Blockchain technology is a secure distributed ledger for lists of transactions, which has immense potential to solve traditional agri-food supply chain issues. An increasing number of research on blockchain-based traceability applications aims to improve food quality and safety. Still, relatively few works considered user interfaces when developing and reporting their applications, which could lead to usability issues. This paper aims to address this gap by reviewing existing works from user interface perspectives. We gathered 25 review papers on blockchain or agri-food supply chain and 39 research papers that presented screenshots of user interfaces of related applications. We first reviewed 7 review papers that focused on the blockchain-based agri-food supply chain to understand the benefits and challenges in the blockchain applications. We then analyzed 14 blockchain-based agri-food traceability applications and 10 non-blockchain-based agri-food traceability applications. The analysis resulted in categorizations of 5 target user groups, 3 main approaches for collecting data, 5 main approaches for visualizing data, and a discussion of other aspects of user interfaces. However, we found insufficient details and discussions on the user interfaces and design decisions of the applications for further usability assessment. Additionally, user involvement for evaluation is lower in blockchain-based researches than in non-blockchain-based researches. This trend could lead to usability problems of blockchain applications, causing blockchain technology to be underutilized. Finally, we discussed research gaps and future research directions related to user interface design, which should be addressed to ease future blockchain adoption.
Background Manual chemical data curation from publications is error-prone, time consuming, and hard to maintain up-to-date data sets. Automatic information extraction can be used as a tool to reduce these problems. Since chemical structures usually described in images, information extraction needs to combine structure image recognition and text mining together. Results We have developed ChemEx, a chemical information extraction system. ChemEx processes both text and images in publications. Text annotator is able to extract compound, organism, and assay entities from text content while structure image recognition enables translation of chemical raster images to machine readable format. A user can view annotated text along with summarized information of compounds, organism that produces those compounds, and assay tests. Conclusions ChemEx facilitates and speeds up chemical data curation by extracting compounds, organisms, and assays from a large collection of publications. The software and corpus can be downloaded from http://www.biotec.or.th/isl/ChemEx.
We explored the use of blockchain technology for traceability to improve the safety and value of food, focusing on the coffee supply chain as a case study. The main goal was to evaluate the feasibility in terms of design, perceived benefits, and challenges of applying blockchain and traceability from the users' perspective. We implemented a prototype using a user-centered iterative interface design. Then we used the prototype to answer our research questions in mixed-method research, including in-depth interviews (10 participants) and a survey (350 participants) with stakeholders in the coffee supply chain in Thailand. The results showed that timeline-based design was preferred over map-based or text-based design for the visualization of traceability information and that blockchain was a promising technology, as 67% of the survey participants saw a positive influence of blockchain on the adoption of applications. The most notable benefits were origin checking and increasing product trustworthiness. The most notable challenges were inaccurate or incomplete information and the disclosure of trade secrets. More work is required to address the challenges for everyone in the supply chain ecosystem to adopt the proposed traceability system, including (1) providing trustworthiness and completeness of information by cross-checking with third parties or other users, (2) protecting sensitive information by aligning users' interests or allowing control of information disclosure, and (3) educating and giving producers the motivation for the difficulty and the extra work.
Media assets, such as overlay graphics or comments, can make video streaming a unique and engaging experience. Appropriately managing media assets during the live streaming, however, is still difficult for streamers who work alone or in small groups. With the aim to ease the management of such assets, we analyzed existing live production tools and designed four low fidelity prototypes, which eventually led to two high fidelity ones, based on the feedback from users and designers. The results of a usability test, using fully interactive prototypes, suggested that a controller and predefined media object behavior were useful for managing objects. The findings from this preliminary work help us design a prototype that helps users to stream rich media presentations.
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