ProvStore: A Public Provenance Repository

Huynh, Trung Dong; Moreau, Luc

doi:10.1007/978-3-319-16462-5_32

Cited by 22 publications

(19 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…If a designer specifies all the provenance to be generated in an application by means of templates, there is only a need to store sets of bindings and templates. Thus, we could envisage a notion of "provenance repository" [64], in which PROV-compatible provenance is only generated on demand, and is not persisted in that form. Instead, the only information that needs to be captured and stored is templates and sets of bindings.…”

Section: Discussionmentioning

confidence: 99%

A Templating System to Generate Provenance

Moreau

Batlajery

Huynh

et al. 2018

IIEEE Trans. Software Eng.

Self Cite

View full text Add to dashboard Cite

PROV-TEMPLATE is a declarative approach that enables designers and programmers to design and generate provenance compatible with the PROV standard of the World Wide Web Consortium. Designers specify the topology of the provenance to be generated by composing templates, which are provenance graphs containing variables, acting as placeholders for values. Programmers write programs that log values and package them up in sets of bindings, a data structure associating variables and values. An expansion algorithm generates instantiated provenance from templates and sets of bindings in any of the serialisation formats supported by PROV. A quantitative evaluation shows that sets of bindings have a size that is typically 40% of that of expanded provenance templates and that the expansion algorithm is suitably tractable, operating in fractions of milliseconds for the type of templates surveyed in the article. Furthermore, the approach shows four significant software engineering benefits: separation of responsibilities, provenance maintenance, potential runtime checks and static analysis, and provenance consumption. The article gathers quantitative data and qualitative benefits descriptions from four different applications making use of PROV-TEMPLATE. The system is implemented and released in the open-source library ProvToolbox for provenance processing. ! 1 INTRODUCTION P ROVENANCE has gained a lot of traction lately in various areas including the Web, legal notices 1 , climate science 2 , scientific workflows [1], [2], [3], computational reproducibility [4], emergency response [5], medical applications 3 , geospatial domain 4 , art and food. The recent standard PROV [6] of the World Wide Web Consortium defines provenance as "as a record that describes the people, institutions, entities, and activities involved in producing, influencing, or delivering a piece of data or a thing." In an increasing number of applications, provenance has become crucial in making systems accountable, by exposing how information flows in systems, and in helping users decide whether information is to be trusted. Provenance is not restricted to computer systems, it can also be used to describe how objects are transformed and people are involved in a physical system [5].Applications and use cases for provenance are well documented in the literature [7], [8], [9], [10]. They include making systems more auditable and accountable [11], reproducing results [12], deriving trust and classification [13], asserting attribution and generating acknowledgments [14], supporting predictive analytics [13], and facilitating traceability [15]. To enable such a powerful functionality, however, one needs to adapt or write applications, so that they generate provenance information, which can then be exploited to offer new benefits to their users.A number of approaches have been proposed to generate provenance: run-time, compile-time, and retrospectively. Runtime generation typically requires applications to be instrumented, and provenance generated accordingly [16],...

show abstract

Section: Discussionmentioning

confidence: 99%

A Templating System to Generate Provenance

Moreau

Batlajery

Huynh

et al. 2018

IIEEE Trans. Software Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This web application fetches provenance documents directly from a provenance store. The current prototype supports the publicly available provenance store PROVSTORE [11] using the PROVSTORE JQUERY API to retrieve public documents from the PROVSTORE for a certain user. Within the provenance document, the script first looks for activities to determine what kinds of panels need to be displayed.…”

Section: Methodsmentioning

confidence: 99%

“…This information is stored in a provenance database or provenance store. For example, PROVSTORE [11] is publicly available provenance store. Large provenance graphs of long running real world workflows are stored in scalable databases more efficiently (e.g., using graph databases such as NEO4J [12]).…”

Section: Provenance Of Electronic Datamentioning

confidence: 99%

Visualizing the Provenance of Personal Data Using Comics

Schreiber

Struminski

2018

Computers

View full text Add to dashboard Cite

Personal health data is acquired, processed, stored, and accessed using a variety of different devices, applications, and services. These are often complex and highly connected. Therefore, use or misuse of the data is hard to detect for people, if they are not capable to understand the trace (i.e., the provenance) of that data. We present a visualization technique for personal health data provenance using comic strips. Each strip of the comic represents a certain activity, such as entering data using a smartphone application, storing or retrieving data on a cloud service, or generating a diagram from the data. The comic strips are generated automatically using recorded provenance graphs. The easy-to-understand comics enable all people to notice crucial points regarding their data such as, for example, privacy violations.

show abstract

“…Our hypothesis is that the metrics could be used to identify the user or the application that produced a provenance graph. In order to verify this, we analyse the provenance network metrics of provenance documents deposited by the public at ProvStore, which is a public repository for provenance documents where a user can sign up for an account and store their provenance online for sharing or visualisation purposes (Huynh and Moreau 2015). We apply the provenance network analytics method of Sect.…”

Section: Application 1: Identifying Owner Of Provenance Documentsmentioning

confidence: 99%

Provenance Network Analytics

Huynh

Ebden

Fischer

et al. 2018

Data Min Knowl Disc

Self Cite

View full text Add to dashboard Cite

Provenance network analytics is a novel data analytics approach that helps infer properties of data, such as quality or importance, from their provenance. Instead of analysing application data, which are typically domain-dependent, it analyses the data's provenance as represented using the World Wide Web Consortium's domainagnostic PROV data model. Specifically, the approach proposes a number of network metrics for provenance data and applies established machine learning techniques over such metrics to build predictive models for some key properties of data. Applying this method to the provenance of real-world data from three different applications, we show that it can successfully identify the owners of provenance documents, assess the quality of crowdsourced data, and identify instructions from chat messages in an alternate-reality game with high levels of accuracy. By so doing, we demonstrate the different ways the proposed provenance network metrics can be used in analysing data, providing the foundation for provenance-based data analytics.

show abstract

ProvStore: A Public Provenance Repository

Cited by 22 publications

References 3 publications

A Templating System to Generate Provenance

A Templating System to Generate Provenance

Visualizing the Provenance of Personal Data Using Comics

Provenance Network Analytics

Contact Info

Product

Resources

About