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DIGIS Data Model for GEOROC 2.0
No full text<h1>DIGIS Data Model</h1>
<p>The data model of the GEOROC 2.0 database, developed within the <a href="http://digis.geo.uni-goettingen.de" rel="nofollow">DIGIS</a> project. A simplified overview of the schema can be found in GEOROC2.0_schema.png.</p>
<p>The model is based on the Observations Data Model Version 2 (ODM2; <a href="http://dx.doi.org/10.1016/j.envsoft.2016.01.010" rel="nofollow">Horsburgh et al., 2016</a>) with minor modifications in accordance with the PetDB use case (<a href="http://dx.doi.org/10.5334/dsj-2017-004" rel="nofollow">Hsu et al. 2017</a>) and the <a href="https://earthchem.org/" rel="nofollow">EarthChem</a> ECDB model. For more information on ODM2 visit <a href="https://www.odm2.org/" rel="nofollow">https://www.odm2.org/</a>.</p>
<h2><a href="https://github.com/digis-georoc/DIGIS-Datamodel#the-georoc-database"></a></h2>
<h2>The GEOROC Database</h2>
<p>The GEOROC Database (Geochemistry of Rocks of the Oceans and Continents) is a comprehensive collection of published analyses of igneous and metamorphic rocks and minerals. It contains major and trace element concentrations, radiogenic and nonradiogenic isotope ratios as well as analytical ages for whole rocks, glasses, minerals and inclusions. Metadata include geospatial and other sample information, analytical details and references.</p>
<p>The GEOROC Database was established at the Max Planck Institute for Chemistry in Mainz (Germany). In 2021, the database was moved to Göttingen University, where it continues to be curated as part of the <a href="http://digis.geo.uni-goettingen.de" rel="nofollow">DIGIS</a> project of the Department of Geochemistry and Isotope Geology at the Geoscience Centre (GZG) and the University and State Library (SUB). Development for GEOROC 2.0 includes a new data model for greater interoperability, options to contribute data, and improved access to the database.</p>
<p>For more information, and to access the data, visit the GEOROC website: <a href="https://georoc.eu/" rel="nofollow">https://georoc.eu/</a>.</p>
<p>DIGIS is funded through the Scientific Library Services and Information Systems (LIS) programme of the German Research Foundation (DFG, grant number: <a href="https://gepris.dfg.de/gepris/projekt/437919684?language=en" rel="nofollow">437919684</a>).</p>
<h2><a href="https://github.com/digis-georoc/DIGIS-Datamodel#model-setup"></a></h2>
<h2>Model Setup</h2>
<p>You can generate a copy of the GEOROC 2.0 data model by running the SQL script located in <code>/sql_scripts</code>. Note that this script is written for a PostgreSQL database - if you want to use a different database management system, you will have to adapt the script to your specific SQL dialect.</p>
<p>This repository contains the new data model only. Visit <a href="https://georoc.eu/" rel="nofollow">https://georoc.eu/</a> for access to the data held within the GEOROC database.</p>
<h2><a href="https://github.com/digis-georoc/DIGIS-Datamodel#future-goals"></a></h2>
<h2>Future Goals</h2>
<p>We are working on an API, based upon this data model, to allow native access to the GEOROC data holdings and to facilitate seamless data exchange with our partners at EarthChem as well as other geochemical data systems.</p>
<p>For any questions or if you would like to get involved, get in touch via email: <a href="mailto:[email protected]">[email protected]</a>.</p>
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A single web-interface to access, visualise and model data from multiple geo- and cosmochemical databases
No full textOvercoming Fragmentation of Geochemical Data Resources: Collaboration between EarthChem, Astromat, GEOROC, and MetBase
No full textGlobal geochemical datasets are increasingly valuable for solving research questions in geochemistry, volcanology and beyond. To support new research, open sharing and access of geochemical data needs to be easy for researchers so they can take full advantage of the rapidly growing volume of data generated in laboratories across the globe, and to comply with the principles of Open Science. Instead, the fragmented landscape of geochemical data systems makes it difficult for researchers to find, access, and contribute their data: Geochemical data are curated and published in a range of thematic, institutional, and programmatic data systems that differ in architecture, metadata schemas, terminology, and data output formats. Researchers have to figure out where to obtain the data they need; learn to use different search applications; retrieve data from multiple databases and painstakingly reformat the datasets they obtained from different systems to integrate them. They need to select an appropriate repository for their data, and potentially work with different submission systems and templates. Collaboration among geochemical data systems is a critical step to overcome this fragmentation and facilitate geochemical data management and access for the research community by coordinating, aligning, and integrating their systems. Through collaboration, data repositories and databases can also leverage each other’s expertise and resources to operate their services more effectively and efficiently.
We here report about new collaborative efforts among four geochemical data systems that aim to harmonize and integrate their data holdings and software ecosystem for the benefit of the research community and to improve their sustainability: EarthChem (https://earthchem.org/), GEOROC (https://georoc.eu/), MetBase (https://metbase.org/), and the Astromaterials Data System (https://www.astromat.org/). Building on the long-term collaboration between EarthChem and GEOROC, this collaboration leverages the new development of the Astromaterials Data System with modern technology and two new projects funded to overhaul the infrastructure of the GEOROC and MetBase databases as an opportunity to jointly develop a more resilient, sustainable platform for data exchange. Results of the collaboration so far include: a) alignment of the Astronaut and MetBase data models b) migration of the MetBase data holdings into the Astromat synthesis database; c) alignment of the EarthChem and GEOROC data models; d) new automated synchronization process of GEOROC data to the ECP; e) harmonized vocabularies for chemical variables, analytical methods (Others are in development in alignment with emerging efforts of the OneGeochemstry initiative); f) design of the future shared architecture of EarthChem and GEOROC that includes plans for a joint data entry tool for curators and a single data submission platform for researchers to contribute their data to the affiliated domain repositories.
The ultimate goal of this harmonization between EarthChem, Astromat, GEOROC and MetBase is to make it easier for researchers to access and contribute data. We hope to integrate further systems in the future, building on ongoing collaborations with the Australian Geochemistry Network, the US Geological Survey, SAMIS (Sample Analysis Microinformation System), the GFZ Data Services, and the Sparrow software
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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