CFP: 3rd International Workshop on Advanced Data Systems Management, Engineering, and Analytics (MegaData): where the Edge meets the Cloud

On behalf of the organizers, I sincerely invite you to consider submitting the results of your recent research to The Third International Workshop on Advanced Data Systems Management, Engineering, and Analytics (MegaData), which will be held in conjunction with the 23rd  IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID2023).

The MegaData objective is to bring together researchers, practitioners, system administrators, system programmers, and others interested in sharing and presenting their perspectives on the effective management of big data systems. The focus of the workshop is on a novel and practical, systems-oriented work, where MegaData, whose moto this year is “MegaData: where the Edge meets the Cloud”, offers an opportunity to showcase the latest advances in this area and discuss and identify future directions and challenges in management and engineering of big data systems.

MegaData covers the area of Big Data operations (management, engineering, and analytics) within Cloud and Edge computing models. It aims to report on the advances and trends in Big Data deployment architectures from both the infrastructure and application levels. Papers presenting recent results, research issues, practical applications, case studies, and industrial implementations are welcome.

Specific topics of interest include, but are not limited, to the following:

  • Resource management and scheduling mechanisms for data systems
  • Auto Scaling and elastic scaling approaches and mechanisms
  • Data governance and privacy of “data in motion” and “data at rest” over edge/cloud
  • Emerging Data deployment models in IoT, IoT-to-Cloud, Edge/fog
  • Federated Learning and edge intelligence for big data systems
  • Advances data storage models, including object stores and key-value stores
  • Techniques for data integrity, availability, reliability, and fault tolerance
  • Big Data workflows (data management, data wrangling, automated workflows)
  • Data pipeline (data lake to analytics, new data stream architectures, edge/fog, cloud enabled solutions)
  • High-performance Data Analytics applications
  • Adaptive offloading techniques among Fog, Edge, and Cloud Computing

Important dates

  • Submission open: December 1st, 2022
  • Paper submission Deadline: January 15th, 2023
  • Acceptance notification: February 10th, 2023
  • Camera-ready submission: March 17th, 2023
  • Conference Dates: May 1st, 2023

We invite original research papers that have not been previously published and are not currently under review for publication elsewhere. Submitted papers should be no longer than 8 pages (including references and appendices) in two-column IEEE template format. Papers need to be submitted through the EasyChair submission portal.

Best papers presented at the workshop will be selected, and the corresponding authors will be invited to submit an extended version of their papers for possible publications in: Special Issue on Emerging Topics in Big Data and Edge Intelligence on Springer Cluster Computing (IF 2.3)

Submit the paper and meet our team in Bangalore, India in May, 2023!

With best wishes,

MegaData organizers – Yaser Jararweh, Feras M. Awaysheh, Moath Jarrah, Anastasija Nikiforova, Sadi Alawadi

International conference on the Intelligent Data Science (IDSTA2021): one conference – a ton of impressions

This November I had another great experience – participation in one of my favorite conferences – International conference on the Intelligent Data Science (IDSTA2021) collocated with Blockchain Computing and Applications (BCCA). Unfortunately, due to the pandemics we were not able to meet each other in person in Tartu, Estonia – a local organizer of this edition. But the organization was still perfect from their side. I was super delighted to serve a publicity chair for this conference for the second time (I mean IDSTA2020 and IDSTA2021).

IDSTA2021
Source: IDSTA2021

In short – 2 days (November 15-16), 50+ talks delivered by very skilled, experienced and knowledgeable researchers ready to establish and develop discussions around their topics during 13 sessions, 4 incredible keynotes delivered by Tarik Taleb, Omer Rana, Helen (Eleni) Karatza, Srijith Rajamohan, Ph.D.. Very lively discussions, insightful presentations and great environment!

Apart of serving as a publicity chair, I act as a reviewer, so I am a part of Program Committee, the session chair (for 2 sessions) and the (co-)author and presenter of two papers. One conference – 5 roles 😀 And what is even cooler is that my efforts have been also noticed by organisers and listed in Message from the General Chairs – it is always pleasant to notice you have been mentioned as a person, who contributed and whose contribution and efforts have been really highly evaluated.

Very briefly on my talks :

  • ShoBeVODSDT: Shodan and Binary Edge based vulnerable open data sources detection tool or what Internet of Things Search Engines know about you” (authored by Artjoms Daskevics and Anastasija Nikiforova) devoted to the study, which proposes a tool for non-intrusive testing of open data sources for detecting their vulnerabilities, called ShoBeVODSDT. It supports the identification of vulnerabilities at early security assessment stages and does not require the implementation of active and possibly disruptive techniques. ShoBeVODSDT uses two IoTSE (Internet of Things Search Engines) – Shodan and Binary Edge – by extending their features with the advanced capabilities built in it. It allows inspecting 8 predefined data sources, representing both rational databases, NoSQL databases and data stores – MySQL, PostgreSQL, MongoDB, Redis, Elasticsearch, CouchDB, Cassandra and Memcached – on their vulnerabilities and their extent. Our observation shows that security features built into the database allow to protect against unauthorized access, but there are databases with low security features, where it is possible to connect to nearly all IP addresses by retrieving information from them. Even more, in some cases the databases, which do not use security mechanisms, have been already compromised.
  • Stakeholder-centred Identification of Data Quality Issues: Knowledge that Can Save Your Business” (authored by Anastasija Nikiforova and Natalija Kozmina), in scope of which (1) we perform a literature analysis to compile a list of the most commonly occurring data quality issues, (2) considering the diversity and quantity of different data quality requirements and/or dimensions, we reduce the list of defects after running a brainstorming session followed by DELPHI analysis involving 12 experts, (3) the resulting list of defects is validated by 30 users with advanced data quality knowledge by means of applying the data quality analysis to real-world data that are freely accessible to all stakeholders (specifically, a pool of 30 open data sets). This leads us to the list of key data quality issues, which may be of advantage to the data holder and the data user giving both a higher level of confidence that the data are error-free and can be used without causing financial losses for business. These requirements, however, are expected to be used as input of the specification for the web-based data quality analysis tool to be developed.

Great event, great people, great emotions and impressions! Thank you, IDSTA2021 and your supportive and super-friendly team!