I-Corps: Solving Information-Integration Problems Using Category Theory

I-Corps：使用范畴论解决信息集成问题

• 批准号: 1611699
• 负责人: David Spivak
• 金额: $ 5万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1611699&HistoricalAwards=false
• 关键词: Corps; Solving; Information; Integration; Problems

Simple business questions can be surprisingly hard to answer. For a large company, a question like "how many employees are tax-exempt?" may require querying hundreds of databases using multiple data models and possibly inconsistent definitions: for example, is a "contractor" also an 'employee?" Over the past 5 years, this I-Corps team has developed a new technology for performing information-integration tasks such as querying, combining, and evolving databases based on category theory, a branch of mathematics that has already revolutionized several areas of computer science, including functional programming. Category theory provides theoretical guidance missing from the widely-used relational model of data, and this team has used it to build a prototype software tool, FQL (categoricaldata.net/fql.html), for integrating databases more quickly and accurately than existing relational tools. But FQL is still an academic prototype. The purpose of this project is to perform customer discovery activities so that the team can better understand (1) the market demand for this new technology and (2) the exact form that an industrial-strength tool should take, e.g. a programming language, a Java library, a cloud service, etc.During the I-Corps program, the team will interview 100+ potential customers, including IT managers of large enterprise companies in a variety of sectors, ETL and database specialists familiar with existing tools, and engineers who use databases in their process design. This team will use this customer information to find a product-market fit for the technology: e.g. are the customers interested in platforms or in-house solutions, how customized do the proposed solutions need to be, what is the best way of communicating the proposed technology-and to develop an industrial-strength tool for categorical data. Specifically, this team will develop use-case scenarios, alpha-test the existing FQL tool on potential customers, and use this information to validate and refine use-cases. By the end of the I-Corps program, the team plans to have a demo, a clear commercialization plan and a minimal viable product.

简单的业务问题可能出人意料地难以回答。对于一家大公司来说，诸如“有多少员工免税？”之类的问题。可能需要使用多个数据模型和可能不一致的定义来查询数百个数据库：例如，“承包商”也是“雇员吗？”在过去的 5 年里，这个 I-Corps 团队开发了一种新技术，用于执行信息集成任务，例如基于范畴论的查询、组合和演化数据库，范畴论是数学的一个分支，已经彻底改变了计算机科学的多个领域，包括函数式编程。范畴论提供了 广泛使用的数据关系模型缺少理论指导，该团队使用它构建了原型软件工具 FQL (categoricaldata.net/fql.html)，用于比现有关系工具更快、更准确地集成数据库。但FQL仍然是一个学术原型。该项目的目的是进行客户发现活动，以便团队能够更好地了解（1）这项新技术的市场需求以及 (2) 工业强度工具应采用的确切形式，例如编程语言、Java 库、云服务等。在 I-Corps 计划期间，团队将采访 100 多个潜在客户，包括各行业大型企业的 IT 经理、熟悉现有工具的 ETL 和数据库专家以及在流程设计中使用数据库的工程师。该团队将使用此客户信息来寻找适合该技术的产品市场： 例如客户是否对平台或内部解决方案感兴趣，提议的解决方案需要如何定制，传达提议的技术的最佳方式是什么，以及为分类数据开发工业强度的工具。具体来说，该团队将开发用例场景，对潜在客户对现有 FQL 工具进行 alpha 测试，并使用此信息来验证和完善用例。在 I-Corps 计划结束时，该团队计划拥有 演示、清晰的商业化计划和最小可行产品。