VLDB 2019 Tutorial
The Ever Evolving Online Labor Market: Overview, Challenges and Opportunities
CNRS, Univ. Grenoble Alpes, New Jersey Institute of Technology
Sihem AmerYahia
sihem.ameryahia@cnrs.fr
Senjuti Basu Roy
senjutib@njit.edu
Time: August 28, 4:00 - 5:30 pm, Location: Avalon
Abstract
The goal of this tutorial is to make the audience aware of various discipline-specific research activities that could be characterized to be part of online labor markets and advocate for a unified framework that is interdisciplinary in nature and requires convergence of different research disciplines. We will discuss how such a framework could bring transformative effect on the nexus of humans, technology, and the future of work.
PART I: Applications
In this part, we will describe dierent applications that tap into on-line labor markets. The applications range from free-lancing, crowd-sourcing, citizen science, as well as flash organizations. We will characterize these applications by describing the nature of the type of work/business and workers, thereby highlighting the desirable properties that each must meet.
PART II: Existing Approaches
Computational DB and ML
Non-Computational Social Science, Psychology
Data and Problem Modeling, Solutions, and Impact
This piece of the tutorial will revisit existing efforts from computational and non-computational communities and summarize them along three dimensions : studied problems, propoposed solutions, and their impacts.
PART III: Toward a Unified Framework
Challenges and opportunities in unifying the design of online labor markets
This part is primarily forward looking and aims to discuss the challenges and opportunities that arise from bringing together empirical and computational approaches to unify the design of future online labor markets.
Presenters
Sihem Amer-Yahia: is a CNRS Research Director at the University of Grenoble Alpes where she leads the SLIDE team. Her interests are at in large-scale data management. Before joining CNRS, she was Principal Scientist at the Qatar Computing Research Institute, Senior Scientist at Yahoo! Research and at&t Labs. Sihem has served on the SIGMOD Executive Board, is a member of the VLDB and the EDBT Endowments. She is the Editor-in-Chief of the VLDB Journal and an Associate Editor for Transctions in Data Science. She was PC chair of VLDB 2018. Sihem received her Ph.D. in Computer Science from Paris-Orsay and INRIA in 1999, and her Dipl^ome d'Ingenieur from INI, Algeria. Sihem is co-organizing a Shonan Meeting on the topic of Human-in-the-loop Big Data and AI: Connecting Theories and Practices for a Better Future of Work.
Senjuti Basu Roy: is an Assistant Professor at the New Jersey Institute of Technology. Her broader research interests lie in the area of data and content management with the focus on designing principled algorithms for ``human-in-the-loop'' systems. She was the PC Co-chair of SIGMOD 2018 mentorship track, VLDB 2018 PhD Workshop program, and the IEEE Workshop on Human-in-the-loop Methods and Human Machine Collaboration in BigData (IEEE HMData2017, 2018, 2019) (co-located with IEEE Big data). She has organized NSF workshop on converging human and technological perspectives in crowd-sourcing research and will be co-organizing a Shonan Meeting on the topic of Human-in-the-loop Big Data and AI: Connecting Theories and Practices for a Better Future of Work.