PAV ontology: provenance, authoring and versioning

Provenance is a critical ingredient for establishing trust of published scientific content. This is true whether we are considering a data set, a computational workflow, a peer-reviewed publication or a simple scientific claim with supportive evidence. Existing vocabularies such as DC Terms and the W3C PROV-O are domain-independent and general-purpose and they allow and encourage for extensions to cover more specific needs. We identify the specific need for identifying or distinguishing between the various roles assumed by agents manipulating digital artifacts, such as author, contributor and curator. We present the Provenance, Authoring and Versioning ontology (PAV): a lightweight ontology for capturing just enough descriptions essential for tracking the provenance, authoring and versioning of web resources. We argue that such descriptions are essential for digital scientific content. PAV distinguishes between contributors, authors and curators of content and creators of representations in addition to the provenance of originating resources that have been accessed, transformed and consumed. We explore five projects (and communities) that have adopted PAV illustrating their usage through concrete examples. Moreover, we present mappings that show how PAV extends the PROV-O ontology to support broader interoperability. The authors strived to keep PAV lightweight and compact by including only those terms that have demonstrated to be pragmatically useful in existing applications, and by recommending terms from existing ontologies when plausible. We analyze and compare PAV with related approaches, namely Provenance Vocabulary, DC Terms and BIBFRAME. We identify similarities and analyze their differences with PAV, outlining strengths and weaknesses of our proposed model. We specify SKOS mappings that align PAV with DC Terms.Comment: 22 pages (incl 5 tables and 19 figures). Submitted to Journal of Biomedical Semantics 2013-04-26 (#1858276535979415). Revised article submitted 2013-08-30. Second revised article submitted 2013-10-06. Accepted 2013-10-07. Author proofs sent 2013-10-09 and 2013-10-16. Published 2013-11-22. Final version 2013-12-06. http://www.jbiomedsem.com/content/4/1/3

Why and How Your Traceability Should Evolve: Insights from an Automotive Supplier

Traceability is a key enabler of various activities in automotive software and systems engineering and required by several standards. However, most existing traceability management approaches do not consider that traceability is situated in constantly changing development contexts involving multiple stakeholders. Together with an automotive supplier, we analyzed how technology, business, and organizational factors raise the need for flexible traceability. We present how traceability can be evolved in the development lifecycle, from early elicitation of traceability needs to the implementation of mature traceability strategies. Moreover, we shed light on how traceability can be managed flexibly within an agile team and more formally when crossing team borders and organizational borders. Based on these insights, we present requirements for flexible tool solutions, supporting varying levels of data quality, change propagation, versioning, and organizational traceability.Comment: 9 pages, 3 figures, accepted in IEEE Softwar

Metamodel for Tracing Concerns across the Life Cycle

Several aspect-oriented approaches have been proposed to specify aspects at different phases in the software life cycle. Aspects can appear within a phase, be refined or mapped to other aspects in later phases, or even disappear.\ud Tracing aspects is necessary to support understandability and maintainability of software systems. Although several approaches have been introduced to address traceability of aspects, two important limitations can be observed. First, tracing is not yet tackled for the entire life cycle. Second, the traceability model that is applied usually refers to elements of specific aspect languages, thereby limiting the reusability of the adopted traceability model.We propose the concern traceability metamodel (CTM) that enables traceability of concerns throughout the life cycle, and which is independent from the aspect languages that are used. CTM can be enhanced to provide additional properties for tracing, and be instantiated to define\ud customized traceability models with respect to the required aspect languages. We have implemented CTM in the tool M-Trace, that uses XML-based representations of the models and XQuery queries to represent tracing information. CTM and M-Trace are illustrated for a Concurrent Versioning System to trace aspects from the requirements level to architecture design level and the implementation

The Application of Object-Oriented Views to an Engineering Environment.

With the increasing popularity of object-oriented technology, object-oriented database systems are being used in design environments as central repositories. In this thesis, we investigate the role of versioning and the characteristics of design databases in design environments. In an effort to improve the configuration management scheme in a design environment, we also investigate the use of database views as a possible configuration tool. We propose a unified version management scheme that facilitates cooperative team work and show that the use of database views provides a powerful configuration management scheme for a design environment

Version Control in Online Software Repositories

Software version control repositories provide a uniform and stable interface to manage documents and their version histories. Unfortunately, Open Source systems, for example, CVS, Subversion, and GNU Arch are not well suited to highly collaborative environments and fail to track semantic changes in repositories. We introduce document provenance as our Description Logic framework to track the semantic changes in software repositories and draw interesting results about their historic behaviour using a rule-based inference engine. To support the use of this framework, we have developed our own online collaborative tool, leveraging the fluency of the modern WikiWikiWeb

Impliance: A Next Generation Information Management Appliance

ably successful in building a large market and adapting to the changes of the last three decades, its impact on the broader market of information management is surprisingly limited. If we were to design an information management system from scratch, based upon today's requirements and hardware capabilities, would it look anything like today's database systems?" In this paper, we introduce Impliance, a next-generation information management system consisting of hardware and software components integrated to form an easy-to-administer appliance that can store, retrieve, and analyze all types of structured, semi-structured, and unstructured information. We first summarize the trends that will shape information management for the foreseeable future. Those trends imply three major requirements for Impliance: (1) to be able to store, manage, and uniformly query all data, not just structured records; (2) to be able to scale out as the volume of this data grows; and (3) to be simple and robust in operation. We then describe four key ideas that are uniquely combined in Impliance to address these requirements, namely the ideas of: (a) integrating software and off-the-shelf hardware into a generic information appliance; (b) automatically discovering, organizing, and managing all data - unstructured as well as structured - in a uniform way; (c) achieving scale-out by exploiting simple, massive parallel processing, and (d) virtualizing compute and storage resources to unify, simplify, and streamline the management of Impliance. Impliance is an ambitious, long-term effort to define simpler, more robust, and more scalable information systems for tomorrow's enterprises.Comment: This article is published under a Creative Commons License Agreement (http://creativecommons.org/licenses/by/2.5/.) You may copy, distribute, display, and perform the work, make derivative works and make commercial use of the work, but, you must attribute the work to the author and CIDR 2007. 3rd Biennial Conference on Innovative Data Systems Research (CIDR) January 710, 2007, Asilomar, California, US