Huge amount of Data is being generated and transmitted everyday. To be able to deal with this data, extract useful information from it, store it, transmit it, and represent it, intelligent technologies and applications are needed. The International Conference on Intelligent Data Science Technologies and Applications (IDSTA) is a peer reviewed conference that will advance the Data Science field by giving an opportunity for researchers, engineers, and practitioners to present their latest findings in the field. It will also invite key persons in the field to share their current knowledge and their future expectations for the field. Topics of interest for submission include, but are not limited to:

    Data Science and Computer Science
        Big Data
        Social Media Analysis
        Database Management Systems
        Scientific Computing
        Web Analytics
        Web Scraping
        Data Fusion
        Performance Analysis and Evaluation
        Evolutionary Computing and Optimization
        Hybrid Methods
        Granular Computing
        Data Visualization
        Predictive Maintenance
        Internet of Things (IoT)
    Data Science and Artificial Intelligence
        Feature Selection
        Neural Networks
        Computer Vision
        Deep Learning
        Data Mining
        Natural Language Processing
        Sentiment Analysis
        Recommender Systems
        Meta-Learning
        Process Mining
        Text Mining
        Fuzzy Computing
    Data Science and Smart City
        City Data Management
        Smart Traffic
        Surveillance
        Location-Based Services
        Robotics
    Data Science for Applied Public Affairs
        Campaign Management
        Mass Communication Politics
        Political Analysis
        Survey Sampling
    Data Science for Business Analytics
        Stock Market Analysis
        Predictive Analytics
        Business Intelligence
    Data Science for Finance
        Risk Management
        Algorithmic Trading
        Fraud Detection
        Financial Analysis
    Data Science and Sustainability
        Datasets on Sustainability
        Sustainability Modeling
        Energy Sustainability
        Water Sustainability
        Environmental Sustainability
        Risk Analysis
    Data Science and Cybersecurity
        Data Privacy and Security
        Network Security
        Communication Security
        Cryptography
        Fraud Detection
        Blockchain
    Data Science and Environmental Science
        GIS
        Climatographic
        Remote Sensing
        Spatial Data Analysis
        Weather Prediction and Tracking
    Data Science and Biotechnologies
        Gnome Analysis
        Drug Discovery and Screening and Side Effect Analysis
        Structural and Folding Pattern
        Disease Discovery and Classification
        Bioinformatics
        Next-Gen Sequencing
    Data Science in Computer Science Education
    Data Science and Human Behaviour Understanding
    Data Science and Semi-Structured and Unstructured Data
    Data Science and Pattern Recognition
    Data Science andTransparency in Research Data
    Data Science and Data and Information Quality
    Data Science and GPU Computing
    Data Science and Crowdsourcing