Despite extensive research on visual query systems, the standard way to interact with relational databases remains to be through SQL queries and tailored form interfaces. This makes the power of relational databases largely inaccessible to non-programmers. This thesis proposes a solution, in two parts.The first contribution of this thesis is a solution to the visual query language problem, that is, the problem of letting end users construct arbitrary database queries through a graphical user interface. We propose the first visual query language to simultaneously satisfy three requirements: (1) query specification through direct manipulation of results, (2) the ability to view and modify any part of the current query without departing from the direct manipulation interface, and (3) SQL-like expressiveness. By directly manipulating nested relational results, and using spreadsheet idioms such as formulas and filters, the user can express arbitrary SQL-92 queries while always remaining able to track and modify the state of the complete query.The second contribution of this thesis is an algorithm for automatically formatting nested relational data using the traditional visual idioms of hand-designed database UIs: tables, multi-column forms, and outline-style indented lists. The algorithm plugs directly into the output stage of our visual query language, and produces the concrete graphics that the user sees and manipulates on the screen during query construction. The algorithm eliminates the need for an application developer to specify low-level presentation details such as label placements, text field dimensions, table column widths, and list styles.Our prototype visual query system gives the user an experience of responsive, incremental query building while pushing all actual query processing to the database layer. We evaluate the query building aspects of our system with formative and controlled user studies on a total of 28 spreadsheet users. The controlled study shows our system outperforming Microsoft Access by 18 points on the System Usability Scale [17]; this corresponds to a 46 percentage point difference on a percentile scale of other studies in the Business Software category. We also evaluate the different layouts that can be produced by our automatic layout algorithm, including via an online user study on 27 subjects.

A key feature of relational database applications is managing plural relationships-one-to-many and many-to-manybetween entities. However, since it is often infeasible to adopt or develop a new database application for any given schema at hand, information workers instead turn to spreadsheets, which lend themselves poorly to schemas requiring multiple related entity sets. In this paper, we propose to reduce the cost-usability gap between spreadsheets and tailor-made relational database applications by extending the spreadsheet paradigm to let the user establish relationships between rows in related worksheets as well as view and navigate the hierarchical cell structure that arises as a result. We present Related Worksheets, a spreadsheet-like prototype application, and evaluate it with a screencast-based user study on 36 Mechanical Turk workers. First-time users of our software were able to solve lookup-type query tasks with the same or higher accuracy as subjects using Microsoft Excel, in one case 40% faster on average.

Fig. 1. Interactive adaptation of the layout of the data to be displayed, based on the available horizontal width of an on-screen window.Abstract-Domain-specific database applications tend to contain a sizable number of table-, form-, and report-style views that must each be designed and maintained by a software developer. A significant part of this job is the necessary tweaking of low-level presentation details such as label placements, text field dimensions, list or table styles, and so on. In this paper, we present a horizontally constrained layout management algorithm that automates the display of structured hierarchical data using the traditional visual idioms of hand-designed database UIs: tables, multi-column forms, and outline-style indented lists. We compare our system with pure outline and nested table layouts with respect to space efficiency and readability, the latter with an online user study on 27 subjects. Our layouts are 3.9 and 1.6 times more compact on average than outline layouts and horizontally unconstrained table layouts, respectively, and are as readable as table layouts even for large datasets.

No abstract

Antimicrobial resistance (AMR) is threatening the lives of millions worldwide. Antibiotics which once saved countless lives, are now failing, ushering in vaccines development as a current global imperative. Conjugate vaccines produced either by chemical synthesis or biologically in Escherichia coli cells, have been demonstrated to be safe and efficacious in protection against several deadly bacterial diseases. However, conjugate vaccines assembly and production have several shortcomings which hinders their wider availability. Here, we developed a tool, Mobile-element Assisted Glycoconjugation by Insertion on Chromosome, MAGIC, a novel method that overcomes the limitations of the current conjugate vaccine design method(s). We demonstrate at least 2-fold increase in glycoconjugate yield via MAGIC when compared to conventional bioconjugate method(s). Furthermore, the modularity of the MAGIC platform also allowed us to perform glycoengineering in genetically intractable bacterial species other than E. coli. The MAGIC system promises a rapid, robust and versatile method to develop vaccines against bacteria, especially AMR pathogens, and could be applied for biopreparedness.