16,086 research outputs found

    Bots, Seeds and People: Web Archives as Infrastructure

    Full text link
    The field of web archiving provides a unique mix of human and automated agents collaborating to achieve the preservation of the web. Centuries old theories of archival appraisal are being transplanted into the sociotechnical environment of the World Wide Web with varying degrees of success. The work of the archivist and bots in contact with the material of the web present a distinctive and understudied CSCW shaped problem. To investigate this space we conducted semi-structured interviews with archivists and technologists who were directly involved in the selection of content from the web for archives. These semi-structured interviews identified thematic areas that inform the appraisal process in web archives, some of which are encoded in heuristics and algorithms. Making the infrastructure of web archives legible to the archivist, the automated agents and the future researcher is presented as a challenge to the CSCW and archival community

    A Twenty-Year Look at “Computational Geology,” an Evolving, In-Discipline Course in Quantitative Literacy at the University of South Florida

    Get PDF
    Since 1996, the Geology (GLY) program at the USF has offered “Computational Geology” as part of its commitment to prepare undergraduate majors for the quantitative aspects of their field. The course focuses on geological-mathematical problem solving. Over its twenty years, the course has evolved from a GATC (geometry-algebra-trigonometry-calculus) in-discipline capstone to a quantitative literacy (QL) course taught within a natural science major. With the formation of the new School of Geosciences in 2013, the merging departments re-examined their various curricular programs. An online survey of the Geology Alumni Society found that “express quantitative evidence in support of an argument” was more favorably viewed as a workplace skill (4th out of 69) than algebra (51st), trig (55th) and calculus 1 and 2 (59th and 60th). In that context, we decided to find out from successful alumni, “What did you get out of Computational Geology?” To that end, the first author carried out a formal, qualitative research study (narrative inquiry protocol), whereby he conducted, recorded, and transcribed semi-structured interviews of ten alumni selected from a list of 20 provided by the second author. In response to “Tell me what you remember from the course,” multiple alumni volunteered nine items: Excel (10 out of 10), Excel modules (8), Polya problem solving (5), “important” (4), unit conversions (4), back-of-the-envelope calculations (4), gender equality (3). In response to “Is there anything from the course that you used professionally or personally since graduating?” multiple alumni volunteered seven items: Excel (9 out of 10), QL/thinking (6), unit conversions (5), statistics (5), Excel modules (3), their notes (2). Outcome analysis from the open-ended comments arising from structured questions led to the identification of alumni takeaways in terms of elements of three values: (1) understanding and knowledge (facts such as conversion factors, and concepts such as proportions and log scales); (2) abilities and skills (communication, Excel, unit conversions); and (3) traits and dispositions (problem solving, confidence, and QL itself). The overriding conclusion of this case study is that QL education can have a place in geoscience education where the so-called context of the QL is interesting because it is in the students’ home major, and that such a course can be tailored to any level of program prerequisites

    Rails Won't Save America

    Get PDF
    Rising gas prices and concerns about greenhouse gases have stimulated calls to build more rail transit lines in urban areas, increase subsidies to Amtrak, and construct a large-scale intercity high-speed rail system. These megaprojects will cost hundreds of billions of dollars, but they won't save energy or significantly reduce greenhouse gas emissions. Although media reports suggest that many people are taking public transit instead of driving, actual numbers show that recent increases in transit ridership account for only 3 percent of the decline in urban driving. Also, contrary to popular belief, rail transit does not save energy. Many light-rail operations use more energy per passenger mile than the average sport utility vehicle, and almost none uses less than a fuel-efficient car such as a Toyota Prius. People who respond to high fuel prices by taking transit are not saving energy; they are merely imposing their energy costs on someone else. Rail transportation is also much more heavily subsidized than other forms of travel. Where highway subsidies average less than a penny per passenger mile, and subsidies to flying are even lower, Amtrak costs taxpayers 22 cents per passenger mile and urban transit costs 61 cents per passenger mile.Even if rail transport did save energy, spending more money on rail will get few people out of their cars. People who want to save energy should plan to buy more fuel-efficient cars and encourage cities to invest in traffic signal coordination, which can save far more energy at a tiny fraction of the cost of building new rail transport lines

    Big data, smart cities and city planning

    Get PDF
    I define big data with respect to its size but pay particular attention to the fact that the data I am referring to is urban data, that is, data for cities that are invariably tagged to space and time. I argue that this sort of data are largely being streamed from sensors, and this represents a sea change in the kinds of data that we have about what happens where and when in cities. I describe how the growth of big data is shifting the emphasis from longer term strategic planning to short-term thinking about how cities function and can be managed, although with the possibility that over much longer periods of time, this kind of big data will become a source for information about every time horizon. By way of conclusion, I illustrate the need for new theory and analysis with respect to 6 months of smart travel card data of individual trips on Greater London’s public transport systems

    XBRL:The Views of Stakeholders

    Get PDF

    End-user Empowerment in the Digital Age

    Get PDF
    End-user empowerment (or human empowerment) may be seen as an important aspect of a human-centric approach towards the digital economy. Despite the role of end-users has been recognized as a key element in information systems and end-user computing, empowering end-users may be seen as a next evolutionary step. This minitrack aims at advancing the understanding of what end-user empowerment really is, what the main challenges to develop end-user empowering systems are, and how end-user empowerment may be achieved in specific domains
    • 

    corecore