Materials created by James Baker in June 2014 for the 108 Mapping Data course of the British Library Digital Scholarship Training Programme.

US Forest Service survey and land use maps for purchase tracts in the Enoree District, Sumter National Forest. These maps have some information on the land use history of the Calhoun Critical Zone Observatory.

The data contained in this map reflects project location data supplied by SNC grantees for grants awarded by the Sierra Nevada Conservancy. Some implementation projects predate SNC’s current policy, beginning in 2017, to acquire polygons for all new projects. As a result project location data on this map consists of a mixture of both point and polygon grant locations. Additionally, some planning, education, and other grants were region wide. These are only represented by location points provided by the grantee as well. The layers in this map may update as our Governing Board awards new grants.

The Digital Geologic-GIS Map of Grant's Headquarters at City Point, Petersburg National Battlefield, Virginia is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (cipo_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (cipo_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (cipo_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (pete_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (pete_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (cipo_geology_metadata_faq.pdf). Please read the pete_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (cipo_geology_metadata.txt or cipo_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

Map data for the original land grants in the present Enoree District of the Sumter National Forest, with dates and names of grantees. This data set consists of a GIS shapefile mosaic of the original survey plats for land grants from the king of England and the state of South Carolina for the years 1749-1851 for the Enoree District of the Sumter National Forest.

Dataset DOI: http://dx.doi.org/10.3886/ICPSR37078.v1

Professional Growth Management - Staff development.

The Municipal ZEV Clean Vehicle (CV) Rebate Program provides rebates to cities, towns, villages and counties (including New York City boroughs) to purchase or lease (for at least 36 months) new clean vehicles for fleet use.Service layer is updated annually, last updated 12/04/2024.For more information, see https://www.dec.ny.gov/chemical/8394.htmlFor more information or to download layer see https://gis.ny.gov/gisdata/inventories/details.cfm?DSID=1383Download the metadata to learn more information about how the data was created and details about the attributes. Use the links within the metadata document to expand the sections of interest. https://services6.arcgis.com/DZHaqZm9cxOD4CWM/arcgis/rest/services/Municipal_Zero_Emission_Vehicle_Rebates/FeatureServer1. The NYS DEC asks to be credited in derived products. 2. Secondary distribution of the data is not allowed. 3. Any documentation provided is an integral part of the data set. Failure to use the documentation in conjunction with the digital data constitutes a misuse of the data. 4. Although every effort has been made to ensure the accuracy of information, errors may be reflected in the data supplied. The user must be aware of data conditions and bear responsibility for the appropriate use of the information with respect to possible errors, original map scale, collection methodology, currency of data, and other conditions.

This dataset collects the slides that were presented at the Cultural Landscapes in Emerging Digital Scholarship: The Search of Conceptual and Computational Frameworks panel at DH2022 (Digital Humanities 2022: RESPONDING TO ASIAN DIVERSITY) in July 2022.

The following Panel Description was written by Oliver Streiter and Tyng-Ruey Chuang. It was submitted to the DH2022 program committee for consideration on 2021-12-11. The panel proposal was accepted on 2022-03-15.

This collection includes the five sets of presentation slides that were delivered online in a virtual session on 2022-07-27. It also includes an overview slideset prepared by Oliver Streiter, as well as the entire panel abstract included in the DH2022 Book of Abstracts. The panel abstract, marked up in TEI, can also be found on GitHub.

Cultural Landscapes in Emerging Digital Scholarship: The Search of Conceptual and Computational Frameworks

(Panel Description by Oliver Streiter and Tyng-Ruey Chuang)

We define cultural landscapes as landscapes created or modified by human societies, as landscapes of historical or archaeological importance, or as landscapes chosen for an economic, spiritual, sanctuary, commemorative or other cultural function. These landscapes are, due to their size, their internal and external heterogenity, and the process of continuous transformation, a research area that has been under-investigated in digital humanities.

In this panel we thus ask three fundamental questions. First, how can cultural landscapes be described, documented, analyzed, managed and preserved, either digitally, or through digital technologies in situ, cf. Chen and Feng (2020). Second, how can individual research or documentation efforts, conceptually or computationally, be connected to gain more holistic views of the landscape? Finally, how GIS-inspired horizontal layers can be vertically connected through linguistic or cultural descriptors?

Many aspects of cultural landscapes are complex and thus difficult to capture, e.g. in GIS-like models. These are, among others, calendric, geomantic, spiritual, and commemorative meanings of landscapes. These meanings may reside in specific geographic relations, e.g. the fengshui of a house, or outside the landscape, e.g. in the collective memory of a community. Where cultural practices, such as daily routines, evolve in a landscape, the calendar, the timing, and the pattern of recurrence of the practices are constitutional to practices and landscapes. Visual, olfactory, acoustic (Kopij and Pilch 2019, Manzetti 2019, Đorđević and Novković 2019), geomantic and climatic features of a landscape, in addition, require the adoption of multiple points of view for their spatial representation, e.g. wind strength as a function of time and place. A layered representation thus seems like a simplified surrogate, where e.g. a climatic function with parameters derived from multiple layers would be more adequate.

Cultural landscapes evolve in time. They can't be frozen, archived or stored in a museum and are vulnerable to disturbance and even destruction. In addition, cultural landscapes are experienced through time by a multiple of peoples in different dimensions and different research traditions with different expertise. The repeated efforts in producing documentation and data about them can span centuries, cf. Posluschny and Beusing (2019), and thus pose a real challenge in creating unified views. After all, each linking of independently produced layers relies on subjective interpretation and should not be hard-coded in the data.

A necessary but not sufficient condition for the success of the layered approach is thus the availability of shared indices and descriptors. But even if found and formulated, they can at best demonstrate spatial correlations, but not causal or cultural relations, which cannot be induced from correlations alone. Modular layers and their horizontal projections alone might thus produce only surface forms of holistic views. Yet, there are few alternatives in theory and practice as of now to represent deep structures and meanings. This panel thus proposes to bring forward ongoing works in documenting and researching cultural landscapes in East Asia by a diverse group of researchers, so as to present different approaches to cultural landscapes in digital scholarship.

The titles of the presentations are the following:

• The Role of Cognitive Grammars in Documenting Cultural Landscapes: Linking, mapping and interpretation -- Oliver Streiter
• Beyond GIS: Trying to make sense of Penghu cultural landscapes -- Hanna Yaqing Zhan
• Historical Landscape In the Context of Ancient Shrines -- Shoichiro HARA
• Digital Linkage of Local Knowledge: The Implementation of and Some Thoughts about the Taiwanese Religion and Folk Culture Platform (TRFC) -- Ying-Fa Hung and Jr-Jie Jang (Presented by Tyng-Ruey Chuang)
• Documenting Cultural Landscapes: Tools and Issues for Collaboration Across Boundaries -- Tyng-Ruey Chuang, Cheng-Jen Lee, Yu-Chia Monica Mu, Chia-Hsun Ally Wang, and Yu-Huang Wang

This dataset is a supplement for P.E. Stek's PhD Thesis project titled "The Development of Technology Cluster InnovationPerformance: Health and Sustainable Energy" (January 2022). The dataset covers approximately 20 high technology sectors and is useful for comparative technology sector analysis. The patent distance data used to measure the effectiveness of the cluster identification method is also included.

This map provides the location of the original land grants within present day Loudoun County from the early 1700s to early 1800s. To view a list of sortable attributes of the information, please click on the Table button in the upper right corner of the map. For additional details, please visit here.

These are the original grantings of land within the Northern Neck Proprietary by Thomas, the 6th Lord of Fairfax and/or his agents until the mid 1780s during the settlement of Virginia. The map shows the approximate location of the original land grant as well as information on the grantee, the acreage of the grant (as calculated using the GIS), the year, and additional comments. The map is intended for historical reference only, as insufficient and incomplete original boundary surveys have resulted in potential inaccurate boundaries.

The original research for all of the land grants mapped in this application was completed by historian Wynne Saffer. They were originally mapped on USGS Quadrangles at a scale of 1:24000, then scanned to a digital file and the boundaries digitized by the Loudoun County Office of Mapping and Geographic Information staff.

The orginial land grant research is located at Thomas Balch Library. The land grants can be viewed on microfilm using the Record Number as a reference. This map is also located on the Office of Mapping and Geographic Information online map gallery, which can be found here.

For more information about Loudoun County's GIS, please contact Office of Mapping and Geographic Information.

Impact Mitigation Grants to communities impacted by the development of oil and gas in the National Petroleum Reserve-Alaska (NPR-A). In accordance with Section 6506a, or former 42 U.S.C. 6508, the monies are to be used by “the State of Alaska for (a) planning, (b) construction, maintenance, and operation of essential public facilities, and (c) other necessary provisions of public service: Provided further, that in the allocation of such funds, the State shall give priority to use by subdivisions of the State most directly or severely impacted by development of oil and gas leased under this section.”Source: Department of Commerce, Community, and Economic Development Division of Community and Regional AffairsThis data is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. For more information and for questions about this data, see: DCRA NPR-A Impact Mitigation Grants and the NPR-A Annual Report.

Gender distribution of authors in tourism scholarship.

This layer was created to update the Hudson River Estuary Grants program boundaries. For purposes of protecting tributaries and upland habitat, the area eligible for Hudson River Estuary Grants includes the counties within New York State bordering the Hudson River from the Verrazano Narrows bridge to the Troy dam and tributaries including the East River to Hell Gate, the Harlem River and Kill Van Kull. A boundary of approximately 5,280 feet (1 mile) has been established as a general guideline for projects in New York City. Date created: 07/23/2024

Grants Administration CPR mini report card for FY2025Q3.

This data represents annual funding allocations through several funding initiatives in The City of Boulder's Housing and Human Services Department. Each year, the Housing and Human Services department makes nearly one hundred community grants through a variety of competitive fund rounds as well as through several sole-source contracts. A data dictionary with descriptions of the fields included in the dataset can be downloaded here.To see data separated by each of the department’s funding initiatives with some additional fields that are unique to each program, please click on the links below:Human Services Fund FundingHealth Equity Fund FundingYouth Opportunity Programs FundingHuman Relations Commission FundingTo learn more about the department’s various community funding initiatives, please visit: https://bouldercolorado.gov/human-services/community-funding.

Grants Administration Clayton Performance Review for FY2025 Q1.

Approved Culture Grants 2015.

Grants Administration CPR report card for FY2025Q1.

Number of Houston and Urban Development (HUD) public housing units (2009-2020).Source: HUD’s Real Estate Assessment Center (REAC) Physical Inspection Scores. 2009 - 2022.

Grants Administration CPR mini report card for FY2025Q1.