{"title":"MTable: Visual query interface for browsing and navigation in NoSQL data stores","authors":"Kanika Soni, Shelly Sachdeva","doi":"10.1016/j.cola.2024.101312","DOIUrl":null,"url":null,"abstract":"<div><div>Almost all human endeavors in the era of the digital revolution, from commercial and industrial processes to scientific and medical research, depend on the use of ever-increasing amounts of data. However, this humungous data and its complexity make data exploration and querying challenging even for experts. This led to the demand for easy access to data, even for naive users, all the more evident. Considering this, the database community has tilted toward NoSQL Data stores. While there has been much study on query formulation assistance for NoSQL data stores, many users still want help when specifying complex queries (such as aggregation pipeline queries), which require an in-depth understanding of the data storage architecture of a specific NoSQL data store. To help users perform interactive browsing and navigation in NoSQL data stores (MongoDB), this paper proposes a novel, simple, and user-friendly interface, MTable, that provides users with a presentation-level interactive view. This view compactly presents the query results from multiple embedded documents within a single tabular format compared to MongoDB's find operation, which always returns the main document. A certain cell of the MTable contains clickable hyperlinks for users to interact directly with the data persisted in the document stores. This helps the users to incrementally construct complex queries and navigate the document stores without worrying about the tedious task of writing complex queries. In a user study, participants performed various querying tasks faster with MTable than with the traditional querying mechanism. MTable has received positive subjective feedback as well.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"82 ","pages":"Article 101312"},"PeriodicalIF":1.7000,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Languages","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590118424000558","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Almost all human endeavors in the era of the digital revolution, from commercial and industrial processes to scientific and medical research, depend on the use of ever-increasing amounts of data. However, this humungous data and its complexity make data exploration and querying challenging even for experts. This led to the demand for easy access to data, even for naive users, all the more evident. Considering this, the database community has tilted toward NoSQL Data stores. While there has been much study on query formulation assistance for NoSQL data stores, many users still want help when specifying complex queries (such as aggregation pipeline queries), which require an in-depth understanding of the data storage architecture of a specific NoSQL data store. To help users perform interactive browsing and navigation in NoSQL data stores (MongoDB), this paper proposes a novel, simple, and user-friendly interface, MTable, that provides users with a presentation-level interactive view. This view compactly presents the query results from multiple embedded documents within a single tabular format compared to MongoDB's find operation, which always returns the main document. A certain cell of the MTable contains clickable hyperlinks for users to interact directly with the data persisted in the document stores. This helps the users to incrementally construct complex queries and navigate the document stores without worrying about the tedious task of writing complex queries. In a user study, participants performed various querying tasks faster with MTable than with the traditional querying mechanism. MTable has received positive subjective feedback as well.