The Workshop on Trusted Information in Big Data
brings together scientists, engineers and students for the aim to share experiences, ideas, and research results about Big Data Management and Trust Computing.
The term “Big Data” refers to the continuing massive expansion in the data volume and diversity as well as the speed sand complexity of data processing. The use of big data underpins critical activities in all sectors of our society. Achieving the full transformative potential of big data in this increasingly digital world requires both new data analysis algorithms, handling the dramatic data growth, and, specially, new techniques that ensure the safe management of such data.
The workshop is devoted to present innovative researches,
technologies, methods and techniques related to new concept of Big Data and Trusted Information.
The workshop seeks original contributions in all relevant areas, including but not limited to the topics concerning:
- Trust Models and Algorithms for Big Data Processing
- Trust Management in Big Data
- System architectures for big data analysis
- Benchmarks, metrics, and workload characterization for big data
- Debugging and performance analysis tools for analytics and data-intensive computing
- Implications of data analytics to mobile and embedded systems
- Data management and analytics for vast amounts of unstructured data
- Artificial Intelligence, Evolutionary Agents
- Data Mining, Data Fusion
- Information Extraction, Retrieval, Indexing
- Enabling Technologies (Social Networking, Web 2.0, Geographical Information Systems, Sensors, Smart Spaces, Smart Cities, Context-Aware Computing, Web Services)
Provisional abstract is due for September 21.
Accepted papers will be included in the Conference proceedings and published by IEEE
Computer Society and referenced in IEEE explore and major indexes.