CIVIC-PG Track B: Legacy Building Toolset

传统建筑工具集(LBT)是一个以交互数据可视化为中心的数字平台，允许社区成员集体探索身份、场所的意义，并创建和参与社区资产。目前这种工具和方法没有得到充分的探索，这一点令人担忧，因为公共政策往往是基于政策制定者如何从居民的角度来看待地方的意义。因此，居民们经常发现，收集和组织社区信息以提交给政策制定者是一件具有挑战性的事情，或者当他们对建立的形式的解释仍然不被认可时，他们将面临排斥。LBT旨在实现社区可访问的工具，以大规模、实时和覆盖文化和身份的形式创建社区驱动的对意义的解释。该工具将在俄克拉荷马城东北部开发，这是一个以黑人为主的弱势社区，所获得的知识将传播给美国各地的其他社区使用。通过设想的第二阶段试点项目开发和部署传统建筑工具集(LBT)将把成功的参与方法PhotoVoice和讲故事与可扩展性结合起来，通过直接在地图、时间表和其他数据可视化中进行众包数据编辑和查看。LBT将包括一组由Web服务数据库后端支持的直观交互、以可视化为中心的浏览器内数据编辑和查看应用程序。这些应用程序将支持通过交互手势直接在可视化本身中输入关于人、地点、时间和其他细节的信息。这包括使用照片、视频或音频注释位置、地区和时间的机会。这些应用程序还将支持将信息组织到整合文本、可视化和多媒体注释的故事中。现有的PhotoVoice和讲故事方法通常需要一位亲自组织和领导这一过程的专家。通过以可视化为中心的用户界面，LBT将提供集中化程度较低的收集、组织和管理社区信息的方法。社区将能够更独立于专家开发和使用故事。许多城市设计和规划项目可能仍然受益于甚至需要专家参与，但社区将能够通过LBT确定需求，并根据需要呼吁社区内外的专家。更广泛的影响将是使参与涉及数据共享的社区合作项目更容易获得、更易使用和更具可扩展性，特别是在历史上处于不利地位的社区，并扩大数据共享和基于数据共享的项目的用户基础。该项目是对公民创新挑战计划的响应-轨道B-弥合基本资源和服务以及社区需求之间的差距-是NSF、国土安全部和能源部的合作。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Legacy Building Toolset (LBT) is a digital platform, centered on interactive data visualizations, that allows community members to collectively explore identity, the meaning of place, and create and engage with community assets. Currently such tools and methods are underexplored, which is concerning because public policy is often based on how policymakers perceive the meaning of place from the perspective of residents. As a result, residents often find it challenging to collect and organize community information to present to policy makers or face exclusion when their interpretations of the built form remain unrecognized. The LBT aims to realize community-accessible tools for creating community-driven interpretations of meaning in the built form at a large scale, in real time, and with an overlay of culture and identity. The tool will be developed in Northeast Oklahoma City, a disadvantaged and predominantly Black community, and the knowledge gained will be disseminated for use by other communities across the United States. The development and deployment of the Legacy Building Toolset (LBT) through the envisioned Stage 2 pilot project will combine successful engagement methods of photovoice and storytelling with scalability via crowdsourced data editing and viewing directly inside maps, timelines, and other data visualizations. The LBT will include a collection of intuitively interactive, visualization-centric, in-browser data editing and viewing applications supported by a web services database backend. The applications will support entry of information about people, places, times, and other details through interactive gesturing directly in the visualizations themselves. This includes opportunities to annotate locations, regions, and times with photos, video, or audio. The applications will also support organization of information into stories that integrate text, visualizations, and multimedia annotations. Existing photovoice and storytelling methods often require an in-person expert who organizes and leads the process. Through visualization-centric user interfaces, the LBT will provide less centralized methods of collecting, organizing, and curating community information. The community will be able to develop and use stories more independently of experts. Many urban design and planning projects may still benefit from or even require expert involvement, but the community will be able to identify needs through the LBT and call upon experts internal or external to the community as needed. The broader impacts will be to make participation in community collaboration projects involving sharing of data more accessible, usable, and scalable, especially in historically disadvantaged communities, and broaden the user base for both data sharing and projects built on it. This project is in response to the Civic Innovation Challenge program—Track B. Bridging the gap between essential resources and services & community needs—and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.