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ALLDATA 2017 : The Third International Conference on Big Data, Small Data, Linked Data and Open Data

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Link: http://iaria.org/conferences2017/ALLDATA17.html
 
When Apr 23, 2017 - Apr 27, 2017
Where Venice, Italy
Submission Deadline Dec 22, 2016
Notification Due Feb 20, 2017
Final Version Due Mar 15, 2017
Categories    big data   small data   linked data   open data
 

Call For Papers

Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to:

- ALLDATA 2017, The Third International Conference on Big Data, Small Data, Linked Data and Open Data

- KESA 2017, The International Workshop on Knowledge Extraction and Semantic Annotation

The submission deadline is December 5, 2016.

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

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


============== ALLDATA 2017 | Call for Papers ===============


CALL FOR PAPERS, TUTORIALS, PANELS


ALLDATA 2017, The Third International Conference on Big Data, Small Data, Linked Data and Open Data

General page: http://www.iaria.org/conferences2017/ALLDATA17.html

Submission page: http://www.iaria.org/conferences2017/SubmitALLDATA17.html


KESA 2017, The International Workshop on Knowledge Extraction and Semantic Annotation

General page: http://www.iaria.org/conferences2017/KESA.html

Submission page: http://www.iaria.org/conferences2017/KESA.html#SubmitAPaper



Event schedule: April 23 - 27, 2017 - Venice, Italy


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: December 5, 2016


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 2017 Topics (for topics and submission details: see CfP on the site)

Call for Papers: http://www.iaria.org/conferences2017/CfPALLDATA17.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, 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


KESA 2017 Topics (for topics and submission details: see CfP on the site)

Call for Papers: http://www.iaria.org/conferences2017/KESA.html#CallForPapers

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

Shallow Parsing & Knowledge Extraction

Knowledge Discovery and Ontology Learning from unstructured sources

Knowledge Extraction based on (Linguistic) Linked Open Data

Data and text mining on (un)structured knowledge bases

Large-scale information extraction

Models for ontology engineering and resource integration

Tools in aid of NLP tasks and application

Machine learning for natural language

Semantic role labelling

Semantic search

Semantic Representation and Knowledge Acquisition

Cognitive, mathematical and computational models of language processing

Languages, methodologies and tools for representing and managing semantic annotations

Deep Language Processing

Linguistic and NLP Ontologies

Analysis of Ontology Models for Natural Language Texts


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ALLDATA 2017 Committee: http://www.iaria.org/conferences2017/ComALLDATA17.html

KESA 2017 Committee: http://www.iaria.org/conferences2017/KESA.html#Committees

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