ALBERT

Description: This paper develops the notion of “open data product”. We define an open data product as the open result of the processes through which a variety of data (open and not) are turned into accessible information through a service, infrastructure, analytics or a combination of all of them, where each step of development is designed to promote open principles. Open data products are born out of a (data) need and add value beyond simply publishing existing datasets. We argue that the process of adding value should adhere to the principles of open (geographic) data science, ensuring openness, transparency and reproducibility. We also contend that outreach, in the form of active communication and dissemination through dashboards, software and publication are key to engage end-users and ensure societal impact. Open data products have major benefits. First, they enable insights from highly sensitive, controlled and/or secure data which may not be accessible otherwise. Second, they can expand the use of commercial and administrative data for the public good leveraging on their high temporal frequency and geographic granularity. We also contend that there is a compelling need for open data products as we experience the current data revolution. New, emerging data sources are unprecedented in temporal frequency and geographical resolution, but they are large, unstructured, fragmented and often hard to access due to privacy and confidentiality concerns. By transforming raw (open or “closed”) data into ready to use open data products, new dimensions of human geographical processes can be captured and analysed, as we illustrate with existing examples. We conclude by arguing that several parallels exist between the role that open source software played in enabling research on spatial analysis in the 90 s and early 2000s, and the opportunities that open data products offer to unlock the potential of new forms of (geo-)data.

Description: The proximity literature usually treats proximity in terms of common attributes shared by agents, disregarding the relative position of an actor inside the network. This paper discusses the importance of such dimension of proximity, labelled as in-network proximity, and proposes an empirical measurement for it, assessing its impact (jointly with other dimensions of proximity) on the creation of strong knowledge network ties in ICT in the region of Trentino. The findings show that actors with higher in-network proximity are more attractive for both other central actors and peripheral ones, which is further strengthening their position within the network. In detail, the centrally positioned actors repeat collaboration with other central actors in the network, as central actors gather more ‘reputation’, signalling that they will possess the needed knowledge resources. Relatively peripheral actors, either new or not so active inside the network, seek for collaboration with relatively central actors in order to tap on knowledge resources they do not acquire.

Description: geopyter, an acronym of Geographical Python Teaching Resources, provides a hub for the distribution of ‘best practice’ in computational and spatial analytic instruction, enabling instructors to quickly and flexibly remix contributed content to suit their needs and delivery framework and encouraging contributors from around the world to ‘give back’ whether in terms of how to teach individual concepts or deliver whole courses. As such, geopyter is positioned at the confluence of two powerful streams of thought in software and education: the free and open-source software movement in which contributors help to build better software, usually on an unpaid basis, in return for having access to better tools and the recognition of their peers); and the rise of Massive Open Online Courses, which seek to radically expand access to education by moving course content online and providing access to students anywhere in the world at little or no cost. This paper sets out in greater detail the origins and inspiration for geopyter, the design of the system and, through examples, the types of innovative workflows that it enables for teachers. We believe that tools like geopyter, which build on open teaching practices and promote the development of a shared understanding of what it is to be a computational geographer represent an opportunity to expand the impact of this second wave of innovation in instruction while reducing the demands placed on those actively teaching in this area.

Description: Location cover models are aimed at siting facilities so as to provide service to demand efficiently. These models are crucial in the management, planning and decision-making of service systems in public and private sectors. As a result, location cover models have been incorporated in a range of GIS tools, either closed or open source. Among them, open-source tools are advantageous due to transparency and reproducibility. Nonetheless, the capabilities and limitations of location cover tools remain largely unknown, necessitating further investigation and assessment. To this end, this paper provides an overview of the open-source tools that are capable of structuring and solving location cover models. Case studies are provided to demonstrate access of location models through different open-source tools as well as exploring solution quality, scalability, computing performance and reproducibility. Directions for improving location cover models accessible through open-source tools are summarized based on this review.

Description: This article presents the results of public and private (car) transport accessibility modelling, which gives the room for the comparison of two types of transport throughout the whole day as well as the rush hours. Both public and private transport models are based on public available data, accessible via the Internet which is downloaded using a programming language and processed using the GIS tools. The public transport model is based on the GTFS data (General Transit Feed Specification), while the car model has been created from data on driving times derived from Google Maps® API. Both models presented in the article have been constructed for a specified period of time, namely from 5.00 am to 10.00 pm in 15-min intervals. The analysis of the above-mentioned models has allowed the comparison of differences in potential accessibility and its deviations at different times of the day. The disparities revealed by the study have indicated that there are certain times of the day when public transport is actually competitive with the private means of transport. The results of potential accessibility analysis are visualised with the use of maps, including the choropleth ones.

Description: Geographic analysis has long supported transport plans that are appropriate to local contexts. Many incumbent ‘tools of the trade’ are proprietary and were developed to support growth in motor traffic, limiting their utility for transport planners who have been tasked with twenty-first century objectives such as enabling citizen participation, reducing pollution, and increasing levels of physical activity by getting more people walking and cycling. Geographic techniques—such as route analysis, network editing, localised impact assessment and interactive map visualisation—have great potential to support modern transport planning priorities. The aim of this paper is to explore emerging open source tools for geographic analysis in transport planning, with reference to the literature and a review of open source tools that are already being used. A key finding is that a growing number of options exist, challenging the current landscape of proprietary tools. These can be classified as command-line interface, graphical user interface or web-based user interface tools and by the framework in which they were implemented, with numerous tools released as R, Python and JavaScript packages, and QGIS plugins. The review found a diverse and rapidly evolving ‘ecosystem’ tools, with 25 tools that were designed for geographic analysis to support transport planning outlined in terms of their popularity and functionality based on online documentation. They ranged in size from single-purpose tools such as the QGIS plugin AwaP to sophisticated stand-alone multi-modal traffic simulation software such as MATSim, SUMO and Veins. Building on their ability to re-use the most effective components from other open source projects, developers of open source transport planning tools can avoid ‘reinventing the wheel’ and focus on innovation, the ‘gamified’ A/B Street https://github.com/dabreegster/abstreet/#abstreet simulation software, based on OpenStreetMap, a case in point. The paper, the source code of which can be found at https://github.com/robinlovelace/open-gat, concludes that, although many of the tools reviewed are still evolving and further research is needed to understand their relative strengths and barriers to uptake, open source tools for geographic analysis in transport planning already hold great potential to help generate the strategic visions of change and evidence that is needed by transport planners in the twenty-first century.