager in the CRM and Process Management & Quality department of BMW Financial Services in China and Germany.

    Walter Cheng (Senior Developer, China) Walter has over 25 years of experience in computer engineering and product development. Walter’s previous experiences include senior computer engineer, product development manager, R&D manager for China-based companies including RCL Ltd, QHX High-Tech Ltd and Huizhou Zhongcheng Electronic Technology Co.

    Anand Krishnan (Senior Developer, U.K.) Anand brings over a decade of experience to the Wikibits team in computer science and engineering. Anand has been employed as Natural Language Processing (NLP) Specialist by Linguamatics, Aditi Technologies and Infosys Technologies. Anand specializes in database management, machine learning and NLP.

    Jay Patel (Developer, U.S.) Jay Patel is an expert in natural language processing (NLP) and machine learning algorithm and holds a pending patent in image processing using his proprietary algorithm. Graduated with M.S. in Informatics from Rutgers University, Jay is currently a consultant with Eli Lilly and Company for developing a NLP pipeline

    Aarif Shaikh (Developer, India) Aarif joined the team with more than six years of experience in developing web-based applications and portals in these domains: banking, insurance, finance, and media. Aarif’s past clients includes Bank AlJazira (Saudi Arabia), Banque Saudi Fransi (Saudi Arabia), Deutsche Gulf Finance (Saudi Arabia), and Reserve Bank of India (India).

    Nikhil Sangode (Junior Developer, U.S.) A recent graduate from the University of Texas in Dallas. Nikhil has various experiences in model-based systems engineering and is fluent in several programming languages. From his employment experiences, Nikhil has developed products for companies including Qualcomm Technologies Inc. and Mobilecomm Professionals Inc.

    Andres Mantilla-Rodriguez (Project Manager, U.S.) Andres has over 5 years of experience in multinational project management and coordination. Having worked on multiple government, corporate and privately funded projects, Andres’s expertise in communication, task and team management can be leveraged to facilitate the timely development of the Wikibits platform.

    Karissa Cottier (Scientific Development Liaison, U.S.) Currently a doctorate candidate at the University of Arizona, Karissa is familiar with the scientific development process. In addition to her science-related background, Karissa is also an avid Instagramer. Karissa serves to disseminate our backend scientific development progress to the general public.


    Mike Chi (Financial Advisor, China) Mike is currently the Manager of Sales Operations for BMW Group (entire China Division). Mike's previous experiences include Financial Controlling Manager at BMW Group and was part of BMW global management trainee program with various roles in strategy, controlling, treasury and sales planning.

    Tom Fitch (Business Development Advisor, U.S.) Recently retired from Eli Lilly and Company, Tom is the owner of a real estate company in the United States. Tom's prior experience in business and industry allows him to offer key insights into the steps needed for start-ups to succeed and the precautions to take during our backend development process.

    Rajesh Krishnan (Product Development Advisor, U.K.) Rajesh has been employed as Business Analyst (Senior, Lead and Tech) and Senior Consultant for companies including HP, edge IPK, Aviva and Vitality. He has managed a portfolio of products in an e-learning startup named TouchSurgery in London and brings his cross-industry expertise to WikiBits.

    Kenny Liu (Technology and Marketing Advisor, China) Kenny boasts over 20 years of experience in product engineering, sales and marketing. Kenny was the lead product engineer and head of marketing division of AMlogic Inc in Shenzhen, China and head of sales and product marketing manager at Silicon Storage Technology (Shanghai and Shenzhen Division, respectively).

    Waseem Akram (Marketing Advisor, India) Regional marketing expert (Medical) for West and South India Business unit of Abbott India Ltd. Waseem has extensive experience in key opinion leader engagement, advocacy activity, marketing and sale strategy development to facilitate business solutions in collaboration with sales and marketing teams.



    One Pager:

    White Paper:





    E-Mail (Support):[email protected]

    Interested in joining our team:[email protected]

  • Wikibits implementation

    • Traditional wiki

    A wiki encompass an enormous variety of information, from the general information, such as the best solution to remove wine stains to cellular networks, which provide knowledge about the inner structure and function of the cell and beyond. All this information requires classification, organization and management. Data maintained on a wiki is highly complex when compared with most other domains or applications. Definitions of such data must thus be able to represent a complex substructure of data as well as relationships and to ensure that information is not lost during data modeling. A wiki information systems must be able to represent any level of complexity in any data schema, relationship, or schema substructure. The amount and range of variability in data store in a wiki is high. Therefore, the systems handling these data should be flexible in data types and values. Defining and representing complex queries is extremely important to the objectives and goals of Wikibits. Hence, our systems will support complex queries and provide tools for building such queries. Thus, we feel Wikibits will benefit the most through a NoSQL database to allow scalability, reliability, flexibility and ease of configuration. The NoSQL structure also synergizes well with our goal for eventual migration of our database onto the blockchain (Wikichain, see section 4.3).

    • Hybridized wiki

    Parallel to the increase of data inputs from users, Wikibits will be developing our own blockchain tailored for information storage. During the initial transaction from traditional distributed database management system (DDBMS) to a blockchain based system, Wikibits will utilize a hybridized approach. Only critically evaluated community inputs will be transcribed onto the blockchain at this stage with all data still managed by the DDBMS. During this period, Wikichain will be beta tested, scrutinized and enhanced for the eventual migration from DDBMS onto the blockchain.

    •  Wikichain

    Using a traditional blockchain based structure for information storage could be challenging. For example, when it comes to information storage, Bitcoin is plagued with issues related to throughput, latency, capacity and network bandwidth. For Wikichain, rather than trying to scale up blockchain technology, we will hybridize the characteristics of a “big data" distributed database and blockchain characteristics. This will avoid the technology choices that plague Bitcoin, such as full replication. We will build Wikichain on top of an enterprise-grade distributed databases, from which Wikichain will inherit high throughput, high capacity, a full-featured NoSQL query language and efficient querying. Nodes can be added to increase throughput and capacity. Since the big data databases has its own built-in consensus algorithm to tolerate benign faults, we will leverage the existing solution. We will let the “tried-and-true” algorithm to decide which transactions to write, and what the block order it will be. We will disallow private, peer-to-peer communication between the nodes except via the database’s built-in communication. This will incur great reduction in complexity and security risk [49]. This means that malicious nodes cannot transmit one message to part of the network and different message to other part of the network. Every time a node speaks," all the others can listen.


    We will hybridize the following features between the blockchain and the database
    *  Immutability: the written data is tamper-resistant (forever on the blockchain)
    *  Creation and transference of assets: while on the network, creating and transferring assets will not need a central entity
    *  Decentralized control: an ecosystem where “no one” owns or controls the network

    The decentralized control will be achieved via a DNS-like federation of nodes with voting permissions. Other nodes can connect to read and propose transactions[41]. The voting operates at a layer above the database's built-in consensus. Quorum is a majority of votes. For speed, each block will be written before a quorum of nodes validate and vote on it. Chainication will happen at voting time. Every block will have an id equal to the hash of its transactions, timestamp, voters list and public key of its creator-node. It will also have a cryptographic signature and a list of votes. A block will not include the hash (id) of the previous block when it first gets written. Instead, votes will get appended to the block over time, and each vote will have a “previous-block" attribute equal to the hash (id) of the block that came before it.
    Immutability will be achieved via several mechanisms: shard replication, reversion of disallowed updates or deletes, regular database backups, and cryptographic signing of all transactions, blocks & votes. Any entity with asset-issuance permissions will have the ability to issue an asset; an asset can only be acquired by new owners if they fulfill its cryptographic conditions. This will prevent hackers or compromised system admins in changing the underlying data, and eliminate the risk of single-point-of-failure.

    • Architecture

    Figure . Architecture of Wikichain system. There are two big data distributed databases: a Transaction Set B (left) to take in and assign incoming transactions, and a Blockchain W (right) holding ordered transactions that are transcribed onto the blockchain. The signing nodes running the Wikichain Consensus Algorithm update B, W, and the transactions (txs) between them

    Figure. illustrates the architecture of the Wikichain system. The Wikichain system will presents its API to users as if it is a single blockchain database. However, on the backend, it will actually be consisted of two distributed databases [50], B (transaction set or “backlog") and W (blockchain), connected by the Wikichain Consensus Algorithm (WCA). The WCA will run on each signing node. Non-signing clients may

    connect to Wikichain; depending on permissions they may be able to read, issue assets, transfer assets, and more. Each of the distributed databases, B and W, is a big data database. We will not interfere with the internal workings of each database to leverage the scalability properties of the databases, in addition to features like revision control and benefits like battle-tested code. Each database will be running its own internal Paxos-like consensus algorithm for consistency among the drives.
    The first database holds the “backlog" transactions, an unordered set of transactions B. When a transaction comes in, it will get validated by the receiving node and if it's valid (according to that node), then it will get stored in B. Identical transactions arriving later will be rejected. The receiving node will also randomly assigns the transaction to one of the other nodes.
    There will be N signing nodes. Bi = {ti,1; ti,2,…} is the set of transactions assigned to node i.
    Node i will be running the WCA to process transactions from B as follows: It will move transactions from the unordered set Bi into an ordered list, create a block for the transactions, and put the block into the second database W. W will be an ordered list of blocks where each block has reference to a parent block and its data, that is, a blockchain.
    A signing node can vote on whether it considers a block valid or invalid. To decide, the signing node checks the validity of every transaction in the block, and if it finds an invalid transaction, then the signing node votes that the block is invalid. If the signing node finds no invalid transactions, then it votes that the block is valid.
    Each block will start out as undecided, with no votes from signing nodes. Once there is majority of positive (valid) votes for a block, or a majority of negative (invalid) votes, the block will go from undecided to decided valid or decided invalid, respectively, and voting on the block will stop. Once it is decided, the information will be transcribed onto the Wikichain. This process is similar to the idea of multiple confirmations in Bitcoin blockchain.

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