Reframing Open Big Data

Recent developments in the techniques and technologies of collecting, sharing and analysing data are challenging the field of information systems (IS) research let alone the boundaries of organizations and the established practices of decision-making. Coined ‘open data’ and ‘big data’, these developments introduce an unprecedented level of societal and organizational engagement with the potential of computational data to generate new insights and information. Based on the commonalities shared by open data and big data, we develop a research framework that we refer to as open big data (OBD) by employing the dimensions of ‘order’ and ‘relationality’. We argue that these dimensions offer a viable approach for IS research on open and big data because they address one of the core value propositions of IS; i.e. how to support organizing with computational data. We contrast these dimensions with two other categories that stem from computer science and engineering, namely ‘big/small’ and ‘open/closed’ to address the complex interplay between people and data, social interaction and technological operations. Thus conceived, this paper contributes an alternative approach for the study of open and big data as well as laying the theoretical groundwork for its future empirical research

Big data and smart cities: a public sector organizational learning perspective

Public sector organizations (city authorities) have begun to explore ways to exploit big data to provide smarter solutions for cities. The way organizations learn to use new forms of technology has been widely researched. However, many public sector organisations have found themselves in new territory in trying to deploy and integrate this new form of technology (big data) to another fast moving and relatively new concept (smart city). This paper is a cross-sectional scoping study—from two UK smart city initiatives—on the learning processes experienced by elite (top management) stakeholders in the advent and adoption of these two novel concepts. The findings are an experiential narrative account on learning to exploit big data to address issues by developing solutions through smart city initiatives. The findings revealed a set of moves in relation to the exploration and exploitation of big data through smart city initiatives: (a) knowledge finding; (b) knowledge reframing; (c) inter-organization collaborations and (d) ex-post evaluations. Even though this is a time-sensitive scoping study it gives an account on a current state-of-play on the use of big data in public sector organizations for creating smarter cities. This study has implications for practitioners in the smart city domain and contributes to academia by operationalizing and adapting Crossan et al’s (Acad Manag Rev 24(3): 522–537, 1999) 4I model on organizational learning

To Frame or Reframe: Where Might Design Thinking Research Go Next?

Design thinking is gaining widespread attention in the practitioner and academic literature. Successful implementation has been documented, and its value shown in empirical studies. There is little examination, however, of how design thinking practices fit with other approaches from which firms might choose to frame and solve problems such as agile, lean startup, scientific method, Six Sigma, critical thinking, and systems thinking. By digging into the basic capabilities underlying design thinking, academic researchers might better understand problem framing and solving in general and provide insight for practitioners as to where alternative approaches might be applied

Lessons Learned from a Decade of Providing Interactive, On-Demand High Performance Computing to Scientists and Engineers

For decades, the use of HPC systems was limited to those in the physical sciences who had mastered their domain in conjunction with a deep understanding of HPC architectures and algorithms. During these same decades, consumer computing device advances produced tablets and smartphones that allow millions of children to interactively develop and share code projects across the globe. As the HPC community faces the challenges associated with guiding researchers from disciplines using high productivity interactive tools to effective use of HPC systems, it seems appropriate to revisit the assumptions surrounding the necessary skills required for access to large computational systems. For over a decade, MIT Lincoln Laboratory has been supporting interactive, on-demand high performance computing by seamlessly integrating familiar high productivity tools to provide users with an increased number of design turns, rapid prototyping capability, and faster time to insight. In this paper, we discuss the lessons learned while supporting interactive, on-demand high performance computing from the perspectives of the users and the team supporting the users and the system. Building on these lessons, we present an overview of current needs and the technical solutions we are building to lower the barrier to entry for new users from the humanities, social, and biological sciences.Comment: 15 pages, 3 figures, First Workshop on Interactive High Performance Computing (WIHPC) 2018 held in conjunction with ISC High Performance 2018 in Frankfurt, German

Recognizing Speech in a Novel Accent: The Motor Theory of Speech Perception Reframed

The motor theory of speech perception holds that we perceive the speech of another in terms of a motor representation of that speech. However, when we have learned to recognize a foreign accent, it seems plausible that recognition of a word rarely involves reconstruction of the speech gestures of the speaker rather than the listener. To better assess the motor theory and this observation, we proceed in three stages. Part 1 places the motor theory of speech perception in a larger framework based on our earlier models of the adaptive formation of mirror neurons for grasping, and for viewing extensions of that mirror system as part of a larger system for neuro-linguistic processing, augmented by the present consideration of recognizing speech in a novel accent. Part 2 then offers a novel computational model of how a listener comes to understand the speech of someone speaking the listener's native language with a foreign accent. The core tenet of the model is that the listener uses hypotheses about the word the speaker is currently uttering to update probabilities linking the sound produced by the speaker to phonemes in the native language repertoire of the listener. This, on average, improves the recognition of later words. This model is neutral regarding the nature of the representations it uses (motor vs. auditory). It serve as a reference point for the discussion in Part 3, which proposes a dual-stream neuro-linguistic architecture to revisits claims for and against the motor theory of speech perception and the relevance of mirror neurons, and extracts some implications for the reframing of the motor theory

'Reframing the poverty debate' the New Labour way

"Poverty is back on the agenda, but back on it in particular and very worrying ways. ... how poverty is defined, understood and talked about says much about the shape and nature of any policy and political response to it." Here, Mooney draws "attention to some of the ways in which the question of poverty is being reconstructed by New Labour and an assortment of journalists, academics and social and political commentators today." And rather than a "neo-liberal vision of social justice premised on a celebration of the market" advances "an entirely different conception and understanding of social justice that argues for social and economic equality through an attack on wealth and vested interests.

CASP-DM: Context Aware Standard Process for Data Mining

We propose an extension of the Cross Industry Standard Process for Data Mining (CRISPDM) which addresses specific challenges of machine learning and data mining for context and model reuse handling. This new general context-aware process model is mapped with CRISP-DM reference model proposing some new or enhanced outputs

The Premortem Technique

[Excerpt] An autopsy—aka a postmortem examination—is a specialized surgical procedure conducted by a pathologist to thoroughly assess a corpse to determine or confirm the exact cause and circumstances of death or the character and extent of changes produced by disease. Knowledge is what you harvest from experience—be that your own or someone else’s—through sense-making. In sundry areas of human endeavor, it is common (but not common enough) to conduct the equivalent of a post-mortem by means of formal completion or evaluation reports—after-action reviews, retrospects, and learning histories are rarer still—to try to understand why an initiative did or did not succeed. And so, except in learning organizations, lessons (to be) learned mostly eventuate in the form of hindsight—that, by and large, focusing on accountability, not learning—at the (wrong) end of a plan. Paraphrasing Karl Marx, this is why history repeats itself: the first time as tragedy, the second time as farce

The Counter Narrative: Reframing Success of High Achieving Black and Latino Males in Los Angeles County

This report highlights young men who are the products of high expectations. We take time to shine a spotlight on the resilient, intelligent, and caring young men across Los Angeles County. This report takes an unapologetic stance in stating that these young men who are thriving in their homes, taking on leadership roles in their schools, and making a difference in their communities. This report is not intended to be full of the doom and gloom about what is wrong with young Black and Latino men. To the contrary, we take the time to center their voices, hear their stories, and listen to their takeaways about how they have accomplished what they are doing and the recommendations that they offer on how to support other Black and Latino young men just like them

Self-Cultivation and Meaning through the Experience of Injury Rehabilitation: A Case Study of Two Female Basketball Players

This case study involved interviewing athletes who had sustained moderate to severe injuries about the experience of being injured and the potential for self-cultivation and meaning synthesized through recovering from an injury. Two female intercollegiate basketball players were interviewed at the beginning of their rehabilitation and again at the end after successfully recovering and returning to sport. Data analysis revealed unique characteristics about the rehabilitation process with respect to loss of control, social support and learning about their confidence, motivation, perseverance, attitude, and resiliency. This article examines the experiences of these athletes as they navigated through the rehabilitation process and highlights the potential for the creation of a positive learning experience and self-cultivation that injured athletes can discover through the experience of recovering from an injury