posted by organizer: sunnyway || 712 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

ADAH 2017   Advanced Data Analytics in Health
DMCIT 2017   ACM-2017 International Conference on Data Mining, Communications and Information Technology(DMCIT 2017)--EI
ETHE Blearning 2017   Blended learning in higher education: research findings
SPLASH 2017   ACM SIGPLAN conference on Systems, Programming, Languages and Applications: Software for Humanity
CFC-Data Analytics/Smart Cities 2017   Call for Chapters (Taylor & Francis): Data Analytics Applications for Smart Cities
ICCBDC - ACM 2017   International Conference on Cloud and Big Data Computing (ICCBDC 2017)--Ei Compendex and Scopus
SI-SoftMM 2017   Special Issue on Soft Computing Techniques and Applications on MM Data Analyzing Systems-- Springer Journal of Multimedia Tools and Applications
ICFEM 2017   19th International Conference on Formal Engineering Methods
CFC-BD&IoT 2017   Call for Book Chapters:  Handbook of Research on Big Data Management and the Internet of Things for Improved Health Systems
INIT/AERFAISummerSchoolML 2017   INIT/AERFAI Summer School on Machine Learning