ALLDATA 2021 - The Seventh International Conference on Big Data, Small Data, Linked Data and Open Data

INVITATION:
===
Please consider to contribute to and/or forward to the appropriate
groups the following opportunity to submit and publish original
scientific results to:
- ALLDATA 2021, The Seventh International Conference on Big Data, Small
Data, Linked Data and Open Data
ALLDATA 2021 is scheduled to be April 18 - 22, 2021 in Porto, Portugal
under the NexComm 2021 umbrella.
The submission deadline is January 19, 2021.
Authors of selected papers will be invited to submit extended article
versions to one of the IARIA Journals: https://www.iariajournals.org
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=== ALLDATA 2021 | Call for Papers ===
CALL FOR PAPERS, TUTORIALS, PANELS
ALLDATA 2021, The Seventh International Conference on Big Data, Small
Data, Linked Data and Open Data
General page: https://www.iaria.org/conferences2021/ALLDATA21.ht...
Submission page: https://www.iaria.org/conferences2021/SubmitALLDAT...
Event schedule: April 18 - 22, 2021
Contributions:
- regular papers [in the proceedings, digital library]
- short papers (work in progress) [in the proceedings, digital library]
- ideas: two pages [in the proceedings, digital library]
- extended abstracts: two pages [in the proceedings, digital library]
- posters: two pages [in the proceedings, digital library]
- posters: slide only [slide-deck posted at www.iaria.org]
- presentations: slide only [slide-deck posted at www.iaria.org]
- demos: two pages [posted at www.iaria.org]
Submission deadline: January 19, 2021
Extended versions of selected papers will be published in IARIA
Journals: https://www.iariajournals.org
Print proceedings will be available via Curran Associates, Inc.:
https://www.proceedings.com/9769.html
Articles will be archived in the free access ThinkMind Digital Library:
https://www.thinkmind.org
The topics suggested by the conference can be discussed in term of
concepts, state of the art, research, standards, implementations,
running experiments, applications, and industrial case studies. Authors
are invited to submit complete unpublished papers, which are not under
review in any other conference or journal in the following, but not
limited to, topic areas.
All tracks are open to both research and industry contributions, in
terms of Regular papers, Posters, Work in progress,
Technical/marketing/business presentations, Demos, Tutorials, and Panels.
Before submission, please check and comply with the editorial rules:
https://www.iaria.org/editorialrules.html
ALLDATA 2021 Topics (for topics and submission details: see CfP on the site)
Call for Papers: https://www.iaria.org/conferences2021/CfPALLDATA21...
===
ALLDATA 2021 Tracks (topics and submission details: see CfP on the site)
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.
Advanced topics in Deep/Machine learning
Distributed and parallel learning algorithms; Image and video coding;
Deep learning and Internet of Things; Deep learning and Big data; Data
preparation, feature selection, and feature extraction; Error resilient
transmission of multimedia data; 3D video coding and analysis; Depth map
applications; Machine learning programming models and abstractions;
Programming languages for machine learning; Visualization of data,
models, and predictions; Hardware-efficient machine learning methods;
Model training, inference, and serving; Trust and security for machine
learning applications; Testing, debugging, and monitoring of machine
learning applications; Machine learning for systems.
Approaches for Data/Big Data processing using Machine Learning
Machine learning models (supervised, unsupervised, reinforcement,
constrained, etc.); Generative modeling (Gaussian, HMM, GAN, Bayesian
networks, autoencoders, etc.); Explainable AI (feature importance, LIME,
SHAP, FACT, etc.); Bayesian learning models; Prediction uncertainty
(approximation learning, similarity); Training of models (hyperparameter
optimization, regularization, optimizers); Active learning (partially
labels datasets, faulty labels, semi-supervised); Applications of
machine learning (recommender systems, NLP, computer vision, etc.); Data
in machine learning (no data, small data, big data, graph data, time
series, sparse 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
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ALLDATA 2021 Committee:
https://www.iaria.org/conferences2021/ComALLDATA21...
Publicity Chairs
Lorena Parra, Universitat Politecnica de Valencia, Spain
Jose Luis García, Universitat Politecnica de Valencia, Spain
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