Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

Sequential Bayesian updating for Big Data

The velocity, volume, and variety of big data present both challenges and opportunities for cognitive science. We introduce sequential Bayesian updat-ing as a tool to mine these three core properties. In the Bayesian approach, we summarize the current state of knowledge regarding parameters in terms of their posterior distributions, and use these as prior distributions when new data become available. Crucially, we construct posterior distributions in such a way that we avoid having to repeat computing the likelihood of old data as new data become available, allowing the propagation of information without great computational demand. As a result, these Bayesian methods allow continuous inference on voluminous information streams in a timely manner. We illustrate the advantages of sequential Bayesian updating with data from the MindCrowd project, in which crowd-sourced data are used to study Alzheimer’s Dementia. We fit an extended LATER (Linear Ap-proach to Threshold with Ergodic Rate) model to reaction time data from the project in order to separate two distinct aspects of cognitive functioning: speed of information accumulation and caution

THE ANALYSIS OF SUMBER WARAS CASE IN SINDONEWS’ EDITORIAL“Sumber Waras bukan Pertarungan Opini” DATED APRIL 15 TH , 2016

Media has an important role in telling an information. There is a case which dragged the governor of Jakarta; Mr. Basuki Tjahaja Purnama or oftenly called as Ahok. The case is about the allegations of irregularities in the procurement of land in West Jakarta. The governor of Jakarta, Basuki Tjahaja Purnama or Ahok was reported by the City Council to the KPK in August 2015 in connection with a land procurement process that, according to the Supreme Court Agency (BPK), caused potential state losses. In the audit of the city administration's 2014 financial report, the BPK found a suspicious case of land procurement worth Rp 755.69 billion (US$ 55.9 million). Using Critical Discourse Analysis theory proposed by Fairclough (1989, 1995, 1997), the researcher wants to find the linguistic expressions used in the editorial. The data is the editorial from Sindonews media dated April 15 th , 2016 entitled Sumber Waras bukan Pertarungan Opini. The researcher found that there are 7 (seven) strategies used in the editorial to tell about the case