A Framework for Linked Data Business Models

M. Vafopoulos
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引用次数: 8

Abstract

Linked Data (LD) are emerging as the potential "killer application" of the third Web era. If they actually become mainstream in the next years depends on how useful will be for the average User. In economic terms, the creation of successful business models to place LD in the market and the resulting revenue streams will support further developments. In this article, the major sources of value and a business model taxonomy for LD are identified. Network effects exist in LD by enabling Web users to build bidirectional and massively processable interconnections among online data and second, these data are critical enablers for existing infrastructure in the government and business spheres. The proposed eleven distinct business model categories are: Public service, Community service, Intelligence, Subscriptions, Sponsorships, Advertising, Marketplace, Affiliate program, Multi-sided platforms, Traffic generation and Data branding. Section I briefly introduces the advent of LD in the Web ecosystem. The next section is about the main question, which is addressed in the present paper. Related literature is reviewed in Section III. The encompassing value source of the Web is specified for LD in Section IV. Section V describes a proposed framework for LD business models and Section VI concludes.
关联数据业务模型框架
关联数据(LD)正在成为第三个网络时代潜在的“杀手级应用”。未来几年它们是否真的成为主流取决于它们对普通用户有多大用处。在经济方面,创造成功的商业模式,将LD推向市场和由此产生的收入流将支持进一步的发展。在本文中,将确定LD的主要价值来源和业务模型分类。网络效应通过允许Web用户在在线数据之间构建双向和大规模可处理的互连而存在于LD中,其次,这些数据是政府和商业领域中现有基础设施的关键推动因素。提出的十一个不同的商业模式类别是:公共服务、社区服务、情报、订阅、赞助、广告、市场、联盟计划、多边平台、流量生成和数据品牌。第一部分简要介绍了Web生态系统中LD的出现。下一节是关于主要问题,这是在本文中解决。第三节回顾了相关文献。Web的价值来源在第四节中为LD指定。第五节描述了LD业务模型的拟议框架,第六节得出结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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