From Data-Intensive Collaboration in Science and Engineering
(W2) Data-Intensive Collaboration in Science and Engineering: Call for Participation
A workshop to be held at CSCW 2012 in Seattle, February 11, 2012.
- Position paper submission deadline:
25 November 2011 Extended to 2 December 2011Submissions closed
- Notification of acceptance: 9 December 2011
- Workshop: 11 February 2012
Science and engineering are facing huge increases in data volumes and shifts toward more data-intensive work. The amount of data being produced is rapidly increasing with the development of new sensing and computer technologies, increasing use of computational simulation, and a move toward larger-scale and more interdisciplinary projects. This trend is affecting not just academic research, but also corporate, government, military, and intelligence work as well. The proliferation of new sensors and increasingly powerful processors is set against the relatively static nature of human cognitive capabilities. This “data deluge” presents challenges for conducting collaborative knowledge work and opportunities to provide better computational and organizational support for that work. This workshop will bring together researchers studying various aspects of collaborative data-intensive work in order to understand these challenges and design systems to support the particular needs of these collaborations.
- Infrastructures for Big Data: We consider “Big Data” in science and engineering not just a matter of large data sets, but also of large-scale and often-distributed processes of data creation, management, use, and curation. Dealing with Big Data requires the development of new cyberinfrastructures. Cyberinfrastructures are large-scale computational and networking infrastructures and the virtual organizations and human infrastructures that support them. We will discuss how to develop technological and organizational arrangements that can realize the potential for new knowledge and collaborations around Big Data while also recognizing and supporting local data practices.
- Interoperability and Standards: Interoperability and standards play a key role in the development of Big Data infrastructures. Fostering collaboration around Big Data requires a means to move data around among different organizations, disciplines and technologies. This interoperability is a function of how data are collected, described, and stored. An important aspect of interoperability is the development of standards. Standards support commonalities across different sites of practice, but can be difficult to implement and develop. Understanding interoperability and standards development and adoption is necessary for effectively supporting data-intensive collaborative work.
- Data-Intensive Collaboration: The third theme for the workshop revolves around supporting new forms of data-intensive collaboration. This involves not only adapting traditional forms of science and engineering to new ways of working, but also enabling new models for large-scale data collaborations including crowdsourcing and citizen science. Many recent scientific contributions have been dependent on social-computational systems that integrate crowdsourcing approaches, engaging large and diverse groups of people, with advanced technologies for supporting the core scientific tasks. Technology-enabled citizen science is making substantive contributions to knowledge production by generating new large-scale data sources and analyses that were previously unimaginable, and which are impractical to produce through other means. At the same time, practitioners creating and managing these projects encounter substantial challenges in technology design, data management and analysis methods suited to the data generated by citizen science. These new forms suggest both challenges and opportunities for managing large data sets. For example, traditional methods for ensuring data quality may not scale well. Use and reuse of large data sets may be complicated by the difficulty of assessing the relevance and reliability of the data. Solving these challenges will require applying theory from virtual organizations, distributed collaboration and online communities.
- Matthew J. Bietz, Dept. of Informatics, University of California Irvine
- Andrea Wiggins, School of Information Studies, Syracuse University
- Mark Handel, The Boeing Company
- Cecilia Aragon, Human Centered Design & Engineering, University of Washington
We welcome submissions of 2-4 page position papers that address one or more of the themes addressed above, or 8-10 page papers that address themes from both this workshop and the Mastering Data-Intensive Collaboration through the Synergy of Human and Machine Reasoning workshop (see Related Workshop below). Papers should be formatted using the standard HCI Archive format and should include an abstract of no more than 150 words. Position papers will be evaluated for originality, significance, quality of research, quality of writing, and contribution to workshop topic diversity. Notice of acceptance will be sent by December 9, 2011. Accepted papers and demos will be made available to all participants prior to the workshop. At least one author from each paper must attend the workshop.
Papers should be submitted by 25 November, 2011 to firstname.lastname@example.org.
Related CSCW 2012 Workshop
There is a complementary workshop at CSCW 2012: W12. Mastering Data-Intensive Collaboration through the Synergy of Human and Machine Reasoning. Both workshops are driven by the same concern with the "data deluge," and both adopt a sociotechnical approach that addressed both social and technological issues. The workshops will be held on successive days so participants can attend either or both workshops.
To help understand the two workshops:
- This workshop (W2) will be held on the first workshop day. It has a broad focus on issues of data-intensive collaboration, and leans more toward social and organizational issues.
- The other workshop (W12) will be held on the second workshop day. It is more narrowly focused on a particular class of technologies and approaches that involve (i) the synergy between human and machine intelligence, and (ii) larger issues surrounding analytical practices and data sharing practices.
The workshops are being organized independently, but share a common theme. The organizers are coordinating our planning so that participants can attend just one or the other, but participants should find it valuable to attend both. We believe our field and community will benefit from the discussion in both workshops, and we encourage participants to attend both days.
To that end, participants who wish to attend both may either submit separate position papers or a single long (8-10 page) paper to both workshops. Long papers should address themes from both workshops, and participants should submit the paper separately to each workshop and indicate that it has also been submitted to the other workshop. The paper will be reviewed independently by each workshop committee. Accepted participants will need to register separately for both workshops.
Interested participants should also check out the other workshop's web site.
Prior Cyberinfrastructure Workshops
This workshop is conceived as part of a series of workshops on HCI and CSCW approaches to cyberinfrastructure and scientific collaboration. Previous workshops were broadly themed, and included:
- CSCW 2008: Designing Cyberinfrastructure to Support Science
- CHI 2009: The Changing Face of Digital Science: New Practices in Scientific Collaborations
- CSCW 2010: The Changing Dynamics of Scientific Collaborations
- HICSS 2011: The Changing Dynamics of Scientific Collaborations