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On July 5th 2018 the HCOMP2018 Conference will host its first Research Project Networking Workshop bringing together participants from the worldwide HCOMP community. It will provide participants with a unique opportunity to:

  • Get a compact overview of the broad research landscape in human computation through the lense of academic and industry projects. The session will include short presentations of the vision and goals, and of the resources produced in these projects (datasets, methods, software), which is available to the HCOMP community.
  • Meet the project teams in an informal and inspiring setting to learn about their work, network and discuss future collaborations, joint events, and funding opportunities worldwide.
  • Establish links between relevant projects worldwide to explore synergies and identify areas for knowledge sharing, data and technology transfer and other collaboration opportunities across different countries.
  • Understand the funding environment, both nationally and internationally, exchange experiences and discuss future joint bids across different countries.

We welcome contributions from all types of research projects, from focused academic grants and partnerships between academia and industry to large funded projects and networks worldwide. As the aim of the session is to establish connections between people and organisations working in similar areas nationally and internationally, we are seeking submissions from recent research projects, be that projects that are ongoing, are about to start, or have been completed recently.  

Projects accepted to the session will also be invited to participate in the poster and demo session of HCOMP2018, where they can have greater outreach and receive feedback on their work from a broader audience. Additionally, there will be possibilities to combine the participation in this session with sponsorship benefits. Check the CFP for further details. 

Here are some of the projects and institutions (e.g. Vrije Universiteit Amsterdam, University of Southampton, Technical University Delft, etc) that have confirmed their participation. We will be updating this list on a weekly basis with new projects coming in.

  • QROWD ProjectQROWD is a H2020 Innovation Action, which integrates geographic, transport, meteorological, cross-domain and news data, while efficiently combining algorithms and human computation incorporated in the entire Big Data Value Chain.
  • ReTV ProjectReTV is a H2020 Research and Innovation Action, which addresses the digital media shift with novel services combining machine and human computation for content repurposing, adaptation and recommendation in order to cope with the rapidly changing digital media landscape that continuously redefines the demands and expectations of TV viewers.
  • WDAqua Project — Answering Questions using Web Data is a H2020 Marie Skłodowska-Curie Innovative Training Network, which advances the field of data-driven question answering through a combination of training, research and innovation and demonstrations in e-commerce, public sector information, publishing and smart cities.
  • CrowdTruth Project – The CrowdTruth team works on a methodology that harnesses the diversity in human interpretation (i.e. inter-annotator disagreement) to capture the wide range of opinions and perspectives, and thus, provide more reliable and realistic real-world annotated data for training and evaluating machine learning components. CrowdTruth is a widely used crowdsourcing methodology adopted by industrial partners and public organisations, e.g. Google, IBM, New York Times, The Cleveland Clinic, Crowdynews, The Netherlands Institute for Sound and Vision, Rijksmuseum, and in a multitude of domains, e.g. AI, news, medicine, social media, cultural heritage, social sciences.
  • SocialGlass Project – The SocialGlass team combines machine learning and data science with human computation and user modelling to improve the study of human mobility and migration, energy consumption behaviour, social area analysis, and societal inclusion. It aims to create a powerful digital reflections of urban interaction at scale from dynamic, sparse, and ambiguous data sources, by combining expertise from Data Science, GeoComputation, Applied Spatial Analysis, and Human Computation.

See the full list here.

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