925 resultados para research data repository
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Includes index.
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Prepared for the ICRDB Program by the Current Cancer Research Project Analyis Center.
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Problem-structuring group workshops can be used in organizations as a consulting tool and as a research tool. One example of the latter is using a problem-structuring method (PSM) to help a group tackle an organizational issue; meanwhile, researchers collect the participants' initial views, discussion of divergent views, the negotiated agreement, and the reasoning for outcomes emerging. Technology can help by supporting participants in freely sharing their opinions and by logging data for post-workshop analyses. For example, computers let participants share views anonymously and without being influenced by others (as well as logging those views), and video-cameras can record discussions and intra-group dynamics. This paper evaluates whether technology-supported Journey Making workshops can be effective research tools that can capture quality research data when compared against theoretical performance benchmarks and other qualitative research tools. © 2006 Operational Research Society Ltd. All rights reserved.
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Overview of the key aspects and approaches to open access, open data and open science, emphasizing on sharing scientific knowledge for sustainable progress and development.
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Conflict of interest: None of the authors have any conflict of interest.
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Visual cluster analysis provides valuable tools that help analysts to understand large data sets in terms of representative clusters and relationships thereof. Often, the found clusters are to be understood in context of belonging categorical, numerical or textual metadata which are given for the data elements. While often not part of the clustering process, such metadata play an important role and need to be considered during the interactive cluster exploration process. Traditionally, linked-views allow to relate (or loosely speaking: correlate) clusters with metadata or other properties of the underlying cluster data. Manually inspecting the distribution of metadata for each cluster in a linked-view approach is tedious, specially for large data sets, where a large search problem arises. Fully interactive search for potentially useful or interesting cluster to metadata relationships may constitute a cumbersome and long process. To remedy this problem, we propose a novel approach for guiding users in discovering interesting relationships between clusters and associated metadata. Its goal is to guide the analyst through the potentially huge search space. We focus in our work on metadata of categorical type, which can be summarized for a cluster in form of a histogram. We start from a given visual cluster representation, and compute certain measures of interestingness defined on the distribution of metadata categories for the clusters. These measures are used to automatically score and rank the clusters for potential interestingness regarding the distribution of categorical metadata. Identified interesting relationships are highlighted in the visual cluster representation for easy inspection by the user. We present a system implementing an encompassing, yet extensible, set of interestingness scores for categorical metadata, which can also be extended to numerical metadata. Appropriate visual representations are provided for showing the visual correlations, as well as the calculated ranking scores. Focusing on clusters of time series data, we test our approach on a large real-world data set of time-oriented scientific research data, demonstrating how specific interesting views are automatically identified, supporting the analyst discovering interesting and visually understandable relationships.
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In order to become better prepared to support Research Data Management (RDM) practices in sciences and engineering, Queen’s University Library, together with the University Research Services, conducted a research study of all ranks of faculty members, as well as postdoctoral fellows and graduate students at the Faculty of Engineering & Applied Science, Departments of Chemistry, Computer Science, Geological Sciences and Geological Engineering, Mathematics and Statistics, Physics, Engineering Physics & Astronomy, School of Environmental Studies, and Geography & Planning in the Faculty of Arts and Science.
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The objective of this research was to develop a methodology for transforming and dynamically segmenting data. Dynamic segmentation enables transportation system attributes and associated data to be stored in separate tables and merged when a specific query requires a particular set of data to be considered. A major benefit of dynamic segmentation is that individual tables can be more easily updated when attributes, performance characteristics, or usage patterns change over time. Applications of a progressive geographic database referencing system in transportation planning are vast. Summaries of system condition and performance can be made, and analyses of specific portions of a road system are facilitated.
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This report evaluates the use of remotely sensed images in implementing the Iowa DOT LRS that is currently in the stages of system architecture. The Iowa Department of Transportation is investing a significant amount of time and resources into creation of a linear referencing system (LRS). A significant portion of the effort in implementing the system will be creation of a datum, which includes geographically locating anchor points and then measuring anchor section distances between those anchor points. Currently, system architecture and evaluation of different data collection methods to establish the LRS datum is being performed for the DOT by an outside consulting team.
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The Data Processing Department of ISHC has developed coding forms to be used for the data to be entered into the program. The Highway Planning and Programming and the Design Departments are responsible for coding and submitting the necessary data forms to Data Processing for the noise prediction on the highway sections.
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Advances in communication, navigation and imaging technologies are expected to fundamentally change methods currently used to collect data. Electronic data interchange strategies will also minimize data handling and automatically update files at the point of capture. This report summarizes the outcome of using a multi-camera platform as a method to collect roadway inventory data. It defines basic system requirements as expressed by users, who applied these techniques and examines how the application of the technology met those needs. A sign inventory case study was used to determine the advantages of creating and maintaining the database and provides the capability to monitor performance criteria for a Safety Management System. The project identified at least 75 percent of the data elements needed for a sign inventory can be gathered by viewing a high resolution image.
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The object of this report is to present the data and conclusions drawn from the analysis of the origin and destination information. Comments on the advisability and correctness of the approach used by Iowa are encouraged.
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Although the benefits of mindfulness meditation practices have been widely documented, research data suggest that there are barriers to regularly engaging in meditation behavior. In order to explore research questions pertaining to meditation initiation and adherence, psychometrically valid scales to assess barriers to meditation practice are necessary. The aim of the present study was to explore the factor structure and construct validity of the Determinants of Meditation Practice Inventory (DMPI) (Williams et al., 2011), a perceived barriers to meditation scale. Exploratory and confirmatory factor analyses along with construct validity tests were performed on data obtained from two large, community samples. Results supported the DMPI as a valid scale assessing perceived barriers with four factors, Lack of Interest, Knowledge Concerns, Pragmatic Concerns and Sociocultural Beliefs. The present study offers a DMPI-revised scale that may be reliably used to assess attitudes and beliefs that might impede meditation behavior.
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This report is the second Ithaka S+R / Jisc / RLUK survey of UK academics. It asks of the UK research community their views on resource discovery, their use of these resources (online and digital), attitudes to research data management, and much more. It provides a powerful insight into how researchers view their own behaviour and the research environment within the UK today. It gives us pointers to how we can provide further support to researchers and first indications as to where resources should be best invested in the future.