Engineering Agile Big-Data Systems

Abstract

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The New DBpedia Release Cycle: Increasing Agility and Efficiency in Knowledge Extraction Workflows

“…The initial set of data groups are published on the Databus by the MARVIN publishing agent. 3 In addition to the MARVIN agent, there is also the DBpedia agent, which publishes cleaned data artifacts, i.e. syntactically valid.…”

“…At the conceptual level, our work is very related to the "Engineering Agile Big-Data" concepts described in [3] and inspired and based on those particular concepts. Below we discuss the related works to ours and primarily in respect to i) data release cycle and ii) data quality assessment.…”

“…Until 2017, The DBpedia release process has been primarily focused on data quality and size, however, it neglected other two important and desirable goals: productivity and agility (cf. [3] for balancing the magic triangle on quality, productivity and agility The release process was facing massive delays (from 12 to 17 months) with increasing costs of development and lower productivity due to the sole focus on quality and the increased size and complexity. The releases were so large and complex that the DBpedia core team failed to produce them for almost three years (2017-2019).…”