posted by organizer: sunnyway || 1364 views || tracked by 5 users: [display]

D2D 2016 : The First International Workshop on Data to Decision

FacebookTwitterLinkedInGoogle

Link: http://ssrg.nicta.com.au/Events/conferences/D2D2016/
 
When Feb 3, 2016 - Feb 5, 2016
Where Laguna Hills, California, U.S.A.
Submission Deadline Nov 18, 2015
Notification Due Dec 11, 2015
Final Version Due Jan 10, 2016
Categories    big data   data engineering   distributed system   software engineering
 

Call For Papers

Computing and networking, data collection and analytics have been booming in the recent decades to manifest the coming Big Data era. Nowadays, more and more data are being collected and analyzed by organizations to make critical decisions. However, many challenges remain to be addressed.
One challenge is that it is not easy to track which versions of a data set flow through which versions of the cleaning, transformation and analytics to produce the decisions, especially with constantly updating heterogeneous data sources, complex human-in-the loop data wrangling, and sometimes non-reproducible black-box data analytics and version control of big data;
Another challenge is to support data scientists to easily explore subsets of data locally, to share reproducible versions of their exploration in the team, and finally to transform the successful versions into large-scale deployment for continuously serving the learned insights and models of other decision-making systems.
Yet another challenge is to keep semantically and physically consistence of views among distributed and multiple data stores. This can be seen from many real-life examples. In the machine learning and data mining community, researchers require data to data and data to model links with proper provenance of information. In the scientific computing community, smart and efficient management of large amounts of data going through various computation workflows with some degree of reproducibility is also a must. In large scale distributed systems such as clouds, data management tends to employ multi-store systems where global data are split based on various criteria and then stored into distributed multiple stores, thus making the maintenance of consistency difficult.
In this workshop, we bring together researchers and practitioners to share their novel approaches and experiences of managing data to decision “ pipelines” in a production or exploration environment, the transparency and trustworthiness of decision and data, data processing and tracking for closing the gap between advanced computing and platforms, and data management and engineering for newly emerging challenges and topics.

Related Resources

ICDMML 2019   【ACM ICPS EI SCOPUS】2019 International Conference on Data Mining and Machine Learning
ICDM 2019   19th Industrial Conference on Data Mining ICDM 2019
Data SI Overcoming Data Scarcity in ES 2019   Data Journal Special Issue on Overcoming Data Scarcity in Earth Science
ISCSAI 2018   2018 International Symposium on Computer Science and Artificial Intelligence
CASCH 2019   Computational Approaches to the sustainability of Cultural Heritage
ISBDAI 2018   2018 International Symposium on Big Data and Artificial Intelligence
Special Issue IEEE-TLT 2018   CfP Special Issue IEEE-TLT: Data Capture and Analysis to Support Learning Engagement
AutoML 2018   The Second International Workshop on Automation in Machine Learning and Big Data
Special Issue: IJCA 2018   Special Issue【EI】International Journal of Computers and Applications: Computational Intelligence Technologies for Clinical Decision Support-From Prognosis to Prediction
DSA 2019   The Frontiers in Intelligent Data and Signal Analysis DSA 2019