Data Science for Social Good

Data science has been described as the fourth paradigm of scientific discovery. The latest wave of data science research, pertaining to machine learning and artificial intelligence (AI), is growing exponentially and garnering millions of annual citations. However, this growth has been accompanied by a diminishing emphasis on social good challenges—our analysis reveals that the proportion of data science research focusing on social good is less than it has ever been. At the same time, the proliferation of machine learning and generative AI has sparked debates about the sociotechnical prospects and challenges associated with data science for human flourishing, organizations, and society. Against this backdrop, we present a framework for “data science for social good” (DSSG) research that considers the interplay between relevant data science research genres, social good challenges, and different levels of sociotechnical abstraction. We perform an analysis of the literature to empirically demonstrate the paucity of work on DSSG in information systems (and other related disciplines) and highlight current impediments. We then use our proposed framework to introduce the articles appearing in the JAIS special issue on data science for social good. We hope that this editorial and the special issue will spur future DSSG research and help reverse the alarming trend across data science research over the past 30-plus years in which social good challenges are attracting proportionately less attention with each passing day

E-Democratic Government Success Framework for United States’ Municipalities

This project develops a comprehensive E-Democratic Government Success Framework that addresses low citizen engagement in local US politics. To develop this framework, I consult the literature on democratic participation, socio-technical theory, data security and privacy, decision support systems, and design science methodology. The main contribution of this project is a five-part method artifact for implementing E-Democracy initiatives—something that has not been readily attempted, despite the decentralized nature of US democracy and the opportunities it offers to experiment with institutions and deliberative procedures. This artifact gives policymakers the means to design, implement, adopt, and evaluate E-Democracy services; and it gives citizens and third parties, such as independent watchdogs, the ability to evaluate E-Democracy initiatives. Additionally, it contributes to the growing research agenda that considers the integration of information communication technology (ICT) into the policymaking process. To evaluate the effectiveness of this artifact, I use three methods: (1) benchmarking through a comparative gap analysis of the artifact’s requirements, past E-Democracy initiatives in the United States, and cybersecurity frameworks; (2) scenario creation that considers the artifact’s application through a synthetic lawsourcing instantiation; and (3) application of defense in depth methodology through mapping artifact requirements that overlap

Data Navigator: An accessibility-centered data navigation toolkit

Making data visualizations accessible for people with disabilities remains a significant challenge in current practitioner efforts. Existing visualizations often lack an underlying navigable structure, fail to engage necessary input modalities, and rely heavily on visual-only rendering practices. These limitations exclude people with disabilities, especially users of assistive technologies. To address these challenges, we present Data Navigator: a system built on a dynamic graph structure, enabling developers to construct navigable lists, trees, graphs, and flows as well as spatial, diagrammatic, and geographic relations. Data Navigator supports a wide range of input modalities: screen reader, keyboard, speech, gesture detection, and even fabricated assistive devices. We present 3 case examples with Data Navigator, demonstrating we can provide accessible navigation structures on top of raster images, integrate with existing toolkits at scale, and rapidly develop novel prototypes. Data Navigator is a step towards making accessible data visualizations easier to design and implement.Comment: To appear at IEEE VIS 202

Accessible charts are part of the equation of accessible papers: a heuristic evaluation of the highest impact LIS Journals

Purpose Statistical charts are an essential source of information in academic papers. Charts have an important role in conveying, clarifying and simplifying the research results provided by the authors, but they present some accessibility barriers for people with low vision. This article aims to evaluate the accessibility of the statistical charts published in the library and information science (LIS) journals with the greatest impact factor. Design/methodology/approach A list of heuristic indicators developed by the authors has been used to assess the accessibility of statistical charts for people with low vision. The heuristics have been applied to a sample of charts from 2019 issues of ten LIS journals with the highest impact factor according to the ranking of the JCR. Findings The current practices of image submission do not follow the basic recommended guidelines on accessibility like color contrast or the use of textual alternatives. On the 2 other hand, some incongruities between the technical suggestions of image submission and their application in analyzed charts also emerged. The main problems identified are: poor text alternatives, insufficient contrast ratio between adjacent colors, and the inexistence of customization options. Authoring tools do not help authors to fulfill these requirements. Research limitations The sample is not very extensive; nonetheless, it is representative of common practices and the most frequent accessibility problems in this context. Social implications The heuristics proposed are a good starting point to generate guidelines for authors when preparing their papers for publication and to guide journal publishers in creating accessible documents. Low vision users, a highly prevalent condition, will benefit from the improvements. Originality/value The results of this research provide key insights into low vision accessibility barriers, not considered in previous literature and can be a starting point for their solution.This research has been done in the framework of the PhD Programme in Engineering and Information Technology of the Universitat de Lleida (UdL). This work has been partially supported by the Spanish project PID2019-105093GB-I00 (MINECO/FEDER, UE) and CERCA Programme/Generalitat de Catalunya