In an era of knowledge-based economy, commercialized research and globalized competition for talent, the creation of innovation ecosystems and innovation networks is at the forefront of efforts of cities. In this context, public authorities, private organizations, and academics respond to the question of the most promising indicators that can predict innovation with various innovation scoreboards. The current paper aims at increasing the understanding of the existing indicators and complementing the various innovation assessment toolkits, using large datasets from non-traditional sources. The success of both top down implemented innovation districts and community-level innovation ecosystems is complex and has not been well examined. Yet, limited data shed light on the association between indicators and innovation performance at the neighborhood level. For this purpose, the city of Boston has been selected as a case study to reveal the importance of its neighborhood's different characteristics in achieving high innovation performance. The study uses a large geographically distributed dataset across Boston's 35 zip code areas, which contains various business, entrepreneurial-specific, socio-economic data and other types of data that can reveal contextual urban dimensions. Furthermore, in order to express the innovation performance of the zip code areas, new metrics are proposed connected to innovation locations. The outcomes of this analysis aim to introduce a 'Neighborhood Innovation Index' that will generate new planning models for higher innovation performance, which can be easily applied in other cases. By publishing this large-scale dataset of urban informatics, the goal is to contribute to the innovation discourse and enable a new theoretical framework that identifies the linkages among cities' socio-economic characteristics and innovation performance.

翻译：在知识经济、商业化研究与全球人才竞争的时代，创新生态系统与创新网络的建设已成为城市发展的核心议题。在此背景下，公共机构、私人组织与学术界通过各类创新记分牌来回答"哪些指标最能预测创新绩效"这一关键问题。本文旨在运用非常规来源的大规模数据集，深化对现有创新指标的理解，并补充现有创新评估工具。自上而下实施的创新区与社区级创新生态系统的成功机制具有复杂性且尚未得到充分研究，而关于社区层面创新指标与创新绩效关联性的数据尤为有限。为此，本研究选取波士顿市作为典型案例，揭示其不同社区特征在实现高创新绩效中的关键作用。研究采用覆盖波士顿35个邮政编码区的大规模地理分布数据集，涵盖商业、创业特征、社会经济数据及可揭示城市语境维度的其他类型数据。为表征各邮政编码区的创新绩效，本研究提出与创新区位相关的新测量指标。分析成果旨在构建"社区创新指数"——该指数可生成提升创新绩效的新型规划模型，并易于推广至其他案例。通过公开这一大规模城市信息学数据集，本研究旨在推动创新领域学术对话，建立识别城市社会经济特征与创新绩效之间关联的新理论框架。