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DOING@ADBIS 2022 : 3rd International Workshop on Intelligent Data – From Data to Knowledge


When Sep 5, 2022 - Sep 5, 2022
Where Torino, Italy
Submission Deadline Jun 1, 2022
Notification Due Jun 24, 2022
Final Version Due Jul 5, 2022
Categories    databases   NLP   machine learning   knowledge representation

Call For Papers

DOING 2022: 3rd International Workshop on Intelligent Data – From Data to Knowledge

September 5, 2022
Torino, Italy
In conjunction with ADBIS 2022


Paper submission: June 1, 2022 at 5 a.m. CET
Notification of acceptance: June 24, 2022
Camera-ready due: July 5, 2022
Workshop day: September 5, 2022


DOING workshop accepts short (limited to 6-8 pages) and long (limited to 12 pages) papers. DOING reserves the right to accept as short papers those submitted as long, describing interesting and innovative ideas but still requiring further technical development. Papers should be written in English, formatted in Latex and present substantially original results. We adopt a double blind review policy: the papers submitted for review MUST NOT contain the authors’ names, affiliations, or any information that may disclose the authors’ identity. Authors should consult Springer’s authors’ guidelines and use their proceedings templates (you can download the templates available on the bottom of that page).

ADBIS 2022 follows a Diversity and Inclusion policy that invites authors to adopt inclusive language in their papers and presentations ( and We also kindly ask all participants to adopt a proper code on conduct (

Accepted papers will be published in the Springer CCIS series and the best papers will be invited to a special issue of the journal Computer Science and Information Systems.

Papers must be submitted via EASY CHAIR :
Track: DOING: Intelligent Data – From Data to Knowledge


The workshop focuses on transforming data into information and then into knowledge. The idea is to gather researchers to discuss two main problems :

- how to extract information from textual data and represent it in knowledge bases;
- how to propose intelligent methods for handling and maintaining these databases with new forms of requests, including efficient, flexible, and secure analysis mechanisms, adapted to the user, and with quality and privacy preservation guarantees.


We invite the submission of work-in-progress that address various aspects of information extraction from textual data, intelligent and efficient interrogation, and maintenance of (large) knowledge bases.
The workshop welcomes submissions of theoretical, technical, experimental, methodological papers, application papers, position papers and papers on experience reports addressing – though not limited to – the following topics:

Artificial intelligence in databases and information systems
Data curation, annotation, and provenance
Data management and analytics
Data mining and knowledge discovery
Data models and query languages
Data quality and data cleansing
Data science (theory and techniques)
Context-aware and adaptive information systems
Constraints extraction from text
Natural language processing
Indexing, query processing and optimization
Information and knowledge extraction
Information integration
Information quality
Graph databases
Knowledge bases (querying, management, evolution and dynamics)
Machine learning for knowledge graph construction, completion, refinement
Machine learning for knowledge and information extraction, for instance, named entity disambiguation, sentiment analysis, relation extraction, or the detection of claims, facts and stances from unstructured documents
Machine Learning in NLP
Management of large volumes of data
Methodologies, models, algorithms, and architectures for applied data science
NLP for Digital Humanities
NLP & Knowledge Graphs
Privacy, trust and security in databases
Query processing and optimization
Question answering over knowledge graphs
Text databases

Preferred Application Domains (but not limited to).

Bio-sciences and healthcare
Environmental issues

DOING workshop is connected to:

DOING@MADICS: action in the MADICS network(
DOING@DIAMS: part of the RTR DIAMS (

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