Finding Collaborators: Toward Interactive Discovery Tools for Research Network Systems
New paper by Charles D Borromeo, Titus K Schleyer, Michael J Becich, and Harry Hochheiser: “Background: Research networking systems hold great promise for helping biomedical scientists identify collaborators with the expertise needed to build interdisciplinary teams. Although efforts to date have focused primarily on collecting and aggregating information, less attention has been paid to the design of end-user tools for using these collections to identify collaborators. To be effective, collaborator search tools must provide researchers with easy access to information relevant to their collaboration needs.
Objective: The aim was to study user requirements and preferences for research networking system collaborator search tools and to design and evaluate a functional prototype.
Methods: Paper prototypes exploring possible interface designs were presented to 18 participants in semistructured interviews aimed at eliciting collaborator search needs. Interview data were coded and analyzed to identify recurrent themes and related software requirements. Analysis results and elements from paper prototypes were used to design a Web-based prototype using the D3 JavaScript library and VIVO data. Preliminary usability studies asked 20 participants to use the tool and to provide feedback through semistructured interviews and completion of the System Usability Scale (SUS).
Results: Initial interviews identified consensus regarding several novel requirements for collaborator search tools, including chronological display of publication and research funding information, the need for conjunctive keyword searches, and tools for tracking candidate collaborators. Participant responses were positive (SUS score: mean 76.4%, SD 13.9). Opportunities for improving the interface design were identified.
Conclusions: Interactive, timeline-based displays that support comparison of researcher productivity in funding and publication have the potential to effectively support searching for collaborators. Further refinement and longitudinal studies may be needed to better understand the implications of collaborator search tools for researcher workflows.”
Law is Code: A Software Engineering Approach to Analyzing the United States Code
New Paper by William Li, Pablo Azar, David Larochelle, Phil Hill & Andrew Lo: “The agglomeration of rules and regulations over time has produced a body of legal code that no single individual can fully comprehend. This complexity produces inefficiencies, makes the processes of understanding and changing the law difficult, and frustrates the fundamental principle that the law should provide fair notice to the governed. In this article, we take a quantitative, unbiased, and software-engineering approach to analyze the evolution of the United States Code from 1926 to today. Software engineers frequently face the challenge of understanding and managing large, structured collections of instructions, directives, and conditional statements, and we adapt and apply their techniques to the U.S. Code over time. Our work produces insights into the structure of the U.S. Code as a whole, its strengths and vulnerabilities, and new ways of thinking about individual laws. For example, we identify the first appearance and spread of important terms in the U.S. Code like “whistleblower” and “privacy.” We also analyze and visualize the network structure of certain substantial reforms, including the Patient Protection and Affordable Care Act (PPACA) and the Dodd-Frank Wall Street Reform and Consumer Protection Act, and show how the interconnections of references can increase complexity and create the potential for unintended consequences. Our work is a timely illustration of computational approaches to law as the legal profession embraces technology for scholarship, to increase efficiency, and to improve access to justice.”
Crowd-Sourcing Corruption: What Petrified Forests, Street Music, Bath Towels and the Taxman Can Tell Us About the Prospects for Its Future
Paper by Dieter Zinnbauer: “This article seeks to map out the prospects of crowd-sourcing technologies in the area of corruption-reporting. A flurry of initiative and concomitant media hype in this area has led to exuberant hopes that the end of impunity is not such a distant possibility any more – at least not for the most blatant, ubiquitous and visible forms of administrative corruption, such as bribes and extortion payments that on average almost a quarter of citizens reported to face year in, year out in their daily lives in so many countries around the world (Transparency International 2013).
Only with hindsight will we be able to tell, if these hopes were justified. However, a closer look at an interdisciplinary body of literature on corruption and social mobilisation can help shed some interesting light on these questions and offer a fresh perspective on the potential of social media based crowd-sourcing for better governance and less corruption. So far the potential of crowd-sourcing is mainly approached from a technology-centred perspective. Where challenges are identified, pondered, and worked upon they are primarily technical and managerial in nature, ranging from issues of privacy protection and fighting off hacker attacks to challenges of data management, information validation or fundraising.
In contrast, short shrift is being paid to insights from a substantive, multi-disciplinary and growing body of literature on how corruption works, how it can be fought and more generally how observed logics of collective action and social mobilisation interact with technological affordances and condition the success of these efforts.
This imbalanced debate is not really surprising as it seems to follow the trajectory of the hype-and-bust cycle that we have seen in the public debate for a variety of other technology applications. From electronic health cards to smart government, to intelligent transport systems, all these and many other highly ambitious initiatives start with technology-centric visions of transformational impact. However, over time – with some hard lessons learnt and large sums spent – they all arrive at a more pragmatic and nuanced view on how social and economic forces shape the implementation of such technologies and require a more shrewd design approach, in order to make it more likely that potential actually translates into impact….”
“Open” disclosure of innovations, incentives and follow-on reuse: Theory on processes of cumulative innovation and a field experiment in computational biology
Paper by Kevin J. Boudreau and Karim R. Lakhani: “Most of society’s innovation systems – academic science, the patent system, open source, etc. – are “open” in the sense that they are designed to facilitate knowledge disclosure among innovators. An essential difference across innovation systems is whether disclosure is of intermediate progress and solutions or of completed innovations. We theorize and present experimental evidence linking intermediate versus final disclosure to an ‘incentives-versus-reuse’ tradeoff and to a transformation of the innovation search process. We find intermediate disclosure has the advantage of efficiently steering development towards improving existing solution approaches, but also has the effect of limiting experimentation and narrowing technological search. We discuss the comparative advantages of intermediate versus final disclosure policies in fostering innovation.”
From the smart city to the wise city: The role of universities in place-based leadership
Paper by Hambleton, R.: “For a variety of reasons the notion of the smart city has grown in popularity and some even claim that all cities now have to be ‘smart’. For example, some digital enthusiasts argue that advances in Information and Communication Technologies (ICT) are ushering in a new era in which pervasive electronic connections will inevitably lead to significant changes that make cities more liveable and more democratic. This paper will cast a critical eye over these claims. It will unpack the smart city rhetoric and show that, in fact, three competing perspectives are struggling for ascendancy within the smart cities discourse: 1) The digital city (emphasising a strong commitment to the use of ICT in governance), 2) The green city (reflecting the growing use of the US phrase smart growth, which is concerned to apply sound urban planning principles), and 3) The learning city (emphasising the way in which cities learn, network and innovate). Five digital danger zones will be identified and discussed. This analysis will suggest that scholars and policy makers who wish to improve the quality of life in cities should focus their attention on wisdom, not smartness. Civic leaders need to exercise judgement based on values if they are to create inclusive, sustainable cities. It is not enough to be clever, quick, ingenious, nor will it help if Big Data is superseded by Even Bigger Data. Universities can play a much more active role in place-based leadership in the cities where they are located. To do this effectively they need to reconsider the nature of modern scholarship. The paper will show how a growing number of universities are doing precisely this. Two respected examples will be presented to show how urban universities, if they are committed to engaged scholarship, can make a significant contribution to the creation of the wise city.”
Can Bottom-Up Institutional Reform Improve Service Delivery?
Working paper by Molina, Ezequiel: “This article makes three contributions to the literature. First, it provides new evidence of the impact of community monitoring interventions using a unique dataset from the Citizen Visible Audit (CVA) program in Colombia. In particular, this article studies the effect of social audits on citizens’ assessment of service delivery performance. The second contribution is the introduction a theoretical framework to understand the pathway of change, the necessary building blocks that are needed for social audits to be effective. Using this framework, the third contribution of this article is answering the following questions: i) under what conditions do citizens decide to monitor government activity and ii) under what conditions do governments facilitate citizen engagement and become more accountable.”
Behavioral Economics of Education: Progress and Possibilities
Paper by Adam M. Lavecchia, Heidi Liu, and Philip Oreopoulos:” Behavioral economics attempts to integrate insights from psychology, neuroscience, and sociology in order to better predict individual outcomes and develop more effective policy. While the field has been successfully applied to many areas, education has, so far, received less attention – a surprising oversight, given the field’s key interest in long-run decision-making and the propensity of youth to make poor long-run decisions. In this chapter, we review the emerging literature on the behavioral economics of education. We first develop a general framework for thinking about why youth and their parents might not always take full advantage of education opportunities. We then discuss how these behavioral barriers may be preventing some students from improving their long-run welfare. We evaluate the recent but rapidly growing efforts to develop policies that mitigate these barriers, many of which have been examined in experimental settings. Finally, we discuss future prospects for research in this emerging field.”
Smarter, Better, Faster: The Potential for Predictive Analytics and Rapid-Cycle Evaluation to Improve Program Development and Outcomes
Paper by Scott Cody and Andrew Asher for The Hamilton Project: “Public administrators have always been interested in identifying cost-effective strategies for managing their programs. As government agencies invest in data warehouses and business intelligence capabilities, it becomes feasible to employ analytic techniques used more-commonly in the private sector. Predictive analytics and rapid-cycle evaluation are analytical approaches that are used to do more than describe the current status of programs: in both the public and private sectors, these approaches provide decision makers with guidance on what to do next. Predictive analytics refers to a broad range of methods used to anticipate an outcome. For many types of government programs, predictive analytics can be used to anticipate how individuals will respond to interventions, including new services, targeted prompts to participants, and even automated actions by transactional systems. With information from predictive analytics, administrators can identify who is likely to benefit from an intervention and find ways to formulate better interventions. Predictive analytics can also be embedded in agency operational systems to guide real-time decision making. For instance, predictive analytics could be embedded in intake and eligibility determination systems, prompting frontline workers to review suspect client applications more-closely to determine whether income or assets may be understated or deductions underclaimed…”
The Internet of Things vision: Key Features, Applications and Open Issues
Article by Eleonora Borgia in Computer Communications: “The Internet of Things (IoT) is a new paradigm that combines aspects and technologies coming from different approaches. Ubiquitous computing, pervasive computing, Internet Protocol, sensing technologies, communication technologies, and embedded devices are merged together in order to form a system where the real and digital worlds meet and are continuously in symbiotic interaction. The smart object is the building block of the IoT vision. By putting intelligence into everyday objects, they are turned into smart objects able not only to collect information from the environment and interact/control the physical world, but also to be interconnected, to each other, through Internet to exchange data and information. The expected huge number of interconnected devices and the significant amount of available data open new opportunities to create services that will bring tangible benefits to the society, environment, economy and individual citizens. In this paper we present the key features and the driver technologies of IoT. In addition to identifying the application scenarios and the correspondent potential applications, we focus on research challenges and open issues to be faced for the IoT realization in the real world.”