The Third International Conference on Big Data, Small Data, Linked Data and Open Data ALLDATA 2017 April 23 - 27, 2017 - Venice, Italy

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Details:

Colocated with other events part of NexComm 2017 Featuring the symposium: KESA 2017:The International Workshop on Knowledge Extraction and Semantic Annotation Posters will be presented during the conference A Work in Progress track is available for preliminary work A Research Ideas track is available for ideas in early stages A Doctoral Forum track is available for discussing and publishing early PhD thesis research Submission (full paper) Dec. 5 January 18, 2017 Notification February 20 February 26, 2017 Registration March 5 March 10, 2017 Camera ready March 15, 2017 ISSN: 2519-8386 ISBN: 978-1-61208-552-4

Published by IARIA XPS Press Archived in the free access ThinkMindTM Digital Library Prints available at Curran Associates, Inc. Authors of selected papers will be invited to submit extended versions to a IARIA Journal Articles will be submitted to appropriate indexes. conference contact: mp@iaria.org

All tracks/topics are open to both research and industry contributions.

Special Tracks:

SMOD: Social Media vs Open Data: Where Most of Data Are?
Chair and Coordinator: Angelica Lo Duca, PhD, Web Applications for the Future Internet Lab, Institute of Informatics and Telematics National Research Council – Pisa, Italy angelica.loduca@iit.cnr.it

DAPRISE: Privacy and Security Issues in Big Data Management
Chair and Coordinator: Prof. Dr. Venkat N. Gudivada, Department of Computer Science
East Carolina University - Greenville, USA gudivadav15@ecu.edu

 

Tracks:

Challenges in processing Big Data and applications
Data classification: small/big/huge, volume, velocity, veridicity, value, etc; Data properties: syntax, semantics, sensitivity, similarity, scarcity, spacial/temporal, completeness, accuracy, compactness, etc.; Data processing: mining, searching, feature extraction, clustering, aggregating, rating, filtering, etc.; Data relationships: linked data, open data, linked open data, etc. Exploiting big/linked data: upgrading legacy open data, integrating probabilist models, spam detection, datasets for noise corrections, predicting reliability, pattern mining, linking heterogeneous dataset collections, exploring type-specific topic profiles of datasets, efficient large-scale ontology matching etc.; Applications: event-based linked data, large scale multi-dimensional network analysis, error detection of atmospheric data,  exploring urban data in smart cities, studying health fatalities,  estimating the energy demand at real-time in cellular networks, multilingual word sense disambiguation, creating open source tool for semantically enriching data, etc.

Big Data
Big data foundations; Big data architectures; Big data semantics, interoperability, search and mining; Big data transformations, processing and storage; Big Data management lifecycle, Big data simulation, visualization, modeling tools, and algorithms; Reasoning on Big data; Big data analytics for prediction; Deep Analytics; Big data and cloud technologies; Big data and Internet of Things; High performance computing on Big data; Scalable access to Big Data; Big data quality and provenance, Big data persistence and preservation; Big data protection, integrity, privacy, and pseudonymisation mechanisms; Big data software (libraries, toolkits, etc.); Big Data visualisation and user experience mechanisms; Big data understanding (knowledge discovery, learning, consumer intelligence); Unknown in large Data Graphs; Applications of Big data (geospatial/environment, energy, media, mobility, health, financial, social, public sector, retail, etc.); Business-driven Big data; Big Data Business Models; Big data ecosystems; Big data innovation spaces; Big Data skills development; Policy, regulation and standardization in Big data; Societal impacts of Big data

Small Data
Social networking small data; Relationship between small data and big data; Statistics on Small data; Handling Small data sets; Predictive modeling methods for Small data sets; Small data sets versus Big Data sets; Small and incomplete data sets; Normality in Small data sets; Confidence intervals of small data sets; Causal discovery from Small data sets; Deep Web and Small data sets; Small datasets for benchmarking and testing; Validation and verification of regression in small data sets; Small data toolkits; Data summarization

Linked Data
RDF and Linked data; Deploying Linked data; Linked data and Big data; Linked data and Small data; Evolving the Web into a global data space via Linked data; Practical semantic Web via Linked data; Structured dynamics and Linked data sets; Quantifying the connectivity of a semantic Linked data; Query languages for Linked data; Access control and security for Linked data; Anomaly detection via Linked data; Semantics for Linked data; Enterprise internal data 'silos' and Linked data; Traditional knowledge base and Linked data; Knowledge management applications and Linked data; Linked data publication; Visualization of Linked data; Linked data query builders; Linked data quality

Open Data
Open data structures and algorithms; Designing for Open data; Open data and Linked Open data; Open data government initiatives; Big Open data; Small Open data; Challenges in using Open data (maps, genomes, chemical compounds, medical data and practice, bioscience and biodiversity); Linked open data and Clouds; Private and public Open data; Culture for Open data or Open government data; Data access, analysis and manipulation of Open data; Open addressing and Open data; Specification languages for Open data; Legal aspects for Open data; Open Data publication methods and technologies, Open Data toolkits; Open Data catalogues, Applications using Open Data; Economic, environmental, and social value of Open Data; Open Data licensing; Open Data Business models; Data marketplaces