The Big Data - Same Humans Problem
Summary: Highlights the “big data—same humans” gap: system-scale gains ignore human cognitive limits for insight. Advocates human-centered scalability through summarization, ranking, personalization, visual analytics, crowdsourcing, and end-to-end pipeline co-design. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Alexandros Labrinidis (University of Pittsburgh)
BibTeX Citation
@inproceedings{labrinidis_cidr15,
address = {Amsterdam, Netherlands},
series = {{CIDR} '15},
title = {{The Big Data - Same Humans Problem}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Labrinidis, Alexandros},
year = {2015}
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