MicroED data collection and processing.

MicroED, a method at the intersection of X-ray crystallography and electron cryo-microscopy, has rapidly progressed by exploiting advances in both fields and has already been successfully employed to determine the atomic structures of several proteins from sub-micron-sized, three-dimensional crystals. A major limiting factor in X-ray crystallography is the requirement for large and well ordered crystals. By permitting electron diffraction patterns to be collected from much smaller crystals, or even single well ordered domains of large crystals composed of several small mosaic blocks, MicroED has the potential to overcome the limiting size requirement and enable structural studies on difficult-to-crystallize samples. This communication details the steps for sample preparation, data collection and reduction necessary to obtain refined, high-resolution, three-dimensional models by MicroED, and presents some of its unique challenges

Circular 02/03 : data collection : collection arrangements on learner data

"This circular is for consultation. It sets out the medium-term strategy of the Learning and Skills Council (the Council) for collecting data on learners and provides details of the proposed content of the Individualised Learner Record for further education institutions and work based learning providers for 2002/03" -- front cover

Reliable online social network data collection

Large quantities of information are shared through online social networks, making them attractive sources of data for social network research. When studying the usage of online social networks, these data may not describe properly users’ behaviours. For instance, the data collected often include content shared by the users only, or content accessible to the researchers, hence obfuscating a large amount of data that would help understanding users’ behaviours and privacy concerns. Moreover, the data collection methods employed in experiments may also have an effect on data reliability when participants self-report inacurrate information or are observed while using a simulated application. Understanding the effects of these collection methods on data reliability is paramount for the study of social networks; for understanding user behaviour; for designing socially-aware applications and services; and for mining data collected from such social networks and applications. This chapter reviews previous research which has looked at social network data collection and user behaviour in these networks. We highlight shortcomings in the methods used in these studies, and introduce our own methodology and user study based on the Experience Sampling Method; we claim our methodology leads to the collection of more reliable data by capturing both those data which are shared and not shared. We conclude with suggestions for collecting and mining data from online social networks.Postprin

Organic data network: Harmonising organic market data collection in Europe

This contribution emerged as part of the collaborative project “Data network for better European organic market information” carried out in the 7th Framework Programme of the EU. Data from an online and a telephone survey among organic market data collectors form the basis for the analysis of the current situation of statistics on organic market data. The results reveal a heterogeneous picture, because organic market growth and data collection within the organic food sector have developed differently throughout Europe. Building on the survey results, the quality of data collection approaches is evaluated through the application of the data quality dimensions relevance, accuracy, comparability, coherence, accessibility/clarity, and timeliness/punctuality (Eurostat, 2009). Thereby best practice examples are identified and used for the elaboration of guidelines for the harmonisation of organic market data collection in Europe

Ethical issues surrounding e-gambling data collection

Online gambling data collection is becoming a focus of interest for various stakeholders in the online gaming industry, since it is relevant for advertising, attracting new players, exploring new markets and trying out new products. Mark Griffiths, of Nottingham Trent University, and Monica Whitty, of the University of Leicester, give an overview of some of the ethical issues raised by data collection in the gaming industry and research undertaken in the gambling studies field

Model-Driven Data Collection for Biological Systems

For biological experiments aiming at calibrating models with unknown parameters, a good experimental design is crucial, especially for those subject to various constraints, such as financial limitations, time consumption and physical practicability. In this paper, we discuss a sequential experimental design based on information theory for parameter estimation and apply it to two biological systems. Two specific issues are addressed in the proposed applications, namely the determination of the optimal sampling time and the optimal choice of observable. The optimal design, either sampling time or observable, is achieved by an information-theoretic sensitivity analysis. It is shown that this is equivalent with maximizing the mutual information and contrasted with non-adaptive designs, this information theoretic strategy provides the fastest reduction of uncertainty.Comment: 2014 American Control Conference, Portland, OR, June 201