: Data provenance is becoming increasingly important for biosciences with the advent of large-scale collaborative environments such as the iPlant collaborative, where scientists co...
Current projects that automate the collection of provenance information use a centralized architecture for managing the resulting metadata - that is, provenance is gathered at rem...
: Data Provenance refers to the lineage of data including its origin, key events that occur over the course of its lifecycle, and other details associated with data creation, proce...
Withthe proliferation of database views and curated databases, the issue of data provenance where a piece of data came from and the process by which it arrived in the database is b...
: Data Provenance refers to the “origin”, “lineage”, and “source” of data. In this work, we examine provenance from a semantics perspective and present the W7 model, an...
Many advanced data management operations (e.g., incremental maintenance, trust assessment, debugging schema mappings, keyword search over databases, or query answering in probabil...
Grigoris Karvounarakis, Zachary G. Ives, Val Tanne...
Tracing the lineage of data is an important requirement for establishing the quality and validity of data. Recently, the problem of data provenance has been increasingly addressed...
Abstract. Provenance is information recording the source, derivation, or history of some information. Provenance tracking has been studied in a variety of settings; however, althou...
: In many application areas like e-science and data-warehousing detailed information about the origin of data is required. This kind of information is often referred to as data pro...
Network accountability and forensic analysis have become increasingly important, as a means of performing network diagnostics, identifying malicious nodes, enforcing trust managem...