Semantic Web 0 (2012) 1 1 IOS Press Lifecycle models of data-centric systems and domains The Abstract Data Lifecycle Model Editor(s): Werner Kuhn, University of Münster, Germany Solicited review(s): Tomi Kauppinen, University of Münster, Germany; Todd Pehle, Orbis Technologies, USA Knud Möller ∗ DERI, National University of Ireland, Galway E-mail: knud.moeller@deri.org Abstract. The Semantic Web, especially in the light of the current focus on its nature as a Web of Data, is a data-centric system, and arguably the largest such system in existence. Data is being created, published, exported, imported, used, transformed and re-used, by different parties and for different purposes. Together, these actions form a lifecycle of data on the Semantic Web. Understanding this lifecycle will help to better understand the nature of data on the SW, to explain paradigm shifts, to compare the functionality of different platforms, to aid the integration of previously disparate implementation efforts or to position various actors on the SW and relate them to each other. However, while conceptualisations of many aspects of the SW exist, no exhaustive data lifecycle has been proposed. This paper proposes a data lifecycle model for the Semantic Web by first looking outward, and performing an extensive survey of lifecycle models in other data-centric domains, such as digital libraries, multimedia, eLearning, knowledge and Web content management or ontology development. For each domain, an extensive list of models is taken from the literature, and then described and analysed in terms of its different phases, actor roles and other characteristics. By contrasting and comparing the existing models, a meta vocabulary of lifecycle models for data-centric systems — the Abstract Data Lifecycle Model, or ADLM — is developed. In particular, a common set of lifecycle phases, lifecycle features and lifecycle roles is established, as well as additional actor features and generic features of data and metadata. This vocabulary now provides a tool to describe each individual model, relate them to each other, determine similarities and overlaps and eventually establish a new such model for the Semantic Web. Keywords: data, data-centric, lifecycle, Semantic Web 1. Introduction The Semantic Web — a web of data rather than doc- uments, where automatic agents can make sense of in- formation, aiding human users and preventing infor- mation overload — is still a young phenomenon, and at this point in time we cannot yet say what shape and form exactly it will take in the years to come. A crucial * current affiliation: Kasabi, UK, E-mail: knud.moeller@kasabi.com aspect during this development process is a common understanding of the anchor points of what this web of data sets out to be, regardless of specific technolo- gies, languages or systems. Without this understand- ing, there is a danger that individual efforts will be in- compatible, that there is a duplication of efforts or that the effort as a whole will derail. It is therefore nec- essary to establish a comprehensive conceptual model and architecture of the Semantic Web: “the architec- ture of any system is one of the primary aspects to con- sider during design and implementation thereof, and the [. . . ] architecture of the Semantic Web is thus cru- 1570-0844/12/$27.50 c  2012 – IOS Press and the authors. All rights reserved