{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T02:03:34Z","timestamp":1760061814079},"reference-count":26,"publisher":"Association for Computing Machinery (ACM)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2010,11]]},"abstract":"<jats:p>Non-technical users are increasingly adding structures to their data. This gives rise to the need for database design. However, traditional database design is deliberate and heavy-weight, requiring technical expertise that everyday users may not possess. For this reason, we propose that users of personal data management applications should be able to create and refine data structures in an ad-hoc way over time, thereby \"organically\" growing their schemas. For this purpose, we develop a spreadsheet-like direct manipulation interface. We show how integrity constraints can still provide value, even in this scenario of frequent schema and data modifications. We also develop a back-end database implementation to support this interface, with a design that permits schema changes at a low cost.<\/jats:p><jats:p>We have folded these ideas into a system, called CRIUS, which supports a nested data model and a graphical user interface. From the user's perspective, the chief advantages of CRIUS are its support for simple schema definition and modification through an intuitive drag-and-drop interface, as well as its guidance towards user data entry based on incrementally updated data integrity. We have evaluated CRIUS by means of user studies and performance studies. The user studies indicate that 1) CRIUS makes it much easier for users to design a database, as compared to state-of-the-art GUI database design tools, and 2) CRIUS makes user data entry more efficient and less error-prone. The performance experiments show that 1) the incremental integrity update in CRIUS is very efficient, making the data entry guidance applicable and 2) the backend database implementation in CRIUS significantly improves the performance of schema update tasks, without a significant impact on other operations.<\/jats:p>","DOI":"10.14778\/1921071.1921075","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"81-92","source":"Crossref","is-referenced-by-count":13,"title":["CRIUS"],"prefix":"10.14778","volume":"4","author":[{"given":"Li","family":"Qian","sequence":"first","affiliation":[{"name":"Univ. of Michigan, Ann Arbor"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kristen","family":"LeFevre","sequence":"additional","affiliation":[{"name":"Univ. of Michigan, Ann Arbor"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"H. 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