Metadata form template for Tempe Open Data.

The UNIC platform (https://unic.dipintra.it) accepts a JSON file for uploading corpus metadata based on the template here. Alternatively, use the spreadsheet template to input the corpus metadata and convert the resulting .xlsm file to JSON using this application at https://huggingface.co/spaces/nannanliu/UNIC_metadata_conversion. When opening the Excel spreadsheet template, please enable Macros, which will automatically validate your input in the columns. Please do not change the order of the columns because they are embedded with code. To add elements and components not included by the UNIC schema, create new columns after the existing ones.

The ESS-DIVE reporting format for file-level metadata (FLMD) provides granular information at the data file level to describe the contents, scope, and structure of the data file to enable comparison of data files within a data package. The FLMD are fully consistent with and augment the metadata collected at the data package level. We developed the FLMD template based on a review of a small number of existing FLMD in use at other agencies and repositories with valuable input from the Environmental Systems Science (ESS) Community. Also included is a template for a CSV Data Dictionary where users can provide file-level information about the contents of a CSV data file (e.g., define column names, provide units). Files are in .csv, .xlsx, and .md. Templates are in both .csv and .xlsx (open with e.g. Microsoft Excel, LibreOffice, or Google Sheets). Open the .md files by downloading and using a text editor (e.g. Notepad or TextEdit). Though we provide Excel templates for the file-level metadata reporting format, our instructions encourage users to 'Save the FLMD template as a CSV following the CSV Reporting Format guidance'. In addition, we developed the ESS-DIVE File Level Metadata Extractor which is a lightweight python script that can extract some FLMD fields following the recommended FLMD format and structure.

This template is a JERM compliant spreadsheet for use with gel electrophoresis data. It is in the style of the JERM MASTER template with worksheets for metadata, organism_sample, instrument and data. To conform to MIAPE-GE all worksheets are mandatory. A detailed description of MIAPE-GE is available from http://www.psidev.info/miape/MIAPE_GE_1_4.pdf

An excel template with data elements and conventions corresponding to the openLCA unit process data model. Includes LCA Commons data and metadata guidelines and definitions Resources in this dataset:Resource Title: READ ME - data dictionary. File Name: lcaCommonsSubmissionGuidelines_FINAL_2014-09-22.pdfResource Title: US Federal LCA Commons Life Cycle Inventory Unit Process Template. File Name: FedLCA_LCI_template_blank EK 7-30-2015.xlsxResource Description: Instructions: This template should be used for life cycle inventory (LCI) unit process development and is associated with an openLCA plugin to import these data into an openLCA database. See www.openLCA.org to download the latest release of openLCA for free, and to access available plugins.

This is the Excel template that was used by each of the COST Action CA16111 - ETHMIGSURVEYDATA participating countries to compile the survey metadata for the surveys initially appearing in the Ethnic and Migrant Minorities Survey Registry (https://ethmigsurveydatahub.eu/emmregistry/).

The ESS-DIVE location metadata reporting format provides instructions and templates for reporting a minimum set of metadata for discrete point locations in geographic space represented by x, y, and z coordinates. This format was created based on a need for earth and environmental science researchers to more consistently provide metadata about locations where they conduct studies. To create the format, we incorporated elements from ESS-DIVE’s community reporting formats as well as 12 additional data standards or other data resources (e.g., databases, data systems, or repositories). In the template, we ask researchers to indicate unique locations using Location IDs and indicate hierarchies of locations through parent location IDs. We also provide additional optional fields for researchers to indicate how they measured the point location and the date and time that the location was first used as a research siteThis dataset contains support documentation for the reporting format (README.md and instructions.md), a terminology guide (guide.md), a crosswalk indicating how this reporting format relates to existing standards and data resources (Location_metadata_crosswalk.csv), a data dictionary (dd.csv), file-level metadata (flmd.csv), and the location metadata templates in both CSV (Location_metadata_template.csv) and Excel formats (Location_metadata_template.xlsx).

Template (Excel Spreadsheet) designed for the EJPSOIL CarboSeq WP2 to collect (meta)data of long term agricultural field experiments for Tier2 (SOC) and where available Tier 3 (carbon input) from Europe.

This resource is a metadata compilation for Michigan geothermal related data in data exchange models submitted to the AASG National Geothermal Data System project to fulfill Year 1 and 2 data deliverables by the Michigan Geological Survey, Western Michigan University. Descriptions, links, and contact information for the ESRI Map Services created using Michigan data are also available here, including borehole temperature data, aqueous chemistry data, drill stem tests, lithology intervals data, well log data, plus, map metadata and bibliographic references data. The data and associated services were provided by the Michigan Geological Survey, Western Michigan University. The compilation is published as an Excel workbook containing header features including title, description, author, citation, originator, distributor, and resource URL links to scanned maps for download. The Excel workbook contains 6 worksheets, including information about the template, notes related to revisions of the template, resource provider information, the metadata, a field list (data mapping view) and vocabularies (data valid terms) used to populate the data worksheet. This metadata compilation was provided by the Michigan Geological Survey at Western Michigan University and made available for distribution through the National Geothermal Data System.

FRAMES is a a set of Excel metadata files and package-level descriptive metadata that are designed to facilitate and improve capture of desired metadata for ecohydrological observations. The metadata are bundled with data files into a data package and submitted to a data repository (e.g. the NGEE Tropics Data Repository) via a web form. FRAMES standardizes reporting of diverse ecohydrological and biogeochemical data for synthesis across a range of spatiotemporal scales and incorporates many best data science practices. This version of FRAMES supports observations for primarily automated measurements collected by permanently located sensors, including sap flow (tree water use), leaf surface temperature, soil water content, dendrometry (stem diameter growth increment), and solar radiation. Version 1.1 extend the controlled vocabulary and incorporates functionality to facilitate programmatic use of data and FRAMES metadata (R code available at NGEE Tropics Data Repository).

Accelerating the development of synthetic biology applications requires reproducible experimental findings. Different standards and repositories exist to exchange experimental data and metadata. However, the associated software tools often do not support a uniform data capture, encoding, and exchange of information. A connection between digital repositories is required to prevent siloing and loss of information. To this end, we developed the Experimental Data Connector (XDC). It captures experimental data and related metadata by encoding it in standard formats and storing the converted data in digital repositories. Experimental data is then uploaded to Flapjack and the metadata to SynBioHub in a consistent manner linking these repositories. This produces complete connected experimental data sets that are exchangeable. The information is captured using a single template Excel Workbook, which can be integrated into existing experimental workflow automation processes and semiautomated capture of results.

Data consist of Excel spreadsheets recording parameters, results, and analyses of diver transects using the Diver-Operated Ski. This dataset is not publicly accessible because: Data are owned by the University of Rhode Island. It can be accessed through the following means: Contact Carol Thornber from the University of Rhode Island at thornber@uri.edu. Format: Data are in excel spreadsheets, This dataset is associated with the following publication: Thornber, C.S., G. Cicchetti, L. Green-Gavrielidis, N.S. Hobbs, G. Pantoni, and D.L. Taylor. Development and use of a novel diver-operated ski for surveying nearshore rocky reef habitats. Limnology and Oceanography: Methods. American Society of Limnology and Oceanography, Lawrence, KS, USA, 22(7): 495-506, (2024).

The following 3 documents are available as an attachment to the dataset or in the dataset

Guide to the publication of your data

This guide is intended to help any community that adheres to the Open Data 29 approach wishing to publish data on the portal. It details, among other things, the process of selecting and uploading data, including a tutorial on how to use the portal.

Dataset Census Chart

This grid is intended to facilitate the work of identifying datasets within a community. Provided in PDF format on the portal, you can find the copy in Excel format in the attachments of this dataset.

Metadatasheet

This form allows communities to fill in the metadata of a dataset in order to keep track of it before publication on the portal.

This is the data set for the essay "Automatic merging of separated construction plans of hydraulic structures" submitted for Bautechnik 5/22. The data set is structured as follows: - The ZIP file "01 Original Data" contains 233 folders (named after the TU IDs) with the associated partial recordings in TIF format. The TIFs are binary compressed in CCITT Fax 4 format. 219 TUs are divided into two parts and 14 into three parts. The original data therefore consists of 480 partial recordings. - The ZIP file "02 Interim Results" contains 233 folders (named after the TU IDs) with relevant intermediate results generated during stitching. This includes the input images scaled to 10 MP, the visualization of the feature assignment(s) and the result in downscaled resolution with visualized seam lines. - The ZIP file "03_Results" contains the 170 successfully merged plans in high resolution in TIF format - The Excel file "Dataset" contains metadata on the 233 examined TUs including the DOT graph of the assignment described in the work and the correctness rating the results and the assignment to the presented sources of error. The data set was generated with the following metadata query in the IT system Digital Management of Technical Documents (DVtU): Microfilm metadata - TA (partial recording) - Number: "> 1" Document metadata - Object part: "130 (Wehrwangen, Wehrpillars)" - Object ID no .: "213 (Weir systems)" - Detail: "*[Bb]wehrung*" - Version: "01.00.00"

This resource is a metadata compilation of a Bibliography for California Geothermal Publications. It was compiled by the California Geological Survey and made available for distribution through the National Geothermal Data System. The compilation is published as an Excel workbook containing header features including title, description, author, citation, originator, distributor, and resource URL links to scanned maps for download. The Excel workbook contains 6 worksheets, including information about the template, notes related to revisions of the template, Resource provider information, the data, a field list, and vocabularies (data valid terms) used to populate the data worksheet. This resource was provided by the Arizona Geological Survey and made available for distribution through the National Geothermal Data System.

Note: Please use the following view to be able to see the entire Dataset Description: https://data.ct.gov/Environment-and-Natural-Resources/Hazardous-Waste-Portal-Manifest-Metadata/x2z6-swxe Dataset Description Outline (5 sections) • INTRODUCTION • WHY USE THE CONNECTICUT OPEN DATA PORTAL MANIFEST METADATA DATASET INSTEAD OF THE DEEP DOCUMENT ONLINE SEARCH PORTAL ITSELF? • WHAT MANIFESTS ARE INCLUDED IN DEEP’S MANIFEST PERMANENT RECORDS ARE ALSO AVAILABLE VIA THE DEEP DOCUMENT SEARCH PORTAL AND CT OPEN DATA? • HOW DOES THE PORTAL MANIFEST METADATA DATASET RELATE TO THE OTHER TWO MANIFEST DATASETS PUBLISHED IN CT OPEN DATA? • IMPORTANT NOTES INTRODUCTION • All of DEEP’s paper hazardous waste manifest records were recently scanned and “indexed”. • Indexing consisted of 6 basic pieces of information or “metadata” taken from each manifest about the Generator and stored with the scanned image. The metadata enables searches by: Site Town, Site Address, Generator Name, Generator ID Number, Manifest ID Number and Date of Shipment. • All of the metadata and scanned images are available electronically via DEEP’s Document Online Search Portal at: https://filings.deep.ct.gov/DEEPDocumentSearchPortal/ • Therefore, it is no longer necessary to visit the DEEP Records Center in Hartford for manifest records or information. • This CT Data dataset “Hazardous Waste Portal Manifest Metadata” (or “Portal Manifest Metadata”) was copied from the DEEP Document Online Search Portal, and includes only the metadata – no images. WHY USE THE CONNECTICUT OPEN DATA PORTAL MANIFEST METADATA DATASET INSTEAD OF THE DEEP DOCUMENT ONLINE SEARCH PORTAL ITSELF? The Portal Manifest Metadata is a good search tool to use along with the Portal. Searching the Portal Manifest Metadata can provide the following advantages over searching the Portal: • faster searches, especially for “large searches” - those with a large number of search returns unlimited number of search returns (Portal is limited to 500); • larger display of search returns; • search returns can be sorted and filtered online in CT Data; and • search returns and the entire dataset can be downloaded from CT Data and used offline (e.g. download to Excel format) • metadata from searches can be copied from CT Data and pasted into the Portal search fields to quickly find single scanned images. The main advantages of the Portal are: • it provides access to scanned images of manifest documents (CT Data does not); and • images can be downloaded one or multiple at a time. WHAT MANIFESTS ARE INCLUDED IN DEEP’S MANIFEST PERMANENT RECORDS ARE ALSO AVAILABLE VIA THE DEEP DOCUMENT SEARCH PORTAL AND CT OPEN DATA? All hazardous waste manifest records received and maintained by the DEEP Manifest Program; including: • manifests originating from a Connecticut Generator or sent to a Connecticut Destination Facility including manifests accompanying an exported shipment • manifests with RCRA hazardous waste listed on them (such manifests may also have non-RCRA hazardous waste listed) • manifests from a Generator with a Connecticut Generator ID number (permanent or temporary number) • manifests with sufficient quantities of RCRA hazardous waste listed for DEEP to consider the Generator to be a Small or Large Quantity Generator • manifests with PCBs listed on them from 2016 to 6-29-2018. • Note: manifests sent to a CT Destination Facility were indexed by the Connecticut or Out of State Generator. Searches by CT Designated Facility are not possible unless such facility is the Generator for the purposes of manifesting. All other manifests were considered “non-hazardous” manifests and not scanned. They were discarded after 2 years in accord with DEEP records retention schedule. Non-hazardous manifests include: • Manifests with only non-RCRA hazardous waste listed • Manifests from generators that did not have a permanent or temporary Generator ID number • Sometimes non-hazardous manifests were considered “Hazar

This resource is a metadata compilation for two published articles related to in situ stress and faulting in South Carolina. The metadata are published as an Excel workbook containing header features including title, description, author, citation, originator, distributor, and resource URL to access articles. The Excel workbook contains 6 worksheets, including information about the template, notes related to revisions of the template, resource provider information, the data, a field list, and vocabularies (data valid terms) used to populate the data worksheet. This resource was provided by the South Carolina Geological Survey and made available for distribution through the National Geothermal Data System.

The SEABORNE (Sustainable UsE And Benefits fOR mariNE) has consolidated and synthesised existing information about who is using the Reef, how it is being used and what the benefits are from this use. SEABORNE began in November 2021, and initially, we were provided with a list of potential datasets relevant to our project in a spreadsheet. To this, we continued to search various data portals online and find additional datasets relevant to our project, particularly focusing on the Great Barrier Reef. We recorded these initially in an Excel spreadsheet. We then transferred this to an MS Access database and developed a more user-friendly entry form. Within the MS Access database, there is one table that stores all the metadata records entered. And another table that stores the static preview images. There are 58 fields (which have been described in a data dictionary) – some of these are mandatory. At the moment there are 3 metadata records entered and we expect this to grow to 50-100 records by the completion of the project. Lineage: Data was produced by examining each of the datasets metadata and documenting various features of each of the individual datasets and how useful they were for examining ecosystem services. Data was initially entered in excel, then migrated to MS Access database, and then imported or read in by SHiny R app.

The data set has been downloaded via the OAI-PMH endpoint of the Berlin State Library/Staatsbibliothek zu Berlin’s Digitized Collections (https://digital.staatsbibliothek-berlin.de/oai) on March 1st 2019 and converted into common tabular formats on the basis of the provided Dublin Core metadata. It contains 146,000 records.

In addition to the bibliographic metadata, representative images of the works have been downloaded, resized to a 512 pixel maximum thumbnail image and saved in JPEG format. The image data is split into title pages and first pages. Title pages have been derived from structural metadata created by scan operators and librarians. If this information was not available, first pages of the media have been downloaded. In case of multi-volume media, title pages are not available.

In total, 141,206 images title/first pages are available.

Furthermore, the tabular data has been cleaned and extended with geo-spatial coordinates provided by the OpenStreetMap project (https://www.openstreetmap.org). The actual data processing steps are summarized in the next section. For the sake of transparency and reproducibility, the original data taken from the OAI-PMH endpoint is still present in the table.

To conclude with, various graphs in GML file format are available that can be loaded directly into graph analysis tools such as Gephi (https://gephi.org/).

The implementation of the data processing steps (incl. graph creation) are available as a Jupyter notebook provided at https://github.com/elektrobohemian/SBBrowse2018/blob/master/DataProcessing.ipynb.

Tabular Metadata

The metadata is available in Excel (cleanedData.xlsx) and CSV (cleanedData.csv) file formats with equal content.

The table contains the following columns. Italique columns have not been processed.

· title The title of the medium

· creator Its creator (family name, first name)

· subject A collection’s name as provided by the library

· type The type of medium

· format A MIME type for full metadata download

· identifier An additional identifier (most often the PPN)

· language A 3-letter language code of the medium

· date The date of creation/publication or a time span

· relation A relation to a project or collection a medium has been digitized for.

· coverage The location of publication or origin (ranging from cities to continents)

· publisher The publisher of the medium.

· rights Copyright information.

· PPN The unique identifier that can be used to find more information about the current medium in all information systems of Berlin State Library/Staatsbibliothek zu Berlin.

· spatialClean In case of multiple entries in coverage, only the first place of origin has been extracted. Additionally, characters such as question marks, brackets, or the like have been removed. The entries have been normalized regarding whitespaces and writing variants with the help of regular expressions.

· dateClean As the original date may contain various format variants to indicate unclear creation dates (e.g., time spans or question marks), this field contains a mapping to a certain point in time.

· spatialCluster The cluster ID determined with the help of the Jaro-Winkler distance on the spatialClean string. This step is needed because the spatialClean fields still contain a huge amount of orthographic variants and latinizations of geographic names.

· spatialClusterName A verbal cluster name (controlled manually).

· latitude The latitude provided by OpenStreetMap of the spatialClusterName if the location could be found.

· longitude The longitude provided by OpenStreetMap of the spatialClusterName if the location could be found.

· century A century derived from the date.

· textCluster A text cluster ID on the basis of a k-means clustering relying on the title field with a vocabulary size of 125,000 using the tf*idf model and k=5,000.

· creatorCluster A text cluster ID based on the creator field with k=20,000.

· titleImage The path to the first/title page relative to the img/ subdirectory or None in case of a multi-volume work.

Other Data

graphs.zip

Various pre-computed graphs.

img.zip

First and title pages in JPEG format.

json.zip

JSON files for each record in the following format:

ppn "PPN57346250X"

dateClean "1625"

title "M. Georgii Gutkii, Gymnasii Berlinensis Rectoris Habitus Primorum Principiorum, Seu Intelligentia; Annexae Sunt Appendicis loco Disputationes super eodem habitu tum in Academia Wittebergensi, tum in Gymnasio Berlinensi ventilatae"

creator "Gutke, Georg"

spatialClusterName "Berlin"

spatialClean "Berolini"

spatialRaw "Berolini"

mediatype "monograph"

subject "Historische Drucke"

publisher "Kallius"

lat "52.5170365"

lng "13.3888599"

textCluster "45"

creatorCluster "5040"

titleImage "titlepages/PPN57346250X.jpg"

Excel spreadsheet with the following columns of data: Date/Time (6/2016 to 10/2016) Total Gaseous Mercury Concentration (ng/m3) Sulfur dioxide concentration (ppb) Carbon monoxide concentration (ppm) Carbon dioxide concentration (ppm) Wind direction in degrees Wind speed in miles per hour Temperature in degrees celcius Percent relative humidity. This dataset is not publicly accessible because: The data used in this study were not generated or funded by the EPA. It can be accessed through the following means: The total-gaseous mercury (TGM) measurement data were collected by Dr. Lynne Gratz, Assistant Professor of Environmental Science, at Colorado College, 14 E. Cache La Poudre St. Colorado Springs, Colorado 80903 USA. This data is not available to EPA for public dissemination. Information on obtaining this data should be directed to Dr. Gratz at: lgratz@coloradocollege.edu or (719) 389-7465. The CO, SO2, temperature, wind speed, wind direction, and relative humidity were collected at the Colorado Department of Public Health & Environment (CDPHE) air monitoring location at Highway 24 in Colorado Springs. This data is already available in the public domain. Certified hourly data from this and other CDPHE air monitoring stations, including the Manitou Springs and Colorado College stations that were also mentioned in this manuscript, are available through the U.S. EPA Air Quality System (AQS) database (https://aqs.epa.gov/api) downloaded on September 1st 2017. Additional information can be obtained by emailing: cdphe.information@state.co.us303. Format: The data are in an Excel format. Citation information for this dataset can be found in the EDG's Metadata Reference Information section and Data.gov's References section.