S.I. On the Importance of Semantics in Big Data Integration, Storage, and Processing

[Apologies if you receive multiple copies of this CfP]

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FOUNDATIONS of COMPUTING and DECISION SCIENCES journal

http://fcds.cs.put.poznan.pl/fcds2/

De Gruyter Publisher

https://www.degruyter.com/view/j/fcds

Indexed by: Clarivate Analytics - Emerging Sources Citation Index

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SPECIAL ISSUE:

On the Importance of Semantics in Big Data Integration, Storage, and Processing

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Guest editors:

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Paolo Ceravolo

Universita' degli Studi di Milano, Italy

Robert Wrembel

Poznan University of Technology, Poland

Aims:

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The complexity of Big Data technologies and the variety of knowledge and skills

needed to design Big Data applications have emphasized the relevance of systems

for managing and documenting Big Data architectures. Documentation,

reconfiguration, and verification are crucial tasks for a solid

design of technological solutions, but are only partially supported in the

current landscape of Big Data technologies. Rethinking data and metadata

management in the context of Big Data technologies is then a primary goal for

future research.

Methods, principles, and perspectives developed by the Data Semantics community

can significantly contribute to the aformentioned issues. Solutions for

integrating and querying schema-less data, have received much attention.

Standards for metadata management have been proposed to improve data integration

among silos and to make data more discoverable and accessible through

heterogeneous infrastructures. A further level of application of Data Semantics

principles in Big Data technologies involves Representing Processes, i.e.

the entire pipeline of technologies connected to achieve a specific solution

and to make this representation shareable and verifiable to support a mature

implementation of the Big Data production cycle.

Following the manifesto paper "Big Data Semantics" (J. Data Semantics 7(2),

2018), which identified the important and yet unsolved issues of managing

semantics of Big Data, we continue research on this topic. The aim of this

special issue of FCDS is to promote research on Big Data semantics and to

create a common place for sharing contributions to this topic.

Topics of interest for submission include (but are not limited to):

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Big Data Management

Metadata Management

Big Data Persistence and Preservation

Big Data Quality and Provenance Control

Big Data Storage and Retrieval

Big Data Integration Architectures and Techniques

Data Source Discovery

Big Data Profiling and Semantics Discovery

Querying Heterogeneous Big Data Repositories

Caching and Materializing Query Results

Quality of Big Data Services

Big Data Service Performance Evaluation

Big Data Service Reliability and Availability

Reproducibility of Big Data Services

Verifiability of Big Data Services

Assurance in Big Data Services

Big Data Visualization

Real Time Visualisation

Visualization Analytics for Big Data

Big Social Media Mining

Big Data Security and Privacy

Big Data System Security and Integrity

Big Data Information Security

Privacy-Preserving Big Data Analytics

Usable Security and Privacy for Big Data

Performance of Big Data Architectures

Query Optimization

Optimal Selection of Analytics

Physical Structures

Timetable:

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20 Feb 2019 - paper submission

10 May 2019 - author notification

31 Jul 2019 - revision submission

31 Sep 2019 - final acceptance notification

10 Oct 2019 - camera-ready submission

Submission information:

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* Papers must be submitted via EasyChair using the following address:

https://easychair.org/conferences/?conf=fcdsspecialissue2019

* We encourage using Latex, the FCDS template can be downloaded

from: http://fcds.cs.put.poznan.pl/FCDS/Files/fcds.zip

* Max number of pages: 28 in the FCDS style