Abstract: Human participation in socio-technical systems is overgrowing conventional crowdsourcing where humans solve simple, independent tasks. Novel systems are attempting to leverage humans for more intellectually challenging tasks, involving longer lasting worker engagement and complex collaboration patterns. Controllability of such systems requires different direct and indirect methods of influencing the participating humans. Conventional human organizations, such as companies or institutions, have been using incentives for decades to align the interests of workers and organizations. With the collaborations managed by the socio-technical platforms growing ever more complex and resembling, or even surpassing in complexity, the conventional ones, there is a need to apply advanced incentivizing techniques in the virtual environment as well. However, existing incentive management techniques in use in crowdsourcing/sociotechnical platforms are not suitable for the described (complex or intellectually-challenging) tasks. In addition, existing platforms currently use custom-developed solutions. This approach is not portable, and effectively prevents reuse of common incentive logic and reputation transfer. Consequently, this prevents workers from comparing different platforms, hindering the competitiveness of the virtual labor market and making it less attractive to skilled workers.
This research presents a complete set of models and tools for programmable incentive management for social computing platforms. In particular, it introduces:
(i) A comprehensive, multidisciplinary review of existing literature on incentives as well as an extensive survey of real-world incentive practices in social computing milieu,
(ii) A low-level model of incentives suitable for use in socio-technical systems
(iii) princ – a model and framework for execution of programmable incentive mechanisms, allowing the offering of incentives through a service model.
(iv) pringl – a high-level domain-specific language for encoding complex incentive strategies for socio-technical systems, encouraging a modular approach in building
incentive strategies, cutting down development and adjustment time and creating a basis for development of standardized but tweakable incentives.
The tools are meant to allow system and incentive designers a complete environment for modeling, administering/executing and adjusting a whole spectrum of realistic incentive mechanisms in a privacy-preserving manner. No known comparable systems were known to exist at the time of writing of the thesis.

Citation: PhD Thesis: Ognjen Scekic: Automated Incentive Management for Social Computing – Foundations, Models, Tools and Algorithms, TU Wien, March 2016.

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Abstract: Today’s crowdsourcing systems are predominantly used for processing independent tasks with simplistic coordination. As such, they offer limited support for handling complex, intellectually and organizationally challenging labour types, such as software development. In order to support crowdsourcing of the software development processes, the system needs to enact coordination mechanisms which integrate human creativity with machine support. While workflows can be used to handle highly-structured and predictable labour processes, they are less suitable for software development methodologies where unpredictability is an unavoidable part the process. This is especially true in phases of requirement elicitation and feature development, when both the client and development communities change with time. In this paper we present models and techniques for coordination of human workers in crowdsourced software development environments. The techniques augment the existing Social Compute Unit (SCU) concept-a general framework for management of ad-hoc human worker teams-with versatile coordination protocols expressed in the Lightweight Social Calculus (LSC). This approach allows us to combine coordination and quality constraints with dynamic assessments of software-user’s desires, while dynamically choosing appropriate software development coordination models.

Citation: Dave Murray-Rust, Ognjen Scekic, Petros Papapanagiotou, Hong-Linh Truong, Dave Robertson, Schahram Dustdar: A Collaboration Model for Community-Based Software Development with Social Machines. EAI Endorsed Trans. Collaborative Computing 1(5): e6 (2015).

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Abstract: Novel types of crowdsourcing systems require a wider spectrum of incentives for efficient motivation and management of human workers taking part in complex collaborations. Incentive management techniques used in conventional crowdsourcing platforms are not suitable for more intellectually-challenging tasks. Currently, incentives are custom-developed and managed by each particular platform. This prevents incentive portability and cross-platform comparison. In this paper we present PRINGL – a domain-specific language for programming and managing complex incentive strategies for socio-technical platforms in general. It promotes re-use of proven incentive logic and simplifies modeling, adjustment and enactment of complex incentives for socio-technical systems. We demonstrate its applicability and expressiveness on a set of realistic use-cases and discuss its properties.

Citation: Ognjen Scekic, Hong Linh Truong, Schahram Dustdar: PRINGL – A domain-specific language for incentive management in crowdsourcing. Computer Networks 90: 14-33(2015).

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Abstract: Novel web-based socio-technical systems require incentives for efficient management and motivation of human workers taking part in complex collaborations. Incentive management techniques used in existing crowdsourcing platforms are not suitable for intellectually-challenging tasks; platform-specific solutions prevent both workers from comparing working conditions across different platforms as well as platform owners from attracting skilled workers. In this paper we present PRINGL, a domain-specific language for programming complex incentive strategies. It promotes re-use of proven incentive logic and allows composing of complex incentives suitable for novel types of socio-technical systems. We illustrate its applicability and expressiveness and discuss its properties and limitations.

Citation: Ognjen Scekic, Hong-Linh Truong, Schahram Dustdar, “Managing Incentives in Social Computing Systems with PRINGL”, 15th Intl. Conf. on Web Information Systems Engineering (WISE), Thessaloniki, Greece, October, 2014.

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Abstract: Crowdsourcing is generally used for tasks with minimal coordination, providing limited support for dynamic reconfiguration. Modern systems, exemplified by social machines, are subject to continual flux in both the client and development communities and their needs. To support crowd sourcing of open-ended development, systems must dynamically integrate human creativity with machine support. While workflows can be used to handle structured, predictable processes, they are less suitable for social machine development and its attendant uncertainty. We present models and techniques for coordination of human workers in crowd sourced software development environments. We combine the Social Compute Unit—a model of ad-hoc human worker teams—with versatile coordination protocols expressed in the Lightweight Social Calculus. This allows us to combine coordination and quality constraints with dynamic assessments of end-user desires, dynamically discovering and applying development protocols.

Citation: Dave Murray-Rust, Ognjen Scekic, Hong-Linh Truong, Dave Robertson and Schahram Dustdar. A Collaboration Model for Community-Based Software Development with Social Machines. 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, 22-25 Oct, Miami, FL, USA, 2014.

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Abstract: Hybrid and Diversity-Aware Collective Adaptive Systems(HDA-CAS) form a broad class of highly distributed systems comprising a number of heterogeneous human-based and machine-based computing(service) units. These units collaborate in ad-hoc formed, dynamically-adaptive collectives. The flexibility of these collectives makes them suit-able for processing elaborate tasks, but at the same time, building a system to support diverse communication types in such collectives is challenging. In this paper, we address the fundamental communication challenges for HDA-CAS. We present the design of a middleware for virtualizing communication within and among collectives of diverse types of service units. The middleware is able to handle numerous, intermittently available, human and software-based service units, and manages the notion of collectivity transparently to the programmer. A prototype implementation for validation purpose is also provided.

Citation: Philipp Zeppezauer, Ognjen Scekic, Hong-Linh Truong, and Schahram Dustdar. Virtualizing Communication for Hybrid and Diversity-Aware Collective Adaptive Systems. 10th International Workshop on Engineering Service-Oriented Applications (WESOA’14), 3 Nov, Paris, France, 2014.

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Abstract: Hybrid Diversity-aware Collective Adaptive Systems (HDA-CAS) is a new generation of socio-technical systems where both humans and machine peers complement each other and operate collectively to achieve their goals. These systems are characterized by the fundamental properties of hybridity and collectiveness, hiding from users the complexities associated with managing the collaboration and coordination of hybrid human/machine teams. In this paper we present the key programming elements of the SmartSociety HDA-CAS platform. We first describe the overall platform’s architecture and functionality and then present concrete programming model elements – Collective-based Tasks (CBTs) and Collectives, describe their properties and show how they meet the hybridity and collectiveness requirements. We also describe the associated Java language constructs, and show how concrete use-cases can be encoded with the introduced constructs.

Citation: O. Scekic, T. Schiavinotto, D. I. Diochnos, M. Rovatsos, H.-L. Truong, I. Carreras, S. Dustdar, Programming Model Elements for Hybrid Collaborative Adaptive Systems, 1st IEEE International Conference on Collaboration and Internet Computing (CIC’15), 27-30 October 2015, Hangzhou, China.

Citation: http://bit.ly/1p8SJOP

Abstract: Society is moving towards a socio-technical ecosystem in which physical and virtual dimensions of life are intertwined and where people interactions ever more take place with or are mediated by machines. Hybrid Diversity-aware Collective Adaptive Systems (HDA-CAS) is a new generation of sociotechnical systems where humans and machines synergetically complement each other and operate collectively to achieve their goals. HDA-CAS introduce the fundamental properties of hybridity and collectiveness, hiding from the users the complexities associated with managing the collaboration and coordination of machine and human computing elements. In this paper we present an HDA-CAS system called SmartSociety, supporting computations with hybrid human/machine collectives. We describe the platform’s architecture and functionality, validate it on two real-world scenarios involving human and machine elements and present a performance evaluation.

Citation: O. Scekic, D. Miorandi, T. Schiavinotto, D. I. Diochnos, A. Hume, R. Chenu-Abente, H.-L. Truong, M. Rovatsos, I. Carreras, S. Dustdar, F. Giunchiglia, SmartSociety — A Platform for Collaborative People-Machine Computation, The 8th IEEE International Conference on Service Oriented Computing & Applications (SOCA’15), 19-21 October 2015, Rome, Italy.

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Download the book here (PDF)

Find the HTML version of the book here (HTML)

HCC, Human-Computer Confluence, is an ambitious research program (funded under FP7-ICT) studying how the emerging symbiotic relation between humans and computing devices can enable radically new forms of sensing, perception, interaction, and understanding. The horizontal character of HCC makes it a fascinating and fertile interdisciplinary field, but it can also compromise its growth, with researchers scattered across disciplines and groups worldwide. A coordination activity promoting discipline connect, identity building and integration while defining future research, education and policy directions is needed at the regional, national, European and international level.

The HCC research agenda book “Human Computer Confluence – The Next Generation Humans and Computers Research Agenda” reflects the state of the research agenda as of October 2013. It is published under the acronym “Th. Sc. Community” (“The Scientific Community”), standing for a representative blend of the top leading scientists worldwide in this field. It presents a collection of 26 research challenge position statements solicited via the Solicitation Portal, and is publicly available to the whole scientific community for commenting, assessment and consensus finding.

SmartSociety members that have contributed to this publication include Fausto Giunchiglia, Stuart Anderson, Mark Hartswood, Schahram Dustdar, Ognjen Šćekić and Hong-Linh Truong.

Version

19.0, last change 16. 01. 2014

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Lead editor / coordinator

Univ. Prof. Dr. Alois Ferscha
Institute for Pervasive Computing
Johannes Kepler University Linz
Altenberger Straße 69
A-4040 Linz
Email: ferscha@pervasive.jku.at

Assistant editor

Michael Matscheko

Copyright

© Institute for Pervasive Computing, Johannes Kepler University Linz, 2014

Copyright of each article stays with the stated authors. Reproduction, for personal use or for further non-commercial or commercial dissemination, of any part of this document is subject to authorisation from the respective copyright holder.

Acknowledgments

This work was supported under the FP7 ICT FET (Future Enabling Technologies) programme of the European Commission under grant agreement No 258063 (HC2).

ISBN 978-3-200-03344-3

Abstract. Information systems are becoming ever more reliant on different forms of social computing, employing individuals, crowds or assembled teams of professionals. With humans as first-class elements, the success of such systems depends heavily on how well we can motivate people to act in a planned fashion. Incentives are an important part of human resource management, manifesting selective and motivating effects. However, support for defining and executing incentives in today’s information systems is underdeveloped, often being limited to simple, per-task cash rewards. Furthermore, no systematic approach to program incentive functionalities for this type of platforms exists.

In this paper we present fundamental elements of a framework for programmable incentive management in information systems. These elements form the basis necessary to support modeling, programming, and execution of various incentive mechanisms. They can be integrated with different underlying systems, promoting portability and reuse of proven incentive strategies. We carry out a functional design evaluation by illustrating modeling and composing capabilities of a prototype implementation on realistic incentive scenarios.

Keywords: rewards, incentives, social computing, crowdsourcing.

doi: http://dx.doi.org/10.1007/978-3-642-38709-8_44

Citation: Ognjen Scekic, Hong-Linh Truong, Schahram Dustdar, “Programming Incentives in Information Systems”, 25th International Conference on Advanced Information Systems Engineering(CAiSE’13), Springer-Verlag, Valencia, Spain, 17-21 June, 2013.

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Abstract. Conventional incentive mechanisms were designed for business environments involving static business processes and a limited number of actors. They are not easily applicable to crowdsourcing and other social computing platforms, characterized by dynamic collaboration patterns and high numbers of actors, because the effects of incentives in these environments are often unforeseen and more costly than in a well-controlled environment of a traditional company.

In this paper we investigate how to design and calibrate incentive schemes for crowdsourcing processes by simulating joint effects of a combination of different participation and incentive mechanisms applied to a working crowd. More specifically, we present a simulation model of incentive schemes and evaluate it on a relevant real-world scenario. We show how the model is used to simulate different compositions of incentive mechanisms and model parameters, and how these choices influence the costs on the system provider side and the number of malicious workers.

Keywords: rewards, incentives, crowdsourcing, social computing, collective adaptive systems.

doi: http://dx.doi.org/10.1007/978-3-642-41030-7_11

Citation: Ognjen Scekic, Christoph Dorn, Schahram Dustdar, “Simulation-Based Modeling and Evaluation of Incentive Schemes in Crowdsourcing Environments”, 21st International Conference on Cooperative Information Systems (CoopIS’13), September 11-13, 2013, Graz, Austria.

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Introduction. Incentives and rewards help align the interests of employees and organizations. They first appeared with the division of labor and have since followed the increasing complexity of human labor and organizations. As a single incentive measure always targets a specific behavior and sometimes additionally induces unwanted responses from workers, multiple incentives are usually combined to counteract the dysfunctional behavior and produce  desired results. Numerous studies have shown the effectiveness of different incentive mechanisms and their selective and motivational effects. Their importance is reflected in the fact that most big and mid-size companies employ some kind of incentive measures.

Expansion of social computing will include not only better exploitation of crowdsourcing but also solutions that extend traditional business processes; increasing research interest seems to confirm the trend. Several frameworks aiming to support such new collaboration models are being developed (such as socially enhanced computing). These new forms of social computing are intended to support greater task complexity, more intelligent task division, complex organizational and managerial structures for virtual teams, and virtual “careers.” With envisioned changes, incentives will also gain importance and complexity to address workers’ dysfunctional behavior. This new emphasis calls for automated ways of handling incentives and rewards. However, the social computing market is dominated by flat and short-lived organizational structures, employing a limited number of simple incentive mechanisms. That is why we view the state of the social computing market as an opportunity to add novel ways of handling incentives and rewards.

Here, we analyze incentive mechanisms and suggest how they can be used for next-generation social computing. We start with a classification of incentive mechanisms in the literature and in traditional business organizations, then identify elements that can be used as building blocks for any composite incentive mechanism and show the same elements are also used in social computing, even though the resulting schemes lack the complexity needed to support advanced business processes; we conclude with our vision
for future developments.

doi: http://doi.acm.org/10.1145/2461256.2461275

Citation: Ognjen Scekic, Hong-Linh Truong, Schahram Dustdar, “Incentives and Rewarding in Social Computing”, Communications of the ACM, Vol. 65, No. 6, pp. 72-82.

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