Digital data set of volcano hazards for active Cascade Volcanos, Washington

1996 ◽  
Author(s):  
Steve P. Schilling
Keyword(s):  
Digital Data ◽  
Data Set ◽  
Volcano Hazards

Digital data for volcano hazards in the Mount Jefferson Region, Oregon

2008 ◽  
Author(s):  
S.P. Schilling ◽  
S. Doelger ◽  
J.S. Walder ◽  
C.A. Gardner ◽  
R.M. Conrey ◽  
...  
Keyword(s):  
Digital Data ◽  
Volcano Hazards

Digital Data for Volcano Hazards of the Mount Hood Region, Oregon

2008 ◽  
Author(s):  
S.P. Schilling ◽  
S. Doelger ◽  
W.E. Scott ◽  
T.C. Pierson ◽  
J.E. Costa ◽  
...  
Keyword(s):  
Digital Data ◽  
Volcano Hazards ◽  
Mount Hood

scholarly journals Digital data set of generalized lithogeochemical characteristics of near-surface bedrock in the New England Coastal Basins

Fact Sheet ◽  
2002 ◽  
Author(s):  
Denise L. Montgomery ◽  
G.R. Robinson ◽  
J.D. Ayotte ◽  
S.M. Flanagan ◽  
K.W. Robinson
Keyword(s):  
New England ◽  
Digital Data ◽  
Data Set ◽  
Near Surface ◽  
Coastal Basins

Business-to-business referral as digital coopetition strategy

2020 ◽  
Vol 54 (6) ◽  
pp. 1181-1203
Author(s):  
Ying Zhu ◽  
Valerie Lynette Wang ◽  
Yong Jian Wang ◽  
Jim Nastos
Keyword(s):  
Physical Distance ◽  
Peer To Peer ◽  
Digital Data ◽  
Data Set ◽  
Content Type ◽  
Digital Space ◽  
Digital Network ◽  
The Impact ◽  
Business To Business ◽  
Practical Implications

Purpose Based on theories related to coopetition, the purpose of this paper is to examine the patterns of business-to-business digital referrals inscribed in businesses’ digital content. Design/methodology/approach A complete industry-wise digital data set is formed by extracting digital referrals in all the content pages. The authors outline how digital referrals are strategically used among peer businesses in the peer-to-peer digital network and in the augmented digital network, taking into consideration geographical framing and physical distance. Findings The authors reveal how geographical framing and physical distance influence peer-to-peer referral patterns in the digital space. Quite counter-intuitively, businesses are more likely to give digital referrals for peers residing in the same region, as well as for peers located in closer proximity. Further, results from the augmented digital network show that peer businesses in closer proximity exhibit greater strategic similarity in their digital referring strategy. Research limitations/implications The findings extend the understanding of business-to-business coopetition to the digital space and suggest that geographical framing and physical distance can induce reciprocated relationships between peers by offering each other digital referrals. Practical implications The findings shed light on the formation of a business-to-business digital coopetition strategy using digital referral marketing. Originality/value This study highlights the impact of digital referrals in business-to-business relationship management, especially in the digital coopetition context.

The Magnetics Information Consortium (MagIC) Data Repository: Successes and Continuing Challenges

2020 ◽  
Author(s):  
Nicholas Jarboe ◽  
Rupert Minnett ◽  
Catherine Constable ◽  
Anthony Koppers ◽  
Lisa Tauxe
Keyword(s):  
Earth Science ◽  
Journal Article ◽  
Research Capacity ◽  
Digital Data ◽  
Data Repository ◽  
Data Set ◽  
Data Repositories ◽  
The Earth ◽  
Ocean Sciences ◽  
Space Sciences

<p>MagIC (earthref.org/MagIC) is an organization dedicated to improving research capacity in the Earth and Ocean sciences by maintaining an open community digital data archive for rock and paleomagnetic data with portals that allow users access to archive, search, visualize, download, and combine these versioned datasets. We are a signatory of the Coalition for Publishing Data in the Earth and Space Sciences (COPDESS)'s Enabling FAIR Data Commitment Statement and an approved repository for the Nature set of journals. We have been in collaboration with EarthCube's GeoCodes data search portal, adding schema.org/JSON-LD headers to our data set landing pages and suggesting extensions to schema.org when needed. Collaboration with the European Plate Observing System (EPOS)'s Thematic Core Service Multi-scale laboratories (TCS MSL) is ongoing with MagIC sending its contributions' metadata to TCS MSL via DataCite records.</p><p>Improving and updating our data repository to meet the demands of the quickly changing landscape of data archival, retrieval, and interoperability is a challenging proposition. Most journals now require data to be archived in a "FAIR" repository, but the exact specifications of FAIR are still solidifying. Some journals vet and have their own list of accepted repositories while others rely on other organizations to investigate and certify repositories. As part of the COPDESS group at Earth Science Information Partners (ESIP), we have been and will continue to be part of the discussion on the needed and desired features for acceptable data repositories.</p><p>We are actively developing our software and systems to meet the needs of our scientific community. Some current issues we are confronting are: developing workflows with journals on how to publish the journal article and data in MagIC simultaneously, sustainability of data repository funding especially in light of the greater demands on them due to data policy changes at journals, and how to best share and expose metadata about our data holdings to organizations such as EPOS, EarthCube, and Google.</p>

scholarly journals Toward a Lifecycle Information Framework and Technology in Manufacturing

2017 ◽  
Vol 17 (2) ◽  
Author(s):  
Thomas Hedberg ◽  
Allison Barnard Feeney ◽  
Moneer Helu ◽  
Jaime A. Camelio
Keyword(s):  
Information Modeling ◽  
Digital Data ◽  
Use Case ◽  
Product Lifecycle ◽  
Dynamic Information ◽  
Data Set ◽  
Data Repositories ◽  
Domain Specific ◽  
Multiple Data ◽  
Information Framework

Industry has been chasing the dream of integrating and linking data across the product lifecycle and enterprises for decades. However, industry has been challenged by the fact that the context in which data are used varies based on the function/role in the product lifecycle that is interacting with the data. Holistically, the data across the product lifecycle must be considered an unstructured data set because multiple data repositories and domain-specific schema exist in each phase of the lifecycle. This paper explores a concept called the lifecycle information framework and technology (LIFT). LIFT is a conceptual framework for lifecycle information management and the integration of emerging and existing technologies, which together form the basis of a research agenda for dynamic information modeling in support of digital-data curation and reuse in manufacturing. This paper provides a discussion of the existing technologies and activities that the LIFT concept leverages. Also, the paper describes the motivation for applying such work to the domain of manufacturing. Then, the LIFT concept is discussed in detail, while underlying technologies are further examined and a use case is detailed. Lastly, potential impacts are explored.

scholarly journals Using Convolutional Networks and Satellite Imagery to Predict Disease Density in a Developing Country

2019 ◽  
Author(s):  
Rahman Sanya ◽  
Gilbert Maiga ◽  
Ernest Mwebaze
Keyword(s):  
Infectious Diseases ◽  
Developing Country ◽  
Satellite Imagery ◽  
Spatial Dynamics ◽  
Image Data ◽  
Urban Housing ◽  
Digital Data ◽  
Data Set ◽  
Convolutional Networks ◽  
Multiple Data

Rapid increase in digital data coupled with advances in deep learning algorithms is opening unprecedented opportunities for incorporating multiple data sources for modeling spatial dynamics of human infectious diseases. We used Convolutional Neural Networks (CNN) in conjunction with satellite imagery-based urban housing and socio-economic data to predict disease density in a developing country setting. We explored both single (uni) and multiple input (multimodality) network architectures for this purpose. We achieved maximum test set accuracy of 81.6 per cent using a single input CNN model built with one convolutional layer and trained using housing image data. However, this fairly good performance was biased in favor of specific disease density classes due to an unbalanced data set despite our use of methods to address the problem. These results suggest CNN are promising for modeling spatial dynamics of human infectious diseases, especially in a developing country setting. Urban housing signals extracted from satellite imagery seem suitable for this purpose, under the same context.

scholarly journals From Individual Graphite Assignment to an Improved Digital Image Analysis of Ductile Iron

2020 ◽  
Vol 14 (4) ◽  
pp. 1090-1104
Author(s):  
J. Friess ◽  
U. Sonntag ◽  
I. Steller ◽  
A. Bührig-Polaczek
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Ductile Iron ◽  
Digital Image Analysis ◽  
Visual Analysis ◽  
Digital Data ◽  
Shape Classification ◽  
Data Set ◽  
Classification Approach ◽  
Graphite Particles

Abstract Since graphite classification by visual analysis exhibits large variations, a more integrative concept of graphite shape classification is required to evaluate the correlations of process, microstructure and properties, and to fulfill customers’ requirements. The automatic digital image analysis is partly based on visual analysis, but it is not thoroughly defined for graphite shape classification. For example, nodules and thereby nodularity are only defined by the shape parameter roundness, although several studies suggest more sophisticated approaches. Within the first of three successive round robin tests, visual assignment for a variety of graphite particles was performed to obtain a universal digital data set of classified graphite particles. For this, the classification approach from standard EN ISO 945-1 was used and extended with degenerated graphite. The assigned particles were evaluated concerning different shape parameters showing that roundness and the assigned minimum limit value of 0.6 are not sufficient to distinguish nodules from less ideal graphite particle shapes. Furthermore, the current classification approach does not represent the full spectrum of graphite morphologies and needs to be extended. The development of a universal hierarchical classification method for nodules and other graphite shapes has been initiated, and the results will contribute to an improved image analysis standard for ductile iron, particularly ISO 945-4.

Digital data for volcano hazards at Newberry Volcano, Oregon

2008 ◽  
Author(s):  
S.P. Schilling ◽  
S. Doelger ◽  
D.R. Sherrod ◽  
L.G. Mastin ◽  
W.E. Scott
Keyword(s):  
Digital Data ◽  
Newberry Volcano ◽  
Volcano Hazards

Completed in Spring 2020: AAGRG´s new recompilation of the Alpine gravity field

2020 ◽  
Author(s):  
Hans-Jürgen Götze ◽  
Keyword(s):  
Reference Frames ◽  
Joint Inversion ◽  
Gravity Data ◽  
Bouguer Anomaly ◽  
Interdisciplinary Studies ◽  
Digital Data ◽  
Long Distance ◽  
Data Set ◽  
Homogeneous Surface ◽  
The Alps

<p>The AlpArray gravity research group (AAGRG) focuses on compiling a homogeneous surface-based gravity dataset across the Alpine area, on creating digital data sets for Bouguer-, Free Air- and isostatic anomalies. In 2016/17 all ten countries around the Alps have agreed to contribute with point/gridded gravity data and/or gravity data processing techniques to recompilation of the Alpine gravity in an area from 2° East to 23° East and 50° North to 42° North. For this recompilation, the group was able to rely on existing national data. For the Ivrea zone in the western Alps, newly surveyed data were also integrated into the database.</p><p>The AAGRG decided to present the data set of the recalculated gravity fields on a 2 km x 2 km and 4 km x 4 km grid for the public. The final products will also include the calculated values for mass corrections of the measured gravity at each grid point. This allows users to use later customized densities for their own calculations of mass corrections between the physical surface and the ellipsoidal reference. The densities used are 2 670 kg/m<sup>3</sup> for landmasses, 1 030 kg/m<sup>3</sup> for water masses above and  -1 640 kg/m<sup>3</sup> below the ellipsoid. The correction radius was set to the Hayford zone O2 (167 km). In the future, the calculation of long-distance effects of topography/bathymetry and its compensating masses (roots) are planned. The new Bouguer anomaly will be station completed (CBA) and compiled according to the most modern criteria and reference frames (both location and gravity). The concept of ellipsoidal heights implicitly includes the geophysical indirect effect. Atmospheric corrections are also considered. Special emphasis was put on the numerous lakes in the study area. They partly have a considerable effect on the gravity of stations that lie at their edges (for example, the rather deep reservoirs in the Alps). In the Ligurian and the Adriatic seas, ship data of the Bureau Gravimétrique International were used. Although not unproblematic, these data got the preference over satellite data.</p><p> It is the aim of the work of the AAGRG to release a gravity database that can be used for high-resolution modeling, interdisciplinary studies from local to regional to continental scales, as well as for joint inversion with other datasets.</p>

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