In conjunction with ACM SIGKDD Conference on Data Mining and Knowledge Discovery (KDD 2014)
August 24, 2014
New York, USA
The emergence of “big data” – data that are far more voluminous, diverse, and inter-related than we know how to cope with – has resulted in the transformation of many historically data poor disciplines into increasingly data rich disciplines. Much attention has focused on the challenges of management, processing, and analysis of big data. However, while we understand how to automate routine aspects of data management http://clanofthecats.com/ and analytics, humans are still largely responsible for most aspects of the scientific process: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. This state of affairs is simply untenable cialis online cheap if we are http://ippp.org/ to realize the full promise and potential of big data.
Against this background, the workshop focuses on Discovery Informatics, an emerging subfield at the intersection of Artificial Intelligence, Knowledge Discovery and Data Mining, Cyber-Human Systems, and Information Integration and Informatics. Discovery Informatics is concerned with (i) Understanding, formalization, and information processing accounts of, and organizational and social structures and incentives that underpin the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).
The workshop aims to bring together researchers and graduate students to explore the research challenges, opportunities, and recent advances in all aspects of Discovery Informatics, including in particular:
- Representation and modeling languages with precise formal semantics, for describing, sharing, and communicating models, theories, and hypotheses
- Sophisticated approaches to construction of comprehensible and communicable predictive models and discovery of causal mechanisms
- Effective approaches for acquiring and making effective use of background assumptions, hypotheses, knowledge, beliefs and conjectures, arguments, domain expertise, and process descriptions from literature.
- Effective methods for identifying gaps in knowledge and formulating questions
- Effective methods for describing, designing, prioritizing, planning observations and experiments
- Effective methods for constructing comprehensible and communicable predictive models from observations and experiments
- Effective methods for generating, prioritizing and testing hypotheses from data and models.
- Sharable and communicable representations and processes, organizational and social structures and practices that facilitate collaborative discovery
We invite participants to submit full papers (no longer than 8 pages, describing research results) or extended abstracts or position papers (no longer than 2 pages, describing research in progress, research challenges, or perspectives).
Submission deadline: June 7, 2014
Author notification: June 20, 2014
Submission of camera-ready papers: June 27, 2014
Workshop: August 24, 2014