A major part of Open Data concerns statistics such as economic and social indicators. Statistical data are structured in a multidimensional manner creating data cubes. Recently, National Statistical Institutes and public authorities adopted the Linked Data paradigm to publish their statistical data on the Web. Many vocabularies have been created to enable modeling data cubes as RDF graphs, and thus creating Linked Open Statistical Data (LOSD). However, the creation of LOSD remains a demanding task mainly because of modeling challenges related either to the conceptual definition of the cube, or to the way of modeling cubes as linked data. The aim of this paper is to identify and clarify (a) modeling challenges related to the creation of LOSD and (b) approaches to address them. Towards this end, nine LOSD experts were involved in an interactive feedback collection and consensus-building process that was based on Delphi method. We anticipate that the results of this paper will contribute towards the formulation of best practices for creating LOSD, and thus facilitate combining and analyzing statistical data from diverse sources on the Web.

开放数据的主要部分涉及统计数据，例如经济和社会指标。统计数据以多维方式构造，从而创建数据多维数据集。最近，国家统计局和公共机构采用了链接数据范式，将其统计数据发布到Web上。已经创建了许多词汇表，以将数据多维数据集建模为RDF图，从而创建了链接的开放统计数据（LOSD）。但是，创建LOSD仍然是一项艰巨的任务，这主要是因为建模方面的挑战与多维数据集的概念定义或将多维数据集建模为链接数据的方式有关。本文的目的是确定和澄清（a）与创建LOSD有关的建模挑战，以及（b）解决这些挑战的方法。为此，九位LOSD专家参与了基于Delphi方法的交互式反馈收集和共识建立过程。我们预计，本文的结果将有助于制定创建LOSD的最佳做法，从而有助于组合和分析来自Web上各种来源的统计数据。