期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2018
卷号：41
期号：1
页码：3
出版社：IEEE Computer Society
摘要：The flourish of data-intensive systems that are geared towards direct use by non-experts, such as NaturalLanguage question answering systems and query-by-example frameworks calls for the incorporation ofprovenance management. Provenance is arguably even more important for such systems than for “clas-sic” database application. This is due to the elevated level of uncertainty associated with the typicalambiguity of user specification (e.g. phrasing questions in Natural Language or through examples). Ex-isting provenance solutions are not geared towards the non-experts, and the typical complexity and sizeof their instances render them ill-suited for this goal. We outline in this paper our ongoing research andpreliminary results, addressing these challenges towards developing provenance solutions that serve toexplain computation results to non-expert users.
