DataCite as a novel bibliometric source: Coverage, strengths and limitations

This paper explores the characteristics of DataCite to determine its possibilities and potential as a new bibliometric data source to analyze the scholarly production of open data. Open science and the increasing data sharing requirements from governments, funding bodies, institutions and scientific journals has led to a pressing demand for the development of data metrics. As a very first step towards reliable data metrics, we need to better comprehend the limitations and caveats of the information provided by sources of open data. In this paper, we critically examine records downloaded from the DataCite's OAI API and elaborate a series of recommendations regarding the use of this source for bibliometric analyses of open data. We highlight issues related to metadata incompleteness, lack of standardization, and ambiguous definitions of several fields. Despite these limitations, we emphasize DataCite's value and potential to become one of the main sources for data metrics development.Comment: Paper accepted for publication in Journal of Informetric

Fractional Exact Solutions and Solitons in Gravity

We survay our recent results on fractional gravity theory. It is also provided the Main Theorem on encoding of geometric data (metrics and connections in gravity and geometric mechanics) into solitonic hierarchies. Our approach is based on Caputo fractional derivative and nonlinear connection formalism.Comment: latex2e, 11pt, 10 pages with table of content; a summary of our talk at Conference "New Trends in Nanotechnology and Nonlinear Dynamical Systems", 25--27 July, 2010, \c{C}ankaya University, Ankara, Turke

Data, Metrics and Monitoring in CGIAR - a strategic study

This document contains the final report of the Panel together with the ISPC commentary. The Panel Report presents an analysis of the current activities within CGIAR concerning data, metrics and indicators, and offers a series of recommendations to address the key issues and challenges identified

Biobanking with Big Data: A Need for Developing “Big Data Metrics”

The term “big data” has often been used as an all-encompassing phrase for research that involves the use of large-scale data sets. However, the use of the term does little to signify the underlying complexity of definitions, of data sets, and of the requirements that need to be taken into consideration for sustainable research and the estimation of downstream impact. In particular, “big data” is frequently connected with biobanks and biobank networks as the institutions involved in tissue preservation are increasingly and perhaps unavoidably linked to the de facto preservation of information. “Big data” is commonly defined as collections of data sets so large and complex that its manipulation and management present significant logistical challenges (Oxford English Dictionary, 2013). Within the sphere of clinically oriented research, the term is often synonymous to electronic patient records from large hospitals, clinical trials, and/or -omics-based consortia and their associated banked samples. These data can be structured or unstructured, generated from diverse sources (sometimes in real time), and in very large volumes

Collecting and Processing Earth Science Data Metrics at NASA ESDIS

Since the launch of Terra satellite in 1999, the number of Earth Science remote sensing data products created and distributed by NASA's Earth Observing System (EOS) Data and Information System (EOSDIS) has increased from a few hundred to nearly ten thousand. NASA's Earth Science Data and Information System (ESDIS) Metrics System (EMS) collects metrics on data ingest, archive, and distribution by its Distributed Active Archive Centers (DAACs) and the Science Investigator-led Systems (SIPS), known as Data Providers. These metrics are critical in helping NASA management as well as data producers in resource planning and gaining a wide range of knowledge of data users and data usage.EMS receives flat files, or log files of data archive, ingest, and distribution either in their raw format, such as Apache web logs, or text files of log records formatted by the Data Providers. Tens of millions of records are processed each day to extract metrics on data products, user information, distribution protocols and services, and so on. The metrics are then made available to designated parties.This presentation provides an overview of the EMS processing workflow and improvement efforts made in recent years to handle ever-increasing number of data records and new metrics requirements, discusses several key steps including mapping log records to data products and identifying user communities along with geo-distribution, and demonstrates typical metrics capabilities produced by the EMS system. Challenges and potential approaches to improve the system are also discussed

Tracking citations and altmetrics for research data: Challenges and opportunities

Methods for determining research quality have long been debated but with little lasting agreement on standards, leading to the emergence of alternative metrics. Altmetrics are a useful supplement to traditional citation metrics, reflecting a variety of measurement points that give different perspectives on how a dataset is used and by whom. A positive development is the integration of a number of research datasets into the ISI Data Citation Index, making datasets searchable and linking them to published articles. Yet access to data resources and tracking the resulting altmetrics depend on specific qualities of the datasets and the systems where they are archived. Though research on altmetrics use is growing, the lack of standardization across datasets and system architecture undermines its generalizability. Without some standards, stakeholders' adoption of altmetrics will be limited

Reliability, Validity, Comparability and Practical Utility of Cybercrime-related Data, Metrics, and Information

With an increasing pervasiveness, prevalence and severity of cybercrimes, various metrics, measures and statistics have been developed and used to measure various aspects of this phenomenon. Cybercrime-related data, metrics, and information, however, pose important and difficult dilemmas regarding the issues of reliability, validity, comparability and practical utility. While many of the issues of the cybercrime economy are similar to other underground and underworld industries, this economy also has various unique aspects. For one thing, this industry also suffers from a problem partly rooted in the incredibly broad definition of the term “cybercrime”. This article seeks to provide insights and analysis into this phenomenon, which is expected to advance our understanding into cybercrime-related information