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Todd Suomela

The Realities of Research Data Management - 0 views

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    "The Realities of Research Data Management is a four-part series that explores how research universities are addressing the challenge of managing research data throughout the research lifecycle. Research data management (RDM) has emerged as an area of keen interest in higher education, leading to considerable investment in services, resources and infrastructure to support researchers' data management needs. In this series, we examine the context, influences and choices higher education institutions face in building or acquiring RDM capacity-in other words, the infrastructure, services and other resources needed to support emerging data management practices. Our findings are based on case studies of four institutions: University of Edinburgh (UK), the University of Illinois at Urbana-Champaign (US), Monash University (Australia) and Wageningen University & Research (the Netherlands), in four very different national contexts. "
Todd Suomela

Data, a first-class research output - 0 views

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    " The Make Data Count (MDC) project is funded by the Alfred P. Sloan Foundation to develop and deploy the social and technical infrastructure necessary to elevate data to a first-class research output alongside more traditional products, such as publications. It will run between May 2017 and April 2019. The project will address the significant social as well as technical barriers to widespread incorporation of data-level metrics in the research data management ecosystem through consultation, recommendation, new technical capability, and community outreach. Project work will build upon long-standing partner initiatives supporting research data management and DLM, leverage prior Sloan investments in key technologies such as Lagotto, and enlist the cooperation of the research, library, funder, and publishing stakeholder communities."
Leslie Harris

How Nonemployed Americans Spend Their Weekdays: Men vs. Women - NYTimes.com - 1 views

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    This article discusses how unemployed men and women spend their time during a typical day. What's most interesting is how the data is represented visually.
jatolbert

The "Digital" Scholarship Disconnect | EDUCAUSE - 0 views

  • Digital scholarship is an incredibly awkward term that people have come up with to describe a complex group of developments. The phrase is really, at some basic level, nonsensical. After all, scholarship is scholarship. Doing science is doing science. We don't find the Department of Digital Physics arguing with the Department of Non–Digital Physics about who's doing "real" physics.
  • Soon, people wanted to start talking more broadly about newly technology-enabled scholarly work, not just in science; in part this was because of some very dramatic and high-visibility developments in using digital technology in various humanistic investigations. To do so, they came up with the neologisms we enjoy today—awful phrases like e-scholarship and digital scholarship.Having said that, I do view the term digital scholarship basically as shorthand for the entire body of changing scholarly practice, a reminder and recognition of the fact that most areas of scholarly work today have been transformed, to a lesser or greater extent, by a series of information technologies: High-performance computing, which allows us to build simulation models and to conduct very-large-scale data analysis Visualization technologies, including interactive visualizations Technologies for creating, curating, and sharing large databases and large collections of data High-performance networking, which allows us to share resources across the network and to gain access to experimental or observational equipment and which allows geographically dispersed individuals to communicate and collaborate; implicit here are ideas such as the rise of lightweight challenge-focused virtual organizations
  • We now have enormous curated databases serving various disciplines: GenBank for gene sequences; the Worldwide Protein Data Bank for protein structures; and the Sloan Digital Sky Survey and planned successors for (synoptic) astronomical observations. All of these are relied upon by large numbers of working scientists. Yet the people who compiled these databases are often not regarded by their colleagues as "real" scientists but, rather, as "once-scientists" who got off-track and started doing resource-building for the community. And it's true: many resource-builders don't have the time to be actively doing science (i.e., analysis and discovery); instead, they are building and enabling the tools that will advance the collective scientific enterprise in other, less traditional ways. The academic and research community faces a fundamental challenge in developing norms and practices that recognize and reward these essential contributions.This idea—of people not doing "real" research, even though they are building up resources that can enable others to do research—has played out as well in the humanities. The humanists have often tried to make a careful distinction between the work of building a base of evidence and the work of interpreting that evidence to support some particular analysis, thesis, and/or set of conclusions; this is a little easier in the humanities because the scale of collaboration surrounding emerging digital resources and their exploitation for scholarship is smaller (contrast this to the literal "cast of thousands" at CERN) and it's common here to see the leading participants play both roles: resource-builder and "working" scholar.
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  • Still, in all of these examples of digital scholarship, a key challenge remains: How can we curate and manage data now that so much of it is being produced and collected in digital form? How can we ensure that it will be discovered, shared, and reused to advance scholarship?
  • On a final note, I have talked above mostly about changes in the practice of scholarship. But changes in the practice of scholarship need to go hand-in-hand with changes in the communication and documentation of scholarship.
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    Interesting short piece on challenges of digital scholarship
Todd Suomela

Beyond buttonology: Digital humanities, digital pedagogy, and the ACRL Framework | Russ... - 0 views

  • Here are a few specific examples you can apply to your instructional design process to help learners with metacognition: Model the metacognitive process during instruction (or in one-on-one consultations) to ask and reflect on big picture questions such as: “What questions can you answer with this tool?” “What can you not do with this tool?” Keep in mind some answers may be simple (e.g., this tool can only work with data in this way, so it is excluded automatically). Also, “Did I get the results I expected? What could I have done differently?” Start with inquiry and build conversations based on the learner’s answers. “Is it the data that does not work? Or is the research question fundamentally wrong to begin with?” Collaborate with faculty to teach together, modelling your practices while demonstrating a specific tool. This could include thinking aloud as you make decisions so learners can self-correct assumptions. Also, be aware of your own expert bias so you can demonstrate how to clear obstacles. Ask learners to specifically define what is difficult for them during the process of instruction. Digital humanities tools are complex and are based on complex methodologies and research questions. By constructing opportunities for learners to self-question as they move from one task to another, they learn to self-assess their progress and adjust accordingly. There are several instructional design activities that promote metacognition: think-pair-share, one minute paper (“share a key concept learned” or “what comes next?”), and case studies.
  • There are specific strategies we can implement to help learners escape the recursive spiral of the liminal state they experience while managing complex digital projects: One of the most challenging aspects of teaching digital tools is forgetting what it is like to be a novice learner. Sometimes being a near-novice oneself helps you better prepare for the basic problems and frustrations learners are facing. But recognizing liminality is a reminder to you as a teacher that the learning process is not smooth, and it requires anticipating common difficulties and regularly checking in with learners to make sure you are not leaving them behind. When meeting with learners one-on-one, make sure to use your in-depth reference interview skills to engage in methods discussions. When a learner is in the liminal state, they are not always able to “see the forest for the trees.” Your directed questions will illuminate the problems they are having and the solutions they had not seen. Pay close attention to the digital humanities work and discussions happening on your own campus, as well as across the academic community. Working through the liminal space may require helping learners make connections to others facing similar problems. Also follow online discussions in order to point your learners to a wide variety of group learning opportunities, such as the active digital humanities community on Slack.9 When designing instructional opportunities, such as workshops and hackathons, pay particular attention to outreach strategies that may bring like-minded learners together, as well as diverse voices. For example, invite the scholar whose project was completed last year to add a more experienced voice to the conversation. By encouraging the formation of learning communities on your campus, you are creating safe spaces to help learners navigate the liminal state with others who may be on the other side of struggling with specific digital project issues. In designing instructional activities, guide learners through visualization exercises that help to identify “stuck” places. Making graphic representations of one’s thoughts (e.g., concept maps) can highlight areas that require clarification.
Todd Suomela

Build a Better Monster: Morality, Machine Learning, and Mass Surveillance - 0 views

  • Unfortunately, the enemy is complacency. Tech workers trust their founders, find labor organizing distasteful, and are happy to leave larger ethical questions to management. A workplace free of 'politics' is just one of the many perks the tech industry offers its pampered employees. So our one chance to enact meaningful change is slipping away. Unless something happens to mobilize the tech workforce, or unless the advertising bubble finally bursts, we can expect the weird, topsy-turvy status quo of 2017 to solidify into the new reality. But even though we're likely to fail, all we can do is try. Good intentions are not going to make these structural problems go away. Talking about them is not going to fix them. We have to do something.
  • Can we fix it? Institutions can be destroyed quickly; they take a long time to build. A lot of what we call ‘disruption’ in the tech industry has just been killing flawed but established institutions, and mining them for parts. When we do this, we make a dangerous assumption about our ability to undo our own bad decisions, or the time span required to build institutions that match the needs of new realities. Right now, a small caste of programmers is in charge of the surveillance economy, and has broad latitude to change it. But this situation will not last for long. The kinds of black-box machine learning that have been so successful in the age of mass surveillance are going to become commoditized and will no longer require skilled artisans to deploy. Moreover, powerful people have noted and benefited from the special power of social media in the political arena. They will not sit by and let programmers dismantle useful tools for influence and social control. It doesn’t matter that the tech industry considers itself apolitical and rationalist. Powerful people did not get to be that way by voluntarily ceding power. The window of time in which the tech industry can still act is brief: while tech workers retain relatively high influence in their companies, and before powerful political interests have put down roots in the tech industry.
Todd Suomela

Young Men Are Playing Video Games Instead of Getting Jobs. That's OK. (For Now.) - Reas... - 0 views

  • Video games, like work, are basically a series of quests comprised of mundane and repetitive tasks: Receive an assignment, travel to a location, overcome some obstacles, perform some sort of search, pick up an item, and then deliver it in exchange for a reward—and, usually, another quest, which starts the cycle all over again. You are not playing the game so much as following its orders. The game is your boss; to succeed, you have to do what it says.
  • Instead of working, they are playing video games. About three quarters of the increase in leisure time among men since 2000 has gone to gaming. Total time spent on computers, including game consoles, has nearly doubled. You might think that this would be demoralizing. A life spent unemployed, living at home, without romantic prospects, playing digital time wasters does not sound particularly appealing on its face. Yet this group reports far higher levels of overall happiness than low-skilled young men from the turn of the 21st century. In contrast, self-reported happiness for older workers without college degrees fell during the same period. For low-skilled young women and men with college degrees, it stayed basically the same. A significant part of the difference comes down to what Hurst has called "innovations in leisure computer activities for young men." The problems come later. A young life spent playing video games can lead to a middle age without marketable skills or connections. "There is some evidence," Hurst pointed out, "that these young, lower-skilled men who are happy in their 20s become much less happy in their 30s or 40s." So are these guys just wasting their lives, frittering away their time on anti-social activities? Hurst describes his figures as "staggering" and "shocking"—a seismic shift in the relationship of young men to work. "Men in their 20s historically are a group with a strong attachment to the labor force," he writes. "The decline in employment rates for low-skilled men in their 20s was larger than it was for all other sex, age, and skill groups during this same time period." But there's another way to think about the change: as a shift in their relationship to unemployment. Research has consistently found that long-term unemployment is one of the most dispiriting things that can happen to a person. Happiness levels tank and never recover. One 2010 study by a group of German researchers suggests that it's worse, over time, for life satisfaction than even the death of a spouse. What video games appear to do is ease the psychic pain of joblessness—and to do it in a way that is, if not permanent, at least long-lasting. For low-skilled young men, what is the alternative to playing games? We might like to imagine that they would all become sociable and highly productive members of society, but that is not necessarily the case.
  • A military shooter might offer a simulation of being a crack special forces soldier. A racing game might simulate learning to handle a performance sports car. A sci-fi role-playing game might simulate becoming an effective leader of a massive space colonization effort. But what you're really doing is training yourself to effectively identify on-screen visual cues and twitch your thumb at the right moment. You're learning to handle a controller, not a gun or a race car. You're learning to manage a game's hidden stats system, not a space station. A game provides the sensation of mastery without the actual ability. "It's a simulation of being an expert," Wolpaw says. "It's a way to fulfill a fantasy." That fantasy, ultimately, is one of work, purpose, and social and professional success.
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