III: Small: Information Systems Under Schema Evolution: Analyzing Change Histories and Management Tools

数据库研究在模式映射方面取得的重大进展（例如，组合，可逆性），数据交换和查询重写，可以为数据库模式演化问题提供突破性的解决方案。 但到目前为止，信息系统还严重缺乏科普问题所需的方法和工具，无法减少数据迁移、查询返工、应用程序重写和模式更改造成的停机时间的成本。事实上，科学数据库的成功使这个老问题变得更糟（例如，Ensembl）和web信息系统（例如，Wikipedia）-在这里，应用程序的快速发展和需求的特点是网络和科学发现过程是加剧了用户和组织的数量和多样性，在这些努力上进行合作。幸运的是，这些公共领域的信息系统的开放性（相对于公司的），以及它们丰富的有趣的演化历史，使得有可能建立一个全面的测试平台，以确定候选方法和工具的优势，局限性和潜力。因此，该项目正在建设：（i）一个包含关键信息系统演变历史的开放源策展储存库，（ii）一套经过测试的综合工具的基准，（iii）收集和分析演变历史的工具，然后用于（a）比较和评估现有的办法、方法和工具，以及（B）吸引研究人员评估和改进他们的技术，并将他们的测试用例添加到基准中。由于理论解决方案现在在现实生活的案例研究中得到验证和改进，因此可以预期对模式映射研究和应用的变革性影响。这些反过来又有望大大改变和改进科学数据库和网络信息系统。欲了解更多信息，请访问项目网页：http://www.cs.ucla.edu/~zaniolo/nsf0917333.html

The significant progress made by database research on schema mapping (e.g., omposition, invertibility), data exchange, and query rewriting, can provide breakthrough solutions for the Database Schema Evolution problem. But as of today, information systems are sorely lacking the methods and tools needed to cope with theproblem, and to reduce the cost of data migration, rework of queries, application rewriting, and downtime created by schema changes. In fact, this old problem has been made worse by the success of scientific databases (e.g., Ensembl) and web informationsystems (e.g., Wikipedia)---where the fast evolution of applications and requirements characterizing the web and the scientific discovery process is exacerbated by the number and diversity of users and organizations cooperating on these endeavors.. Fortunately, the openness ofthese public-domain information systems (vs. corporate ones), and the abundance of their interesting evolution histories make it possible tobuilt a comprehensive testbed to determine the strengths, limitations, and potentials of candidate methods and tools proposed for the problem. Thus, this project is building: (i) an open-source curated repository containing evolution histories from key information systems, (ii) benchmarks for a comprehensive set of tools tested therein, and (iii) instruments to collect and analyze evolution histories.These are then used to (a) compare and evaluate existing approaches, methods and tools, and (b) entice researchers to evaluate and improve their techniques and add their test cases to the benchmark.A transformative impact can be expected upon schema mappingresearch and applications, inasmuch as theoretical solutions are now validated and improved on real-life case-studies. These in turn are expected to transform and improve significantly scientific databases and web information systems. For furtherinformation see the project web page:http://www.cs.ucla.edu/~zaniolo/nsf0917333.html