[dbjapan] Fwd: Deadline Extension: ALLDATA 2020 || February 23 - 27, 2020 - Lisbon, Portugal

[宇田川佳久 <udagaway3 [at] gmail.com>]

日本データベース学会の皆様

　東京情報大学の宇田川と申します。
IARIA主催の ALLDATA 2020 のご案内を転送させて頂きます。
ALLDATAでは、Big, Small, Linked, Openデータ関連の
論文を募集しています。
　投稿締切り：2019年10月26日
　会議開催期間：2020年2月23から27日
　会議開催場所 ：ポルトガル、リスボン市

ALLDATAの他に、下記の国際会議も開かれます。
　　・SOFTENG 2020（ソフトウエアエンジニアリング）
　　・ICONS 2020（システムエンジニアリング）
　　・MMEDIA 2020（マルチメディア）
　　・他
論文査読が丁寧で、幅広い分野の研究発表があるのが特徴です。
ご検討いただけますと幸いです。

---------------------------------
東京情報大学 総合情報学部
　宇田川　佳久
所在地: 〒265-8501
    千葉県千葉市若葉区御成台４-１
URL: http://www.tuis.ac.jp/
E-mail: yu207233 [at] rsch.tuis.ac.jp
----------------------------------

---------- Forwarded message ---------
From: ALLDATA 2020 <invitation [at] iariaprogram.org>

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 2020, The Sixth International Conference on Big Data, Small Data, Linked Data and Open Data

The submission deadline has been extended to October 26, 2019

Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: http://www.iariajournals.org

=================


============== ALLDATA 2020 | Call for Papers ===============

CALL FOR PAPERS, TUTORIALS, PANELS


ALLDATA 2020, The Sixth International Conference on Big Data, Small Data, Linked Data and Open Data

General page: http://www.iaria.org/conferences2020/ALLDATA20.html

Submission page: http://www.iaria.org/conferences2020/SubmitALLDATA20.html


Event schedule: February 23 - 27, 2020 - Lisbon, Portugal


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]

- doctoral forum submissions: [in the proceedings, digital library]


Proposals for:

- mini symposia: see http://www.iaria.org/symposium.html

- workshops: see http://www.iaria.org/workshop.html

- tutorials:  [slide-deck posed on www.iaria.org]

- panels: [slide-deck posed on www.iaria.org]


Submission deadline: October 26, 2019


Sponsored by IARIA, www.iaria.org

Extended versions of selected papers will be published in IARIA Journals:  http://www.iariajournals.org

Print proceedings will be available via Curran Associates, Inc.: http://www.proceedings.com/9769.html

Articles will be archived in the free access ThinkMind Digital Library: http://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: http://www.iaria.org/editorialrules.html


ALLDATA 2020 Topics (for topics and submission details: see CfP on the site)

Call for Papers: http://www.iaria.org/conferences2020/CfPALLDATA20.html

============================================================

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, c
 reating 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.

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 Mode
 ls; 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

------------------------

ALLDATA 2020 Committee: http://www.iaria.org/conferences2020/ComALLDATA20.html










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