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IEEE Data Engineering Bulletin, Volume 41
Volume 41, Number 1, March 2018
- David B. Lomet:

Letter from the Editor-in-Chief. 1 - Tova Milo:

Letter from the Special Issue Editor. 2
- Daniel Deutch, Nave Frost, Amir Gilad:

Provenance for Non-Experts. 3-14 - Juliana Freire, Fernando Seabra Chirigati:

Provenance and the Different Flavors of Reproducibility. 15-26 - Abdussalam Alawini, Susan B. Davidson, Gianmaria Silvello, Val Tannen, Yinjun Wu:

Data Citation: A New Provenance Challenge. 27-38 - Jane Xu, Waley Zhang, Abdussalam Alawini, Val Tannen:

Provenance Analysis for Missing Answers and Integrity Repairs. 39-50 - Bahareh Sadat Arab, Su Feng, Boris Glavic, Seokki Lee

, Xing Niu, Qitian Zeng:
GProM - A Swiss Army Knife for Your Provenance Needs. 51-62 - Matteo Interlandi, Tyson Condie:

Supporting Data Provenance in Data-Intensive Scalable Computing Systems. 63-73 - Ang Chen, Chen Chen, Lay Kuan Loh, Yang Wu, Andreas Haeberlen, Limin Jia, Boon Thau Loo

, Wenchao Zhou:
Data Center Diagnostics with Network Provenance. 74-85
Volume 41, Number 2, June 2018
- David B. Lomet:

Letter from the Editor-in-Chief. 1 - Guoliang Li:

Letter from the Special Issue Editor. 2
- Michael Stonebraker, Ihab F. Ilyas:

Data Integration: The Current Status and the Way Forward. 3-9 - Chen Chen, Behzad Golshan, Alon Y. Halevy, Wang-Chiew Tan, AnHai Doan:

BigGorilla: An Open-Source Ecosystem for Data Preparation and Integration. 10-22 - Joseph M. Hellerstein, Jeffrey Heer, Sean Kandel:

Self-Service Data Preparation: Research to Practice. 23-34 - AnHai Doan, Pradap Konda, Paul Suganthan G. C., Adel Ardalan, Jeffrey R. Ballard, Sanjib Das, Yash Govind, Han Li, Philip Martinkus, Sidharth Mudgal, Erik Paulson, Haojun Zhang:

Toward a System Building Agenda for Data Integration (and Data Science). 35-46 - Xiaolan Wang, Laura M. Haas, Alexandra Meliou:

Explaining Data Integration. 47-58 - Renée J. Miller, Fatemeh Nargesian, Erkang Zhu, Christina Christodoulakis, Ken Q. Pu, Periklis Andritsos:

Making Open Data Transparent: Data Discovery on Open Data. 59-70 - Luciano Barbosa, Valter Crescenzi, Xin Luna Dong, Paolo Merialdo, Federico Piai, Disheng Qiu, Yanyan Shen, Divesh Srivastava:

Big Data Integration for Product Specifications. 71-81 - Mengchu Cai, Martin Grund, Anurag Gupta, Fabian Nagel, Ippokratis Pandis, Yannis Papakonstantinou, Michalis Petropoulos:

Integrated Querying of SQL database data and S3 data in Amazon Redshift. 82-90 - Donatella Firmani, Sainyam Galhotra, Barna Saha, Divesh Srivastava:

Robust Entity Resolution Using a CrowdOracle. 91-103 - Ju Fan, Guoliang Li:

Human-in-the-loop Rule Learning for Data Integration. 104-115
Volume 41, Number 3, September 2018
- David B. Lomet:

Letter from the Editor-in-Chief. 1 - Alexandra Meliou:

Letter from the Special Issue Editor. 2
- Doris Jung Lin Lee, Aditya G. Parameswaran

:
The Case for a Visual Discovery Assistant: A Holistic Solution for Accelerating Visual Data Exploration. 3-14 - Yeounoh Chung, Sacha Servan-Schreiber, Emanuel Zgraggen, Tim Kraska:

Towards Quantifying Uncertainty in Data Analysis & Exploration. 15-27 - Jun Yang, Pankaj K. Agarwal, Sudeepa Roy, Brett Walenz, You Wu, Cong Yu, Chengkai Li:

Query Perturbation Analysis: An Adventure of Database Researchers in Fact-Checking. 28-42 - Kareem El Gebaly, Guoyao Feng, Lukasz Golab, Flip Korn, Divesh Srivastava:

Explanation Tables. 43-51 - Chuan Lei

, Fatma Özcan, Abdul Quamar, Ashish R. Mittal, Jaydeep Sen, Diptikalyan Saha, Karthik Sankaranarayanan:
Ontology-Based Natural Language Query Interfaces for Data Exploration. 52-63 - Stratos Idreos, Kostas Zoumpatianos, Manos Athanassoulis

, Niv Dayan, Brian Hentschel, Michael S. Kester, Demi Guo, Lukas M. Maas, Wilson Qin, Abdul Wasay, Yiyou Sun:
The Periodic Table of Data Structures. 64-75
Volume 41, Number 4, December 2018
- David B. Lomet:

Farewell. 1-2 - Haixun Wang:

Letter from the Editor-in-Chief. 3 - Joseph E. Gonzalez:

Letter from the Special Issue Editor. 4
- Sebastian Schelter, Felix Bießmann, Tim Januschowski, David Salinas, Stephan Seufert, Gyuri Szarvas:

On Challenges in Machine Learning Model Management. 5-15 - Manasi Vartak, Samuel Madden:

MODELDB: Opportunities and Challenges in Managing Machine Learning Models. 16-25 - Hui Miao, Amol Deshpande:

ProvDB: Provenance-enabled Lifecycle Management of Collaborative Data Analysis Workflows. 26-38 - Matei Zaharia, Andrew Chen, Aaron Davidson, Ali Ghodsi, Sue Ann Hong, Andy Konwinski, Siddharth Murching, Tomas Nykodym, Paul Ogilvie, Mani Parkhe, Fen Xie, Corey Zumar:

Accelerating the Machine Learning Lifecycle with MLflow. 39-45 - Yunseong Lee, Alberto Scolari, Byung-Gon Chun, Markus Weimer, Matteo Interlandi:

From the Edge to the Cloud: Model Serving in ML.NET. 46-53 - Chaitanya K. Baru:

Report from the Workshop on Common Model Infrastructure, ACM KDD 2018. 54-57

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