CrowdPrecision High-Quality Crowdsourcing Service Powered by Blockchain

Chapter 1:


Team Members

Thomas Tran-Gia/Team Leader

Thomas has five years of experience working in Crowdsourcing Technology. He is a programmer of, where he works on various aspects of Crowdsourcing, including worker quality control, security enhancement and campaign management. Since joining the Crowdsourcing business, he has become used to working in globally distributed international teams, making him the perfect team leader.

Andreas Schütz/Blockchain Advisor

Andreas has an M.Sc. in Information Systems and fell in love with Blockchain in 2011. He has been giving Blockchain workshops since 2016. He also loves to write articles for his website www.etherbasics. com, which has about 30,000 visitors every month. Besides that, he researches on how his second passion, information security, can be supported by Blockchain. He is also running case studies on the development of smart contracts for campus and e-learning platforms.

Tobias Fertig/Blockchain Programmer

Tobias has an M.Sc. in Computer Science and is a REST expert. He has been developing RESTful APIs for five years. His passion for distributed systems led him to Blockchain Technologies. He has also been a lecturer at the University of Applied Sciences Würzburg-Schweinfurt in Germany since 2014. He lectures on Operation Systems and Distributed Systems and also on Software Engineering, Programming and Blockchain Technologies. He is one of our core developers.

Igor Eisenbraun/Blockchain Business

Igor mined his first bitcoins in 2011 and has been a Blockchain enthusiast ever since. He loves the idea of using a decentralized, unforgeable currency in the digital world. He is co-founder of www.etherbasics. com, which provides fundamentals for Ethereum novices. In recent years he has been able to gain a lot of experience in various Blockchain projects.

Henry Vu/Communication Manager

With a background as a software developer and a business consultant, Henry has been able to gain a deep understanding of Blockchain Technology and its promising advantages from both sides: technical and businesswise. Besides researching and teaching at the University of Applied Sciences Würzburg-Schweinfurt, he also gives seminars and talks on cryptocurrencies and Blockchain.

Phuoc Tran-Gia/Chief Scientific Advisor

Phuoc is a Professor of Computer Science at the University of Würzburg, Germany, where he holds the Chair of Distributed Systems and Computer Networks. He pursues research on performance analysis of Peer-to-Peer mechanisms, Future Internet Architecture and Crowdsourcing Technology. He is a cofounder of several companies, including Infosim and Weblabcenter, and he helps to run the Crowdsourcing platform

Matthias Hirth/Crowdsourcing Expert

Matthias is head of the Future Internet Research group of the Chair of Communication Networks at the University of Würzburg. Since 2010 he has been focusing on the optimization of Crowdsourcing workflows and processes. His work has been published in more than 50 articles in internationally recognized journals and conference publications. He is an active member of the Crowdsourcing research community. Besides his academic activities, he works as a scientific advisor for Crowdsourcing companies.

Leng Yaw-Owe/Business Manager, Asia-Pacific

Leng Yaw-Owe is a Singaporean Entrepreneur in Information Technology. He has started and owned many companies, including the access network platform ASI and the network management software company Infosim Asia-Pacific. His vision is to broaden the use of Crowdsourcing in Asia-Pacific area and to achieve multi-language support for Crowdsourcing.

Wolfgang Stegmann/Business Advisor

Wolfgang is a Statutory Auditor and Tax Consultant in Germany. From 1996-2014 he was Vice-Chairman of DATEV, a major German Tax Consulting Software Company. Previously, 1982-1996, he was a Partner in Ernst & Young, Germany (Audit). Since 2014, he has been an Auditor, Tax and Business Consultant, and since 2017 a Consultant on Tax and Legal Aspects of Blockchain Applications.

Paul Müller/Communication Manager

Paul is a Professor of Computer Science at the University of Kaiserslautern, Germany. He was also Director of the Regional Computing and Data Center. He was responsible for the nationwide G-Lab testbed working on Future Internet. This led him to research on Peer-to-Peer systems and Blockchain Technologies. Since 2017 he has been Blockchain consultant of various banking and governmental organizations.

Karl Klug/Intellectual Property Advisor

Karl is an expert on Information & Communication Technology and Security Architecture, a technologist with a multidisciplinary background. He works as a high-tech consultant and adviser on patenting and patent strategy. For many years he was responsible for the patents and intellectual properties at Siemens ICN Corporation based in Munich area.

Benedikt Glatzl/Business Advisor

With more than 10 years of experience in product and management positions in the startup and tech industry, Benedikt can tap into extensive knowledge about helping organizations to achieve excellence in the fields of products and operations. Before assuming his role as Head of Products & Operations at Parkbob and Ulmon, he worked for Google as a Product Quality Strategist and in Google’s Global Innovation Programs, where he supported executive teams and Google partners in developing innovative solutions for their current problems and needs. He teaches Design Thinking, Prototyping and Lean Operations at various universities and institutions throughout Europe.

Chapter 2:

CrowdPrecision Mission


With the fast evolution of information and communications technology, the Internet has become available almost anywhere and at any time. Smartphones and similar devices have become increasingly essential in everyday life and various kinds have been made readily available in large numbers. The ease of access to such devices has had an immense impact on the number of people around the globe who are interconnected. These global connections enable people to communicate and collaborate across borders instantaneously and at a low cost. That would have been challenging or even impossible a few years ago. Besides enabling easy and fast transfer of information, the Internet has also generated an incredibly huge potential labor force that is available 24/7, globally distributed, and has a highly diverse set of skills.

One approach to access this labor force consisting of global Internet users is Crowdsourcing. Instead of delegating large tasks to dedicated employees, the work is broken down into smaller jobs that can be accomplished independently and are distributed via marketplaces to a large number of online workers. On the one hand, the parallelization leads to a much faster achievement of the tasks. On the other hand, the approach helps to reduce the overall labor costs due to the inclusion of global workers of different salary expectations. Additionally, it further facilitates the flexible scaling of human crowd resources based on current demands, similar to technical cloud infrastructures.

Besides economic aspects, Crowdsourcing also offers a great opportunity for individuals from developing countries, as it introduces channels for safe and well-paid online labor. With its new possibilities for increasing productivity and redefining ways by which businesses carry out projects, Crowdsourcing is already successfully applied in various fields of traditional work, including text production, logo design, programming, and even research and development tasks. Furthermore, it also makes possible the cost-efficient and timely completion of vast numbers of so-called microtasks, which non-expert crowdworkers can complete within a few minutes and without any prior knowledge but which are impossible to perform using algorithmic means. Micro-tasks exhibiting interesting patterns and worker behaviors, for example labeling or tagging a set of objects, are utilized for machine learning and could be used in deep learning. The current approach to understanding crowdsourced human input is vital for the further development of machine learning models and approaches.

The rapid rise in the use of international platforms like Amazon Mechanical Turk (MTurk), Microworkers, and Crowdflower demonstrate the considerable growth of Crowdsourcing in recent years. Consequently, CrowdPrecision aims at combining the success of these traditional Crowdsourcing platform providers with the benefits of current developments in Blockchain Technology and using cryptocurrencies.

Chapter 3:

CrowdPrecision Architecture

Building a Trust-based Microtasking System

Most Crowdsourcing platforms maintain their own workforce and give employers access to these workers through their own interfaces as illustrated in [[REF Figure Classic CS Structure]]. This results in numerous restrictions for both the workers and the employers.

Workers registered on multiple platforms inconveniently have to maintain different work records on each platform. There are no ways to link these records across different providers to produce a unified profile. As a result, even experienced workers have to undergo qualification tests for asecond or third etc. time when registering on a new platform and, therefore, have to rebuild their reputation from scratch.

Accessing a worker’s cross-platform record is virtually impossible for employers because the data are spread over several platforms. Therefore, employers would need to have an account at every platform and would need to find a way to match users. From the employer‘s point of view, there is a restriction in terms of the selection of workers, as they only have access to the workers of the platform they are currently logged in at. If a large group of workers or workers with a very specific

set of skills are required, campaigns have to be separately launched on multiple platforms in order to acquire the required number of participants or workers with the necessary skills. CrowdPrecision aims at developing a meta-platform at a level above the existing commercial providers as illustrated in Figure 3.2. This provides employers with a unified interface for distributing tasks to workers across platforms without the need to access a number of different user accounts and deal with a number of different user interfaces. Additionally, all task ratings are accumulated in CrowdPrecision, enabling the platform to build sophisticated worker profiles including their skill sets and demographic properties as well as giving employers ways to ascertain qualifications and verify their profiles. As CrowdPrecision also enables workers to build a unified profile on the platform, workers can register at different Crowdsourcing platforms but still keep their unified CrowdPrecision task record. This allows them to work on CrowdPrecision tasks on multiple Crowdsourcing platforms without having to undergo new qualification tests.

Existing Crowdsourcing platforms would also benefit from collaborating with CrowdPrecision, as new tasks will be routed to their platform even if only a few workers match the demographic or skill-requirements requested by the employers, as CrowdPrecision will form cross-platform groups.

The integration of existing Crowdsourcing platforms and other crowd providers will be possible through CrowdPrecision‘s RESTful API. This API will allow current providers to enhance their services easily with the benefits of cryptocurrency payments and without major changes to their existing code base. Benefits for the platform providers include an increase in their user base, as new tasks can be submitted to their platforms via CrowdPrecision‘s unified employer interface. Additionally, collaboration with CrowdPrecision will result in a better utilization of their available labor force as even small groups of workers with specialized skills can find appropriate tasks thanks to cross-platform task scheduling. This, in turn, offers great opportunities for CrowdPrecision to quickly develop the kind of huge worker base required for a stable mode of operation. Here, – a large Crowdsourcing platform with almost 1.1 million registered users processing about 9000 tasks per day and having delivered more than 33 million successful tasks so far – has agreed to be our first collaboration partner and crowd provider.

The implementation of CrowdPrecision’s trust and reputation system will be based on the Ethereum Blockchain. All relevant task information, including type of task, remuneration, employer, workers competing for the task and the final assessment of a worker’s submission will be permanently stored on the Blockchain, while sensitive campaign information is stored on our centralized database. This gives both the employers and the workers a deeper insight into the working and employment history of the other partner. This transparency will encourage both parties to work and act more diligently and reliably as their past behavior will have a significant influence on the future availability of new tasks to individual workers or the willingness of workers to accept jobs offered by a particular employer. Despite their work and employment history being made transparent and public, our infrastructure preserves the privacy of workers and employers by keeping sensitive data private, e.g. detailed task descriptions or the concrete data submitted by the worker in response.

Chapter 4:

CrowdPrecision Initial Token Sale

  • What is an Initial Token Sale

When new cryptocurrency projects are launched, they often initiate an event called an Initial Token Sale (ITS). At the ITS, early adopters have the chance to buy the cryptocurrency tokens before they are launched on an official trading platform. For the organizers of the ITS, it provides the opportunity to raise funds in order to realize a new idea or upscale an existing product or service. Crowdfunding through ITSs has gained popularity in the scene of cryptocurrencies in recent years and a large majority of popular projects underwent this process. By now, the process of an ITS is, therefore, well explored. An ITS can last from a few minutes to a few weeks. Adopters that join an ITS early can gain bonuses in the form of extra tokens.

  • Benefits of an Initial Token Sale

Crowdsourcing has become established in recent years and is widely used by a lot of companies in an efficient way. It gives workers access to the global labor market, no matter where in the world they live. It is therefore not surprising that platforms like have gained considerable popularity in recent years. In order to make interoperability possible, it is important to provide a set of APIs for different business models. Blockchain Technology can help to enrich the functionality of existing platforms by establishing interoperability with a joint token and building trust with the help of a platform-independent protocol. In order to overcome these challenges, it is crucial to have additional funds. Moreover, an ITS can help to make the tokens accessible to a large community at an early stage. The community can enrich CrowdPrecision with its ideas right from the start.

  • The CrowdPrecision Initial Token Sale

Chapter 5:

CrowdPrecision Operation Mode

  • Payment Organization

As with traditional Crowdsourcing platforms, workers will be paid by the employers for each successfully completed task. Employers may choose from various pre-implemented task validation mechanisms, including majority voting or plausibility checks, while maintaining the right to a manual final decision. In contrast to many other platforms, CrowdPrecision follows a service-oriented approach that enables both workers and employers to contact the platform’s administrative support to solve disputes.

  • Service-oriented Crowdsourcing

Crowdsourcing is the most rigorously consistent realization of the outsourcing approach, minimizing pricing by breaking work down into smaller tasks and reducing administrative overheads. Due to the vast number of potential crowdworkers, different strategies have evolved to crowdsource even the evaluation of work or the design of the Crowdsourcing jobs themselves. This leads to the impression that distributing work via micro-tasking platforms is self-explanatory and self-organizing.

However, evidence proves that designing Crowdsourcing tasks actually requires a significant amount of prior knowledge and an understanding of the workers and existing challenges. This is also proven by the fact that most present-day major platforms have a full service approach which does not require employers to design the Crowdsourcing tasks at all but which levies significant service charges or fees for platform usage.

CrowdPrecision follows an intermediate approach that enables Crowdsourcing specialists to run Crowdsourcing experiments and specialized tasks with a minimum of administrative services and control by CrowdPrecision, while at the same time supporting novice users with guidance during their first steps in Crowdsourcing to maximize the efficiency of the task design and ascertain fair treatment of the workers. Additionally, CrowdPrecision provides full service models. Here the team’s data science and Crowdsourcing experts will take care of pre- and post-processing the submitted data and designing the Crowdsourcing tasks. Customers will then be given the resulting high-quality data. This differentiated service approach results in an optimal Crowdsourcing experience for all kinds of employers using Crowdsourcing for data processing, human computation tasks and tasks involving human judgement.

Furthermore, CrowdPrecision‘s modular design allows access to a wide range of workers. Basically, there can be two types of worker: 1) Individual workers who register directly with Crowd- Precision or 2) workers registered at a collaborating partner’s platform, e.g. Individual workers registering directly at CrowdPrecision can perform tasks submitted by employers straightaway and receive their payment reduced only by CrowdPrecision‘s service charge. However, the team’s experience shows that building up a crowd from scratch is hard to do.

To overcome this problem, CrowdPrecision also supports the integration of existing Crowdsourcing providers or communities in general. In this case, the existing Crowdsourcing provider can decide whether to add an additional service charge to the task or whether to pay the full price to the worker. This integration helps the collaborating providers to increase the number of available tasks on their platforms, and it consequently also increases their revenue. Additionally, we support the integration of non-monetary worker sources, e.g. forum communities. In this case the forum owner as a central entity will receive the reward for the tasks and can then choose how to use the revenue, e.g. to provide advertisement-free content or new community features.

Following the unified interface approach, CrowdPrecision will also include ways in which workers can create a unified account. If, for example, a worker is registered at different platforms that collaborate with CrowdPrecision, his/her trust and skill ratings will be available on all platforms. Due to CrowdPrecision’s service-oriented approach, the administrative support protects Crowdsourcing workers in cases of disputes and filters out unsatisfactory or unethical work.

Chapter 6:


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Ade Hilman Negara

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