A Cartographic Workflow Manual for Endangered Species Conservation

In response to global consumer demand for rare and exotic wildlife products, poaching of endangered species has become pervasive around the world (Eliason 1999). Despite the enactment of CITES, and other international efforts to protect vulnerable species from overexploitation, the global market for illegal wildlife products is estimated as high as $20-billion a year industry (Wyler 2008). Within important wildlife habitat sites, law enforcement struggle to curb rampant poaching that threatens the ultimate survival of many endangered species (Jachmann 2008; Rowcliffe 2004). Law-enforcement agencies responsible for protecting wildlife from poachers often lack geospatial tools that could greatly improve the effectiveness of their efforts. These tools include accurate topographic maps with the appropriate scale and the level of detail necessary for navigating in difficult and dangerous terrain, and GIS base data needed to monitor and evaluate the effectiveness of patrols (Pickles 2015). Recently, collaborations between the University of Montana (UM) and the large cat advocacy group Panthera, have enabled the production of geospatial packages for four protected areas of concern. These packages include printed topographic map series, GPS base-maps and comprehensive GIS base data. Throughout the creation of these packages, UM faculty and students have developed a nuanced workflow for this process using GIS and graphic design software. Until 2018, this workflow had yet to be fully documented. This document presents this workflow in the form of a cartographic manual, including step-by-step methods for creating appropriate geospatial packages. The goal of this document is to increase the efficiency of future cartographic collaborations between UM and conservation-minded groups, while providing valuable educational resources for UM students in GIS and cartography

Semantic enrichment for enhancing LAM data and supporting digital humanities. Review article

With the rapid development of the digital humanities (DH) field, demands for historical and cultural heritage data have generated deep interest in the data provided by libraries, archives, and museums (LAMs). In order to enhance LAM data’s quality and discoverability while enabling a self-sustaining ecosystem, “semantic enrichment” becomes a strategy increasingly used by LAMs during recent years. This article introduces a number of semantic enrichment methods and efforts that can be applied to LAM data at various levels, aiming to support deeper and wider exploration and use of LAM data in DH research. The real cases, research projects, experiments, and pilot studies shared in this article demonstrate endless potential for LAM data, whether they are structured, semi-structured, or unstructured, regardless of what types of original artifacts carry the data. Following their roadmaps would encourage more effective initiatives and strengthen this effort to maximize LAM data’s discoverability, use- and reuse-ability, and their value in the mainstream of DH and Semantic Web