A geo-temporal information extraction service for processing descriptive metadata in digital libraries

In the context of digital map libraries, resources are usually described according to metadata records that define the relevant subject, location, time-span, format and keywords. On what concerns locations and time-spans, metadata records are often incomplete or they provide information in a way that is not machine-understandable (e.g. textual descriptions). This paper presents techniques for extracting geotemporal information from text, using relatively simple text mining methods that leverage on a Web gazetteer service. The idea is to go from human-made geotemporal referencing (i.e. using place and period names in textual expressions) into geo-spatial coordinates and time-spans. A prototype system, implementing the proposed methods, is described in detail. Experimental results demonstrate the efficiency and accuracy of the proposed approaches

Historical collaborative geocoding

The latest developments in digital have provided large data sets that can increasingly easily be accessed and used. These data sets often contain indirect localisation information, such as historical addresses. Historical geocoding is the process of transforming the indirect localisation information to direct localisation that can be placed on a map, which enables spatial analysis and cross-referencing. Many efficient geocoders exist for current addresses, but they do not deal with the temporal aspect and are based on a strict hierarchy (..., city, street, house number) that is hard or impossible to use with historical data. Indeed historical data are full of uncertainties (temporal aspect, semantic aspect, spatial precision, confidence in historical source, ...) that can not be resolved, as there is no way to go back in time to check. We propose an open source, open data, extensible solution for geocoding that is based on the building of gazetteers composed of geohistorical objects extracted from historical topographical maps. Once the gazetteers are available, geocoding an historical address is a matter of finding the geohistorical object in the gazetteers that is the best match to the historical address. The matching criteriae are customisable and include several dimensions (fuzzy semantic, fuzzy temporal, scale, spatial precision ...). As the goal is to facilitate historical work, we also propose web-based user interfaces that help geocode (one address or batch mode) and display over current or historical topographical maps, so that they can be checked and collaboratively edited. The system is tested on Paris city for the 19-20th centuries, shows high returns rate and is fast enough to be used interactively.Comment: WORKING PAPE

Potential Indirect Relationships in Productive Networks

Productive Networks, such as Social Networks Services, organize evidence about human behavior. This evidence is independent of the network content type, and may support the discovery of new relationships between users and content, or with other users. These indirect relationships are important for recommendation systems, and systems where potential relationships between users and content (e.g., locations) is relevant, such as with the emergency management domain, where the discovery of relationships between users and locations on productive networks may enable the identification of population density variations, increasing the accuracy of emergency alerts. This thesis presents a Productive Networks model, which enables the development of a methodology for indirect relationships discovery, using the metadata on the network, and avoiding the computational cost of content analysis. We designed and conducted a set of experiments to evaluate our proposals. Our results are twofold: firstly, the productive network model is sufficiently robust to represent a wide range of networks; secondly, the indirect relationship discovery methodology successfully identifies relevant relationships between users and content. We also present applications of the model and methodology in several contexts

An Evaluation of Open Source Geographic Information Systems Routing Tools in Vaccine Delivery in Kano State, Northern Nigeria

The recent proliferation of online/desktop/mobile open source geographic information systems (GIS)routing tools such as qgis road graph plugin (QRG), open street routing machine (OSRM), google maps engine (GME), graphhopper (GH), and Osm And has led to the need to provide a method for comparatively evaluating the strength and weakness of these routing tools. This is crucial in view of its implication on the prospect and otherwise of routing related projects such as supply chain logistics, supply/delivery operations, and emergency services, among others. In this paper, comparative evaluation of these tools has been carried out using drive test survey and desktop routing estimation with respect to routine vaccine delivery in Kano, Nigeria. Kano state being one of the states in Nigeria with huge burden of health challenges with records of 3062 maternal death between 2005 – 2010(Ibrahim, 2014) . Thus vaccine delivery is one of such healthcare delivery programmes used to addressing some of these health challenges. The primary objective of this paper is to demonstrate comparative advantage of using open sourceGIS routing tools to optimize vaccine delivery process such that there would be significant reduction in logistics, manpower and cost associated with routine vaccine delivery. The capacity of the selected open source GIS routing tools was evaluated against this backdrop. Hence drive test survey was used to define the benchmark for determine the best rank among these desktop routing tools. The drive test survey was carried on selected number of delivery routes and the results were compared with values derived from desktop routing estimation using these tools. Two rounds of drive test survey were carried out for the delivery routes and an average was considered in order to minimum possible error associated with possible inconsistent in driving behavior. Significant discrepancies were observed in the outputs derived between desktop (QRG), online (OSRM, GME, GH) and mobile (Osm And) routing platforms. OSM vector base map was used across all the routing tools except GME.The overall outcome indicated QRG had the highest cumulative error margin of 67.52km while the lowest was reported for GraphHoper (46.17km) using same OSM base map. This is an indication that the routing algorithm used is not the same. When compared with GME that uses different base map, the cumulative error margin is very close (QRG – 67.52, GME – 55.99), an indication that similar routing algorithm has been used. Drive test outcome may not be sufficient to determine best or otherwise routing tool, it may be appropriate to consider other valuable criteria for the purpose of ranking these tools. Hence, those criteria were not limited to drive test/routing output error margin, others include capacity for multiple routing, base map completeness/content, support for traffic input, routing platform, and alternative routing option. With these considerations, QRG was ranked 1st. while OsmAnd (5) was least ranked. GME and GH had same ranking (2). QRG was ranked above other OSM based routing tools because it uses desktop platform and a capacity to integrate traffic input. It was ranked above GME majorly because of its robust OSM base map compared to google base map