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A filter circuit board for the Earthworm Seismic Data Acquisition System

The Earthworm system is a seismic network data acquisition and processing system used by the Northern California Seismic Network as well as many other seismic networks. The input to the system is comprised of many realtime electronic waveforms fed to a multi-channel digitizer on a PC platform. The digitizer consists of one or more National Instruments Corp. AMUX–64T multiplexer boards attached to an A/D converter board located in the computer. Originally, passive filters were installed on the multiplexers to eliminate electronic noise picked up in cabling. It was later discovered that a small amount of crosstalk occurred between successive channels in the digitizing sequence. Though small, this crosstalk will cause what appear to be small earthquake arrivals at the wrong time on some channels. This can result in erroneous calculation of earthquake arrival times, particularly by automated algorithms. To deal with this problem, an Earthworm filter board was developed to provide the needed filtering while eliminating crosstalk. This report describes the tests performed to find a suitable solution, and the design of the circuit board. Also included are all the details needed to build and install this board in an Earthworm system or any other system using the AMUX–64T board. Available below is the report in PDF format as well as an archive file containing the circuit board manufacturing information.

Open-File Report

Calculation of streamflow statistics for Ontario and the Great Lakes states

Basic, flow-duration, and n-day frequency statistics were calculated for 779 current and historical streamflow gages in Ontario and 3,157 streamflow gages in the Great Lakes states with length-of-record daily mean streamflow data ending on December 31, 2000 and September 30, 2001, respectively. The statistics were determined using the U.S. Geological Survey’s SWSTAT and IOWDM, ANNIE, and LIBANNE software and Linux shell and PERL programming that enabled the mass processing of the data and calculation of the statistics. Verification exercises were performed to assess the accuracy of the processing and calculations. The statistics and descriptions, longitudes and latitudes, and drainage areas for each of the streamflow gages are summarized in ASCII text files and ESRI shapefiles.

Illinois, Indiana, Michigan, Minnesota, New York,

Carbonatites of the world, explored deposits of Nb and REE— Database and grade and tonnage models

This report is based on published tonnage and grade data on 58 Nb- and rare-earth-element (REE)-bearing carbonatite deposits that are mostly well explored and are partially mined or contain resources of these elements. The deposits represent only a part of the known 527 carbonatites around the world, but they are characterized by reliable quantitative data on ore tonnages and grades of niobium and REE. Grade and tonnage models are an important component of mineral resource assessments. Carbonatites present one of the main natural sources of niobium and rare-earth elements, the economic importance of which grows consistently. A purpose of this report is to update earlier publications. New information about known deposits, as well as data on new deposits published during the last decade, are incorporated in the present paper. The compiled database (appendix 1; linked to right) contains 60 explored Nb- and REE-bearing carbonatite deposits - resources of 55 of these deposits are taken from publications. In the present updated grade-tonnage model we have added 24 deposits comparing with the previous model of Singer (1998). Resources of most deposits are residuum ores in the upper part of carbonatite bodies. Mineral-deposit models are important in exploration planning and quantitative resource assessments for two reasons: (1) grades and tonnages among deposit types vary significantly, and (2) deposits of different types are present in distinct geologic settings that can be identified from geologic maps. Mineral-deposit models combine the diverse geoscience information on geology, mineral occurrences, geophysics, and geochemistry used in resource assessments and mineral exploration. Globally based deposit models allow recognition of important features and demonstrate how common different features are. Well-designed deposit models allow geologists to deduce possible mineral-deposit types in a given geologic environment, and the grade and tonnage models allow economists to estimate the possible economic viability of these resources. Thus, mineral-deposit models play a central role in presenting geoscience information in a useful form to policy makers. The foundation of mineral-deposit models is information about known deposits. This publication presents the latest geologic information and newly developed grade and tonnage models for Nb- and REE-carbonatite deposits in digital form. The publication contains computer files with information on deposits from around the world. It also contains a text file allowing locations of all deposits to be plotted in geographic information system (GIS) programs. The data are presented in FileMaker Pro as well as in .xls and text files to make the information available to a broadly based audience. The value of this information and any derived analyses depends critically on the consistent manner of data gathering. For this reason, we first discuss the rules used in this compilation. Next, the fields of the database are explained. Finally, we provide new grade and tonnage models and analysis of the information in the file.

Open-File Report

A linked GeoData map for enabling information access

Overview The Geospatial Semantic Web (GSW) is an emerging technology that uses the Internet for more effective knowledge engineering and information extraction. Among the aims of the GSW are to structure the semantic specifications of data to reduce ambiguity and to link those data more efficiently. The data are stored as triples, the basic data unit in graph databases, which are similar to the vector data model of geographic information systems (GIS); that is, a node-edge-node model that forms a graph of semantically related information. The GSW is supported by emerging technologies such as linked geospatial data, described below, that enable it to store and manage geographical data that require new cartographic methods for visualization. This report describes a map that can interact with linked geospatial data using a simulation of a data query approach called the browsable graph to find information that is semantically related to a subject of interest, visualized using the Data Driven Documents (D3) library. Such a semantically enabled map functions as a map knowledge base (MKB) (Varanka and Usery, 2017). A MKB differs from a database in an important way. The central element of a triple, alternatively called the edge or property, is composed of a logic formalization that structures the relation between the first and third parts, the nodes or objects. Node-edge-node represents the graphic form of the triple, and the subject-property-object terms represent the data structure. Object classes connect to build a federated graph, similar to a network in visual form. Because the triple property is a logical statement (a predicate), the data graph represents logical propositions or assertions accepted to be true about the subject matter. These logical formalizations can be manipulated to calculate new triples, representing inferred logical assertions, from the existing data. To demonstrate a MKB system, a technical proof-of-concept is developed that uses geographically attributed Resource Description Framework (RDF) serializations of linked data for mapping. The proof-of-concept focuses on accessing triple data from visual elements of a geographic map as the interface to the MKB. The map interface is embedded with other essential functions such as SPARQL Protocol and RDF Query Language (SPARQL) data query endpoint services and reasoning capabilities of Apache Marmotta (Apache Software Foundation, 2017). An RDF database of the Geographic Names Information System (GNIS), which contains official names of domestic feature in the United States, was linked to a county data layer from The National Map of the U.S. Geological Survey. The county data are part of a broader Government Units theme offered to the public as Esri shapefiles. The shapefile used to draw the map itself was converted to a geographic-oriented JavaScript Object Notation (JSON) (GeoJSON) format and linked through various properties with a linked geodata version of the GNIS database called “GNIS–LD” (Butler and others, 2016; B. Regalia and others, University of California-Santa Barbara, written commun., 2017). The GNIS–LD files originated in Terse RDF Triple Language (Turtle) format but were converted to a JSON format specialized in linked data, “JSON–LD” (Beckett and Berners-Lee, 2011; Sorny and others, 2014). The GNIS–LD database is composed of roughly three predominant triple data graphs: Features, Names, and History. The graphs include a set of namespace prefixes used by each of the attributes. Predefining the prefixes made the conversion to the JSON–LD format simple to complete because Turtle and JSON–LD are variant specifications of the basic RDF concept. To convert a shapefile into GeoJSON format to capture the geospatial coordinate geometry objects, an online converter, Mapshaper, was used (Bloch, 2013). To convert the Turtle files, a custom converter written in Java reconstructs the files by parsing each grouping of attributes belonging to one subject and pasting the data into a new file that follows the syntax of JSON–LD. Additionally, the Features file contained its own set of geometries, which was exported into a separate JSON–LD file along with its elevation value to form a fourth file, named “features-geo.json.” Extracted data from external files can be represented in HyperText Markup Language (HTML) path objects. The goal was to import multiple JSON–LD files using this approach.

Open-File Report

Computer-generated mineral commodity deposit maps

This report describes an automated method of generating deposit maps of mineral commodity information. In addition, it serves as a user's manual for the authors' mapping system. Procedures were developed which allow commodity specialists to enter deposit information, retrieve selected data, and plot deposit symbols in any geographic area within the conterminous United States. The mapping system uses both micro- and mainframe computers. The microcomputer is used to input and retrieve information, thus minimizing computing charges. The mainframe computer is used to generate map plots which are printed by a Calcomp plotter. Selector V data base system is employed for input and retrieval on the microcomputer. A general mapping program (Genmap) was written in FORTRAN for use on the mainframe computer. Genmap can plot fifteen symbol types (for point locations) in three sizes. The user can assign symbol types to data items interactively. Individual map symbols can be labeled with a number or the deposit name. Genmap also provides several geographic boundary file and window options.

Open-File Report