Indonesia embraces the Data Science

The information era is the time when information is not only largely generated, but also vastly processed in order to extract and generated more information. The complex nature of modern living is represented by the various kind of data. Data can be in the forms of signals, images, texts, or manifolds resembling the horizon of observation. The task of the emerging data sciences are to extract information from the data, for people gain new insights of the complex world. The insights may came from the new way of the data representation, be it a visualizations, mapping, or other. The insights may also come from the implementation of mathematical analysis and or computational processing giving new insights of what the states of the nature represented by the data. Both ways implement the methodologies reducing the dimensionality of the data. The relations between the two functions, representation and analysis are the heart of how information in data is transformed mathematically and computationally into new information. The paper discusses some practices, along with various data coming from the social life in Indonesia to gain new insights about Indonesia in the emerging data sciences. The data sciences in Indonesia has made Indonesian Data Cartograms, Indonesian Celebrity Sentiment Mapping, Ethno-Clustering Maps, social media community detection, and a lot more to come, become possible. All of these are depicted as the exemplifications on how Data Science has become integral part of the technology bringing data closer to people.Comment: Paper presented in South East Asian Mathematical Society (SEAMS) 7th Conference, 10 pages, 7 figure

Interculturality in the university education. A qualitative study.

Intercultural training in the University is a necessity and a hope. A need, to the extent that must respond to the complex social and educational realities where the different cultural element is absolutely real and emerging. And, a hope, because while we educate for the respect and the promotion of intercultural we will be training teachers who will grow in future generations the seeds of peace and solidarity, and, therefore, much-needed positive values and fundamental for humanity. Therefore, in this work, we will present the results of the qualitative part of the process of research carried out in the context of the Faculty of Education Sciences of the University of Malaga during the years 2015, 2016 and 2017. The pedagogical practice of initial formation must ensure intercultural inclusion, through strategies of work that is involved to the cultural diversity present in the University classroom, in order to improve human interactions within the space training, and outside, to generate attitudes of cooperation and intercultural dialogue in university students, extending these attitudinal "ramifications" to society in general.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Right Here Right Now (RHRN) pilot study: testing a method of near-real-time data collection on the social determinants of health

Background: Informing policy and practice with up-to-date evidence on the social determinants of health is an ongoing challenge. One limitation of traditional approaches is the time-lag between identification of a policy or practice need and availability of results. The Right Here Right Now (RHRN) study piloted a near-real-time data-collection process to investigate whether this gap could be bridged. Methods: A website was developed to facilitate the issue of questions, data capture and presentation of findings. Respondents were recruited using two distinct methods – a clustered random probability sample, and a quota sample from street stalls. Weekly four-part questions were issued by email, Short Messaging Service (SMS or text) or post. Quantitative data were descriptively summarised, qualitative data thematically analysed, and a summary report circulated two weeks after each question was issued. The pilot spanned 26 weeks. Results: It proved possible to recruit and retain a panel of respondents providing quantitative and qualitative data on a range of issues. The samples were subject to similar recruitment and response biases as more traditional data-collection approaches. Participants valued the potential to influence change, and stakeholders were enthusiastic about the findings generated, despite reservations about the lack of sample representativeness. Stakeholders acknowledged that decision-making processes are not flexible enough to respond to weekly evidence. Conclusion: RHRN produced a process for collecting near-real-time data for policy-relevant topics, although obtaining and maintaining representative samples was problematic. Adaptations were identified to inform a more sustainable model of near-real-time data collection and dissemination in the future

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Forecasting the Spreading of Technologies in Research Communities

Technologies such as algorithms, applications and formats are an important part of the knowledge produced and reused in the research process. Typically, a technology is expected to originate in the context of a research area and then spread and contribute to several other fields. For example, Semantic Web technologies have been successfully adopted by a variety of fields, e.g., Information Retrieval, Human Computer Interaction, Biology, and many others. Unfortunately, the spreading of technologies across research areas may be a slow and inefficient process, since it is easy for researchers to be unaware of potentially relevant solutions produced by other research communities. In this paper, we hypothesise that it is possible to learn typical technology propagation patterns from historical data and to exploit this knowledge i) to anticipate where a technology may be adopted next and ii) to alert relevant stakeholders about emerging and relevant technologies in other fields. To do so, we propose the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas. A formal evaluation of the approach on a set of technologies in the Semantic Web and Artificial Intelligence areas has produced excellent results, confirming the validity of our solution

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

Engage, participate, empower: modelling power transfer in disadvantaged rural communities

Abstract This article explores a process meant to empower disadvantaged communities that have not previously engaged in government-instigated civic projects. Drawing on a large exploratory study of an empowerment project in seven Scottish rural communities, findings include that empowering communities should harness community development techniques that use both external actors and sources of support (i.e. exogenous practices), and those that utilise assets from within the community (i.e. endogenous practices). The paper presents the Engagement-Participation-Empowerment Model showing stages in transferring power from external actors to local communities. The paper highlights that the process of community empowerment starts with engagement and follows with participation – both representing a precondition of community empowerment. The paper indicates that there are limits to which community members are capable of embracing current community empowerment policies and showing that even targeted ‘well-tailored’ community empowerment programmes might fail. Implications of the study for further research and policy are identified. </jats:p

The Body Dances: Carnival Dance and Organization

Building on the work of Pierre Bourdieu and Maurice Merleau-Ponty we seek to open up traditional categories of thought surrounding the relation `body-organization' and elicit a thought experiment: What happens if we move the body from the periphery to the centre? We pass the interlocking theoretical concepts of object-body/subject-body and habitus through the theoretically constructed empirical case of `carnival dance' in order to re-evaluate such key organizational concepts as knowledge and learning. In doing so, we connect with an emerging body of literature on `sensible knowledge'; knowledge that is produced and preserved within bodily practices. The investigation of habitual appropriation in carnival dance also allows us to make links between repetition and experimentation, and reflect on the mechanism through which the principles of social organization, whilst internalized and experienced as natural, are embodied so that humans are capable of spontaneously generating an infinite array of appropriate actions. This perspective on social and organizational life, where change and permanence are intricately interwoven, contrasts sharply with the dominant view in organization studies which juxtaposes change/ creativity and stability

BDGS: A Scalable Big Data Generator Suite in Big Data Benchmarking

Data generation is a key issue in big data benchmarking that aims to generate application-specific data sets to meet the 4V requirements of big data. Specifically, big data generators need to generate scalable data (Volume) of different types (Variety) under controllable generation rates (Velocity) while keeping the important characteristics of raw data (Veracity). This gives rise to various new challenges about how we design generators efficiently and successfully. To date, most existing techniques can only generate limited types of data and support specific big data systems such as Hadoop. Hence we develop a tool, called Big Data Generator Suite (BDGS), to efficiently generate scalable big data while employing data models derived from real data to preserve data veracity. The effectiveness of BDGS is demonstrated by developing six data generators covering three representative data types (structured, semi-structured and unstructured) and three data sources (text, graph, and table data)