Skluma: A Statistical Learning Pipeline for Taming Unkempt Data Repositories. Beckman, P., Skluzacek, T. J., Chard, K., & Foster, I. In Proceedings of the 29th International Conference on Scientific and Statistical Database Management, of SSDBM '17, pages 41:1–41:4, New York, NY, USA, 2017. ACM.
Skluma: A Statistical Learning Pipeline for Taming Unkempt Data Repositories [link]Paper  doi  bibtex   
@inproceedings{Beckman:2017:SSL:3085504.3091116,
 author = {Beckman, Paul and Skluzacek, Tyler J. and Chard, Kyle and Foster, Ian},
 title = {Skluma: A Statistical Learning Pipeline for Taming Unkempt Data Repositories},
 booktitle = {Proceedings of the 29th International Conference on Scientific and Statistical Database Management},
 series = {SSDBM '17},
 year = {2017},
 isbn = {978-1-4503-5282-6},
 location = {Chicago, IL, USA},
 pages = {41:1--41:4},
 articleno = {41},
 numpages = {4},
 url = {http://doi.acm.org/10.1145/3085504.3091116},
 doi = {10.1145/3085504.3091116},
 acmid = {3091116},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {data integration, data wrangling, metadata extraction, statistical learning},
}

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