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Heterogeneous Data Management, Polystores, and Analytics for Healthcare

VLDB Workshops, Poly 2020 and DMAH 2020, Virtual Event, August 31 and September 4, 2020, Revised Selected Papers

  • Conference proceedings
  • © 2021

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Overview

Editors:
  1. Vijay Gadepally

    1. Massachusetts Institute of Technology, Lexington, USA

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  2. Timothy Mattson

    1. Intel Corporation, Portland, USA

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  3. Michael Stonebraker

    1. Massachusetts Institute of Technology, Cambridge, USA

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  4. Tim Kraska

    1. Massachusetts Institute of Technology, Cambridge, USA

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  5. Fusheng Wang

    1. Stony Brook University, Stony Brook, USA

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  6. Gang Luo

    1. University of Washington, Seattle, USA

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  7. Jun Kong

    1. Georgia State University, Atlanta, USA

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  8. Alevtina Dubovitskaya

    1. Lucerne Unviersity of Applied Sciences, Rotkreuz, Switzerland

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12633)

Part of the book sub series: Security and Cryptology (LNSC)

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About this book

This book constitutes revised selected papers from two VLDB workshops: The International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2020, and the 6th International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2020, which were held virtually on August 31 and September 4, 2020.

For Poly 2020, 4 full and 3 short papers were accepted from 10 submissions; and for DMAH 2020, 7 full and 2 short papers were accepted from a total of 15 submissions. The papers were organized in topical sections as follows: Privacy, Security and/or Policy Issues for Heterogenous Data; COVID-19 Data Analytics and Visualization; Deep Learning based Biomedical Data Analytics; NLP based Learning from Unstructured Data; Biomedical Data Modelling and Prediction.

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Table of contents (17 papers)

  1. Front Matter

    Pages i-xiii
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  2. Poly 2020: Privacy, Security and/or Policy Issues for Heterogenous Data

    1. Front Matter

      Pages 1-1
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    2. A Polystore Based Database Operating System (DBOS)

      • Michael Cafarella, David DeWitt, Vijay Gadepally, Jeremy Kepner, Christos Kozyrakis, Tim Kraska et al.
      Pages 3-24
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    3. Polypheny-DB: Towards Bridging the Gap Between Polystores and HTAP Systems

      • Marco Vogt, Nils Hansen, Jan Schönholz, David Lengweiler, Isabel Geissmann, Sebastian Philipp et al.
      Pages 25-36
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    4. Persona Model Transfer for User Activity Prediction Across Heterogeneous Domains

      • Takahiro Hara
      Pages 37-41
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    5. PolyMigrate: Dynamic Schema Evolution and Data Migration in a Distributed Polystore

      • Alexander Stiemer, Marco Vogt, Heiko Schuldt, Uta Störl
      Pages 42-53
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    6. An Architecture for the Development of Distributed Analytics Based on Polystore Events

      • Athanasios Zolotas, Konstantinos Barmpis, Fady Medhat, Patrick Neubauer, Dimitris Kolovos, Richard F. Paige
      Pages 54-65
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    7. Towards Data Discovery by Example

      • El Kindi Rezig, Allan Vanterpool, Vijay Gadepally, Benjamin Price, Michael Cafarella, Michael Stonebraker
      Pages 66-71
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    8. The Transformers for Polystores - The Next Frontier for Polystore Research

      • Edmon Begoli, Sudarshan Srinivasan, Maria Mahbub
      Pages 72-77
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  3. DMAH 2020: COVID-19 Data Analytics and Visualization

    1. Front Matter

      Pages 79-79
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    2. Open-World COVID-19 Data Visualization [Extended Abstract]

      • Hyunseung Hwang, Steven Euijong Whang
      Pages 81-84
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  4. DMAH 2020: Deep Learning based Biomedical Data Analytics

    1. Front Matter

      Pages 85-85
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    2. Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles

      • Hong-Jun Yoon, Hilda B. Klasky, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer Doherty et al.
      Pages 87-99
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    3. An Intelligent and Efficient Rehabilitation Status Evaluation Method: A Case Study on Stroke Patients

      • Yao Tong, Hang Yan, Xin Li, Gang Chen, Zhenxiang Zhang
      Pages 100-119
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    4. Multiple Interpretations Improve Deep Learning Transparency for Prostate Lesion Detection

      • Mehmet A. Gulum, Christopher M. Trombley, Mehmed Kantardzic
      Pages 120-137
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  5. DMAH 2020: NLP Based Learning from Unstructured Data

    1. Front Matter

      Pages 139-139
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    2. Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study

      • Xiaoyi Zhang, Rodoniki Athanasiadou, Narges Razavian
      Pages 141-150
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    3. Enhancing Medical Word Sense Inventories Using Word Sense Induction: A Preliminary Study

      • Qifei Dong, Yue Wang
      Pages 151-167
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  6. DMAH 2020: Biomedical Data Modelling and Prediction

    1. Front Matter

      Pages 169-169
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    2. Teaching Analytics Medical-Data Common Sense

      • Tomer Sagi, Nitzan Shmueli, Bruce Friedman, Ruth Bergman
      Pages 171-187
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Other volumes

  1. Heterogeneous Data Management, Polystores, and Analytics for Healthcare

Editors and Affiliations

  • Massachusetts Institute of Technology, Lexington, USA

    Vijay Gadepally

  • Intel Corporation, Portland, USA

    Timothy Mattson

  • Massachusetts Institute of Technology, Cambridge, USA

    Michael Stonebraker, Tim Kraska

  • Stony Brook University, Stony Brook, USA

    Fusheng Wang

  • University of Washington, Seattle, USA

    Gang Luo

  • Georgia State University, Atlanta, USA

    Jun Kong

  • Lucerne Unviersity of Applied Sciences, Rotkreuz, Switzerland

    Alevtina Dubovitskaya

Bibliographic Information

  • Book Title: Heterogeneous Data Management, Polystores, and Analytics for Healthcare

  • Book Subtitle: VLDB Workshops, Poly 2020 and DMAH 2020, Virtual Event, August 31 and September 4, 2020, Revised Selected Papers

  • Editors: Vijay Gadepally, Timothy Mattson, Michael Stonebraker, Tim Kraska, Fusheng Wang, Gang Luo, Jun Kong, … Alevtina Dubovitskaya

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-71055-2

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Softcover ISBN: 978-3-030-71054-5Published: 04 March 2021

  • eBook ISBN: 978-3-030-71055-2Published: 03 March 2021

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIII, 233

  • Number of Illustrations: 13 b/w illustrations, 71 illustrations in colour

  • Topics: Computer Applications, Database Management, Machine Learning

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