1,721,313 research outputs found
ProvStore: a public provenance repository
No full textProvStore is the first online public provenance repository supporting the new PROV standards by W3C. It allows users and applications to store and (optionally) publish the provenance of their data on the Web. Provenance documents can be transformed, visualized, and shared in various serializations, with all the functionality also available to automated applications via a RESTful API (OAuth supported)
Jean-Luc Moreau La Kanteletar, 1972
No full textJean-Luc Moreau La Kanteletar, 1972. In: Littératures 21,1974. Paroles et musique. p. 196
Jean-Luc Moreau La Kanteletar, 1972
No full textJean-Luc Moreau La Kanteletar, 1972. In: Littératures 21,1974. Paroles et musique. p. 196
The Foundations for Provenance on the Web
No full textProvenance, i.e., the origin or source of something, is becoming an important concern, since it offers the means to verify data products, to infer their quality, to analyse the processes that led to them, and to decide whether they can be trusted. For instance, provenance enables the reproducibility of scientific results; provenance is necessary to track attribution and credit in curated databases; and, it is essential for reasoners to make trust judgements about the information they use over the Semantic Web. As the Web allows information sharing, discovery, aggregation, filtering and flow in an unprecedented manner, it also becomes very difficult to identify, reliably, the original source that produced an information item on the Web. Since the emerging use of provenance in niche applications is undoubtedly demonstrating the benefits of provenance, we contend that provenance can and should reliably be tracked and exploited on the Web, and we survey the necessary foundations to achieve such a vision. Using multiple data sources, we have compiled the largest bibliographical database on provenance so far. This large corpus allows us to analyse emerging trends in the research community. Specifically, using the CiteSpace tool, we identify clusters of papers that constitute research fronts, from which we derive characteristics that we use to structure our foundational framework for provenance on the Web. We note that such an endeavour requires a multi-disciplinary approach, since it requires contributions from many computer science sub-disciplines, but also other non-technical fields given the human challenge that is anticipated. To develop our vision, it is necessary to provide a definition of provenance that applies to the Web context. Our conceptual definition of provenance is expressed in terms of processes, and is shown to generalise various definitions of provenance commonly encountered. Furthermore, by bringing realistic distributed systems assumptions, we refine our definition as a query over assertions made by processes. Given that the majority of work on provenance has been undertaken by the database, workflow and e-science communities, we review some of their work, contrasting approaches, and focusing on important topics we believe to be crucial for bringing provenance to the Web, such as abstraction, collections, storage, queries, workflow evolution, semantics and activities involving human interactions. However, provenance approaches developed in the context of databases and workflows essentially deal with closed systems. By that, we mean that workflow or database management systems are in full control of the data they manage, and track their provenance within their own scope, but not beyond. In the context of the Web, a broader approach is required by which chunks of provenance representation can be brought together to describe the provenance of information flowing across multiple systems. This is the specific purpose of the Open Provenance Vision, which is an approach that consists of controlled vocabulary, serialization formats and interfaces that allow the provenance of individual systems to be expressed, connected in a coherent fashion, and queried seamlessly. In this context, the Open Provenance Model is an emerging community-driven representation of provenance, which has been actively used by some twenty teams to exchange provenance information according to the Open Provenance Vision. Having identified an open approach and a model for provenance, we then look at techniques that have been proposed to expose provenance over the Web. We also study how Semantic Web technologies have been successfully exploited to express, query and reason over provenance. Symmetrically, we also identify how Semantic Web technologies such as RDF underpinning the Linked Data effort bring their own difficulties with respect to provenance. A powerful argument for provenance is that it can help make systems transparent, so that it becomes possible to determine whether a particular use of information is appropriate under a set of rules. Such capability helps make systems and information accountable. To offer accountability, provenance itself must be authentic, and rely on security approaches that we review. We then discuss systems where provenance is the basis of an auditing mechanism to check past processes against rules or regulations. In practice, not all users want to check and audit provenance, instead, they may rely on measures of quality or trust; hence, we review emerging provenance-based approaches to compute trust and quality of data
Security Issues in a SOA-based Provenance System
Full text linkRecent work has begun exploring the characterization and utilization of provenance in systems based on the Service Oriented Architecture (such as Web Services and Grid based environments). One of the salient issues related to provenance use within any given system is its security. Provenance presents some unique security requirements of its own, which are additionally dependent on the architectural and environmental context that a provenance system operates in. We discuss the security considerations pertaining to a Service Oriented Architecture based provenance system. Concurrently, we outline possible approaches to address them
A provenance-aware policy language (cProvl) and a data traceability model (cProv) for the Cloud
No full textProvenance plays a pivotal in tracing the origin of something and determining how and why something had occurred. With the emergence of the cloud and the benefits it encompasses, there has been a rapid proliferation of services being adopted by commercial and government sectors. However, trust and security concerns for such services are on an unprecedented scale. Currently, these services expose very little internal working to their customers; this can cause accountability and compliance issues especially in the event of a fault or error, customers and providers are left to point finger at each other. Provenance-based traceability provides a mean to address part of this problem by being able to capture and query events occurred in the past to understand how and why it took place. However, due to the complexity of the cloud infrastructure, the current provenance models lack the expressibility required to describe the inner-working of a cloud service. For a complete solution, a provenance-aware policy language is also required for operators and users to define policies for compliance purpose. The current policy standards do not cater for such requirement. To address these issues, in this paper we propose a provenance (traceability) model cProv, and a provenance-aware policy language (cProvl) to capture traceability data, and express policies for validating against the model. For implementation, we have extended the XACML3.0 architecture to support provenance, and provided a translator that converts cProvl policy and request into XACML type
The Provenance of Electronic Data
Full text linkIn the study of fine art, provenance refers to the documented history of some art object. Given that documented history, the object attains an authority that allows scholars to appreciate its importance with respect to other works, whereas, in the absence of such history, the object may be treated with some skepticism. Our IT landscape is evolving as illustrated by applications that are open, composed dynamically, and that discover results and services on the fly. Against this challenging background, it is crucial for users to be able to have confidence in the results produced by such applications. If the provenance of data produced by computer systems could be determined as it can for some works of art, then users, in their daily applications, would be able to interpret and judge the quality of data better. We introduce a provenance lifecycle and advocate an open approach based on two key principles to support a notion of provenance in computer systems: documentation of execution and user-tailored provenance queries
Standardisation of Provenance Systems in Service Oriented Architectures --- White Paper
No full textThis White Paper presents provenance in computer systems as a mechanism by which business and e-science can undertake compliance validation and analysis of their past processes. We discuss an open approach that can bring benefits to application owners, IT providers, auditors and reviewers. In order to capitalise on such benefits, we make specific recommendations to move forward a standardisation activity in this domain
Preserving Linked Data Integrity on the Semantic Web by application of techniques from Hypermedia
No full textThis report presents a Literature Review of past work in Hypertext link integrity and current work in the emerging area of Semantic Web link integrity. A design and prototype for a system which applies some ideas from Hypertext link integrity to the Semantic Web is presented alongside plans for future enhancements of this system. In addition other possible avenues of research regarding ideas from traditional Hypertext link integrity are briefly discussed
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