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Assessing the influence of indoor mapping sources for indoor spatial analysis of physical distancing 评估室内测绘资源对物理距离室内空间分析的影响
IF 1.4 Q2 Social Sciences Pub Date : 2023-12-21 DOI: 10.5311/josis.2023.27.296
Alan T. Murray, Jiwon Baik, Hannah Malak
GIScience and spatial information contributions to indoor mapping and navigation are many, but there remain significant challenges. Indoor environments are where people spend most of their time, socializing, working, learning, exercising, etc. During times of emergencies, disease outbreaks, and crises, indoor management and planning must be prepared to handle such events, yet doing so is often hindered by a lack of supporting spatial information and appropriate analytics. This paper focuses on COVID-19 mitigation measures to reduce disease transmission through physical distancing in indoor spaces, such as classrooms, offices, dining commons, restaurants, and entertainment venues. Geographical data to support indoor environments is discussed, particularly issues of acquisition, spatial data uncertainty, and implications for spatial analytics. Planning for classroom physical distancing on a university campus highlights capabilities, issues, and challenges, with a comparison made between previous studies relying on architectural data and more precise information obtained using LiDAR. 
GIScience 和空间信息对室内制图和导航的贡献是多方面的,但仍然存在巨大的挑战。室内环境是人们度过社交、工作、学习、锻炼等大部分时间的地方。在发生紧急事件、疾病爆发和危机时,室内管理和规划部门必须做好应对此类事件的准备,但由于缺乏支持性空间信息和适当的分析方法,这项工作往往受到阻碍。本文重点介绍 COVID-19 缓解措施,通过在教室、办公室、餐厅、餐馆和娱乐场所等室内空间拉开物理距离来减少疾病传播。本文讨论了支持室内环境的地理数据,特别是获取问题、空间数据的不确定性以及对空间分析的影响。对大学校园教室物理距离的规划突出强调了能力、问题和挑战,并对以前依靠建筑数据进行的研究和使用激光雷达获得的更精确信息进行了比较。
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引用次数: 0
Maximizing the value of a volunteer: A novel method for prioritizing humanitarian VGI activities 志愿者价值最大化:确定人道主义志愿服务活动优先次序的新方法
IF 1.4 Q2 Social Sciences Pub Date : 2023-12-21 DOI: 10.5311/josis.2023.27.246
Kirsty Watkinson, Jonathan J. Huck, Angela Harris
As a consequence of their reliance on a scarce volunteer resource, humanitarian mapping organizations must prioritize their mapping activities. For mapping in anticipation of a crisis or mapping in support of long-term crises, the only method available to organizations is an estimation of the "completeness" of the map, with organizations directing volunteers to map areas where data are missing. Whilst this method is suitable for organizations that focus on general map improvement, for those who create data for a specific reason (e.g., drinking water provision) the method is sub-optimal. In this article, we present a new method of humanitarian mapping prioritization, that considers the purpose of map data collection. The method identifies locations where contributions by volunteers are expected to have the biggest impact on the desired use of the map data and therefore maximizes the value gained from volunteer contributions. We explain our method using the example of measuring distance to healthcare and demonstrate its superior ability to consider the context of map data over generic estimations of map "completeness". Our method provides humanitarian mapping organizations with an easily reproducible and low cost method and an opportunity to make better informed decisions about mapping prioritization, when the purpose of map data collection is known. Using our method, organizations will be able to maximize the value gained from a scarce volunteer resource and increase the efficiency of humanitarian map data production. 
由于依赖稀缺的志愿者资源,人道主义制图组织必须确定制图活动的优先次序。对于预测危机的制图或支持长期危机的制图,组织可用的唯一方法是估计地图的 "完整性",由组织引导志愿者对数据缺失的区域进行制图。虽然这种方法适用于那些专注于一般地图改进的组织,但对于那些因特定原因(如饮用水供应)而创建数据的组织来说,这种方法并不理想。在本文中,我们提出了一种考虑到地图数据收集目的的人道主义地图优先级排序新方法。该方法可确定志愿者贡献对地图数据的预期用途影响最大的地点,从而使志愿者贡献的价值最大化。我们以测量医疗保健的距离为例解释了我们的方法,并展示了该方法在考虑地图数据背景方面优于一般地图 "完整性 "估算的能力。我们的方法为人道主义制图组织提供了一种易于复制、成本低廉的方法,并为其提供了一个机会,在了解地图数据收集目的的情况下,就制图优先顺序做出更明智的决策。使用我们的方法,各组织将能够最大限度地利用稀缺的志愿者资源,并提高人道主义地图数据制作的效率。
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引用次数: 0
Procedural metadata for geographic information using an algebra of core concept transformations 使用核心概念转换代数的地理信息程序元数据
IF 1.4 Q2 Social Sciences Pub Date : 2023-12-21 DOI: 10.5311/josis.2023.27.268
Niels Steenbergen, Eric Top, E. Nyamsuren, Simon Scheider
Transformations are essential for dealing with geographic information. They are involved not only in the conversion between geodata formats and reference systems, but also in turning geodata into useful information according to some purpose. However, since a transformation can be implemented in various formats and tools, its function and purpose usually remains hidden underneath the technicalities of a workflow. To automate geographic information procedures, we therefore need to model the transformations implemented by workflows on a conceptual level, as a form of procedural knowledge. Although core concepts of spatial information provide a useful level of description in this respect, we currently lack a model for the space of possible transformations between such concepts. In this article, we present the algebra of core concept transformations (CCT). It consists of a type hierarchy which models core concepts as relation types, and a set of basic transformations described in terms of function signatures that use such types. We enrich GIS workflows with abstract machine-readable metadata, by compiling algebraic tool descriptions and inferring goal concepts across a workflow. In this article, we show how such procedural metadata can be used to retrieve workflows based on task descriptions derived from geo-analytical questions. Transformations can be queried independently from their implementations or data formats.
转换对于处理地理信息至关重要。它们不仅涉及地理数据格式和参考系统之间的转换,还涉及根据某种目的将地理数据转化为有用信息。然而,由于转换可以通过各种格式和工具实现,其功能和目的通常隐藏在工作流程的技术细节之下。因此,为了实现地理信息程序的自动化,我们需要在概念层面上对工作流程实施的转换进行建模,将其作为一种程序知识。虽然空间信息的核心概念在这方面提供了一个有用的描述层次,但我们目前还缺乏一个模型来描述这些概念之间可能的转换空间。在本文中,我们提出了核心概念转换代数(CCT)。它包括一个将核心概念建模为关系类型的类型层次结构,以及一组使用这些类型的函数签名来描述的基本转换。我们通过编译代数工具描述和推断整个工作流中的目标概念,用机器可读的抽象元数据来丰富 GIS 工作流。在本文中,我们将展示如何利用此类程序元数据,根据从地理分析问题中得出的任务描述检索工作流。转换可以独立于其实现或数据格式进行查询。
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引用次数: 0
More is less - Adding zoom levels in multi-scale maps to reduce the need for zooming interactions 多即是少--在多比例尺地图中增加缩放级别,减少缩放交互的需要
IF 1.4 Q2 Social Sciences Pub Date : 2023-12-21 DOI: 10.5311/josis.2023.27.277
Marion Dumont, G. Touya, Cécile Duchêne
When you zoom in or out of current multi-scale cartographic applications, it is common to feel lost and disoriented for a few seconds because dimensions and map symbols have changed. To make the exploration of these multi-scale maps more fluid, one option is to design maps where the transformations due to scale change are more progressive. This paper proposes to use cartographic generalization techniques to design these multi-scale maps with additional intermediate scales to improve progressiveness. These more progressive maps are tested in a user study with a task requiring multiple zooms in and out. The users perform better with the progressive maps, and in particular, the total quantity of required zooming is reduced compared to maps without additional intermediate scales. However, the survey is not fully conclusive on task performance due to the complexity of such a survey with real maps. This difficulty in assessing how well progressive map generalisation reduces disorientation is discussed and guidelines are proposed to design further studies. 
当您放大或缩小当前的多比例尺制图应用程序时,通常会因为尺寸和地图符号发生了变化而在几秒钟内感到迷失方向。为了让人们更流畅地探索这些多比例尺地图,一种方法是设计出比例尺变化所带来的转换更加渐进的地图。本文建议使用制图概括技术来设计这些多比例尺地图,增加中间比例尺以提高渐进性。这些渐进性更强的地图在一项用户研究中进行了测试,该研究的任务要求多次放大和缩小。与没有额外中间比例尺的地图相比,用户在使用渐进式地图时表现更佳,尤其是所需缩放的总量减少了。不过,由于使用真实地图进行调查的复杂性,这项调查并不能完全确定任务的完成情况。本文讨论了评估渐进式地图概括如何有效减少迷失方向的困难,并提出了设计进一步研究的指导原则。
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引用次数: 0
Distributed spatial data sharing: a new model for data ownership and access control 分布式空间数据共享:数据所有权和访问控制的新模式
IF 1.4 Q2 Social Sciences Pub Date : 2023-12-21 DOI: 10.5311/josis.2023.27.220
Majid Hojati, Rob Feick, Steven Roberts, Carson Farmer, Colin Robertson
With the advent of new technologies and broader participation in geospatial data production, new challenges emerge for spatial data sharing. Spatial data sharing practices are increasingly transacted through and, to varying degrees, controlled by a handful of privately controlled corporate services. Data production has evolved from being largely centralized, expert-oriented, and authoritative in nature to now also include hybrid data collection processes involving distributed assemblages of individuals who share and co-produce spatial data while interacting through centralized architectures and control regimes. These changes have resulted mainly from technological and social changes linked to the emergence of Web 2.0 and widely available Internet participation tools. Concerns about how spatial data access and sharing are controlled, particularly for sensitive or personally-identifying data, have increased interest in distributed file technologies that allow users to share resources independently of centralized platforms. This paper examines how spatial data sharing practices may move towards a more decentralized sharing ecosystem as technologies for a further distributed web mature. We identify this transition as increasingly hybridized forms of data ownership and access control concerns are coupled with new distributed systems (e.g., Web 3.0). We also discuss opportunities and barriers to distributed spatial data sharing, including possible benefits for big geographic data management and the need  for protocols to share, integrate, and process spatial data shared on distributed networks.
随着新技术的出现和地理空间数据生产的广泛参与,空间数据共享面临着新的挑战。空间数据共享实践越来越多地通过少数私人控制的企业服务进行交易,并在不同程度上受其控制。数据生产已从主要是集中式、专家导向型和权威性的,发展到现在还包括混合数据收集过程,涉及个人的分布式集合,他们在通过集中式架构和控制制度进行互动的同时,共享和共同生产空间数据。这些变化主要源于与 Web 2.0 和广泛使用的互联网参与工具的出现相关的技术和社会变革。由于人们对空间数据访问和共享的控制方式,尤其是敏感数据或个人身份数据的控制方式感到担忧,因此人们对允许用户独立于集中式平台共享资源的分布式文件技术越来越感兴趣。本文探讨了随着分布式网络技术的进一步成熟,空间数据共享实践如何向更加分散的共享生态系统转变。我们认为,随着数据所有权和访问控制问题的日益混合形式与新的分布式系统(如 Web 3.0)相结合,这种转变也会发生。我们还讨论了分布式空间数据共享的机遇和障碍,包括对大型地理数据管理可能带来的好处,以及需要制定协议来共享、整合和处理分布式网络上共享的空间数据。
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引用次数: 0
Reimagining GIScience education for enhanced employability 重新规划 GIScience 教育,提高就业能力
IF 1.4 Q2 Social Sciences Pub Date : 2023-12-21 DOI: 10.5311/josis.2023.27.307
Hongyu Zhang
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引用次数: 0
Spatial Information Science in 2023 2023年的空间信息科学
IF 1.4 Q2 Social Sciences Pub Date : 2023-06-30 DOI: 10.5311/josis.2023.26.305
Benjamin Adams, S. Dodge, R. Purves
Since our 10th anniversary issues published in 2020 [1, 2], JOSIS has continued to publish a number of excellent research articles on many of the topics highlighted by our editorial board in their invited papers. These include articles on crowdsourcing [10], place [18, 17, 23, 13, 3], spatial language [5, 15, 24, 19], GeoAI [14], movement analysis [26, 11], urban analysis and wayfinding [16, 21, 7], methods for spatial analysis and uncertainty [22, 25, 6, 20], environmental data and modeling [8, 12, 9], and qualitative spatial reasoning [4]. We are happy to also note that these articles represent research conducted around the world, with authors based in Australia, Bangladesh, Canada, Croatia, France, Germany, Lebanon, the Netherlands, New Zealand, Portugal, South Africa, Switzerland, the United Kingdom, and the United States. In addition to five research articles, this issue contains two commentaries that revisit thematic questions about the field of GIScience both past and present. The first of these by René Westerholt examines how GIScience is taught in the interdisciplinary contexts and how that affects the identity of the field. The second by Christophe Claramunt and Matthew Dube looks at the state of the field through the lens of the original NCGIA research agenda. As we go forward, it is clear that spatial information science (and GIScience) continues to evolve as both a scientific field as well as in terms of the applications to which it is applied. We take this opportunity to remind all of our readers that JOSIS is run by your researchers for researchers. As a diamond open access journal, your article will be published under a Creative Commons licence, with no fees to either readers or authors. We rely on the community to provide constructive and detailed reviews, and are proud of the quality and diversity of articles we publish.
自我们于2020年出版10周年纪念刊[1,2]以来,JOSIS继续就我们编委会在其受邀论文中强调的许多主题发表了许多优秀的研究文章。其中包括关于众包[10]、地点[18,17,23,13,3]、空间语言[5,15,24,19]、GeoAI[14]、运动分析[26,11]、城市分析和寻路[16,21,7]、空间分析和不确定性方法[22,25,6,20]、环境数据和建模[8,12,9]以及定性空间推理[4]的文章。我们还高兴地注意到,这些文章代表了世界各地进行的研究,作者来自澳大利亚、孟加拉国、加拿大、克罗地亚、法国、德国、黎巴嫩、荷兰、新西兰、葡萄牙、南非、瑞士、英国和美国。除了五篇研究文章外,本期还包含两篇评论,回顾了过去和现在关于地理信息科学领域的主题问题。RenéWesterholt的第一篇研究了在跨学科背景下如何教授地理信息科学,以及这如何影响该领域的身份。Christophe Claramunt和Matthew Dube的第二篇文章从NCGIA最初的研究议程的角度审视了该领域的现状。随着我们的发展,很明显,空间信息科学(和地理信息科学)作为一个科学领域以及它所应用的应用都在继续发展。我们借此机会提醒所有读者,JOSIS是由您的研究人员为研究人员运营的。作为一本钻石开放获取期刊,您的文章将在知识共享许可证下发表,读者或作者均不收取任何费用。我们依靠社区提供建设性和详细的评论,并为我们发表的文章的质量和多样性感到自豪。
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引用次数: 0
A brief review of the evolution of GIScience since the NCGIA research agenda initiatives 简要回顾自NCGIA研究议程倡议以来gisscience的演变
IF 1.4 Q2 Social Sciences Pub Date : 2023-06-30 DOI: 10.5311/josis.2023.26.300
Christophe Claramunt, Matthew P. Dube
Geographical information science (GIScience) is progressively acknowledged as a scientific field based on a wide range of theories and methods that are constantly evolving. This motivates our attempt at a tentative observation of the research progress and challenges that have gone along with its gradual recognition as a domain of its own. The brief critical review presented in this paper develops an observation of such evolution. The peculiarity of our approach is that it is not based on a quantitative evaluation of the research outputs as identified by usual journal production metrics, but rather on a progressive identification of the research questions and their evolution, which the GIS academic community has been addressing over the past 30 years since the landmark NCGIA initiatives' research agendas have largely inspired and contributed to the development of geographical information science as a field.
地理信息科学(GIScience)逐渐被认为是一个建立在不断发展的广泛理论和方法基础上的科学领域。这促使我们尝试对研究进展和挑战进行试探性观察,这些进展和挑战伴随着它逐渐被视为一个独立的领域。本文所作的简要评述对这种演变进行了观察。我们方法的独特之处在于,它不是基于通常期刊生产指标所确定的研究成果的定量评估,而是基于对研究问题及其演变的逐步识别,这是GIS学术界在过去30年里一直在解决的问题,因为具有里程碑意义的NCGIA倡议的研究议程在很大程度上启发和促进了地理信息科学作为一个领域的发展。
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引用次数: 0
Teaching GIScience in the multidisciplinary nexus 跨学科关系下的地理信息学教学
IF 1.4 Q2 Social Sciences Pub Date : 2023-06-30 DOI: 10.5311/josis.2023.26.299
R. Westerholt
Many GIScientists are affiliated with institutions beyond what we would call core GIScience. This implies that we teach in degree programs that follow their own curricular logic, and presents us with challenges in terms of what to teach, how to possibly attract students to GIScience careers, and in terms of our own self-images and identities. After briefly taking stock of some of the bigger curricular initiatives from the past 30 years, and informed by a brief discussion of key arguments and findings regarding teaching GIScience 'elsewhere', this commentary aims to stimulate discussion on the multifaceted and multidisciplinary nexus in which many of us are embedded. The commentary includes short reflections on the implications of the multidisciplinary contexts mentioned for the creation of a GIScience identity among students enrolled in other degrees, recruitment of PhD students and faculty, and what all this possibly means for how we see ourselves as GIScientists.
许多GIScientists隶属于我们称之为核心GIScience之外的机构。这意味着我们在遵循他们自己课程逻辑的学位课程中进行教学,并在教学内容、如何吸引学生从事GIScience职业以及我们自己的自我形象和身份方面给我们带来了挑战。在简要总结了过去30年中的一些更大的课程举措,并简要讨论了关于在“其他地方”教授GIScience的关键论点和发现后,本评论旨在激发人们对我们许多人所处的多方面和多学科关系的讨论。评论包括对在其他学位的学生中创建地理信息科学身份、招聘博士生和教师所提及的多学科背景的影响的简短思考,以及所有这些可能对我们如何看待自己作为地理信息科学家意味着什么。
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引用次数: 0
A Geographical Perspective on Simpson's Paradox 辛普森悖论的地理学透视
IF 1.4 Q2 Social Sciences Pub Date : 2023-05-17 DOI: 10.5311/josis.2023.26.212
M. Sachdeva, A. Fotheringham
The concept of scale is inherent to, and consequential for, the modeling of geographical processes. However, scale also causes huge problems because the results of many types of spatial analysis appear to be dependent on the scale of the units for which data are reported (measurement scale). Consequently, when the same spatial models are calibrated at different scales of aggregations, the results are often vastly different (the well-known Modifiable Areal Unit Problem or MAUP). With the advent of local models and the fundamental difference in their scale of application compared to global models, this issue is further exacerbated in unexpected ways. For example, a global model and local model calibrated using data measured at the same aggregation scale can also result in different and sometimes contradictory inferences (the classic Simpson's Paradox). Here we provide a geographical perspective on why and how contrasting inferences might result from the calibration of a local and global model using the same data. Further, we examine the viability of such an occurrence using a synthetic experiment and two empirical examples. Finally, we discuss how such a perspective might inform the analyst’s conundrum: when the respective inferences run counter to one another, do we believe the local or global model results?
规模的概念是地理过程建模所固有的,也是地理过程建模的结果。然而,尺度也会带来巨大的问题,因为许多类型的空间分析的结果似乎取决于报告数据的单位的尺度(测量尺度)。因此,当在不同的聚集尺度上校准相同的空间模型时,结果往往大不相同(众所周知的可修改面积单元问题或MAUP)。随着局部模型的出现以及与全球模型相比其应用规模的根本差异,这一问题以意想不到的方式进一步加剧。例如,使用在相同聚合尺度上测量的数据校准的全局模型和局部模型也可能导致不同的、有时是矛盾的推断(经典的辛普森悖论)。在这里,我们提供了一个地理视角,说明使用相同数据校准局部和全局模型可能会产生对比推断的原因和方式。此外,我们使用一个综合实验和两个经验例子来检验这种情况的可行性。最后,我们讨论了这样一个视角如何为分析师的难题提供信息:当各自的推断相互矛盾时,我们相信局部或全局模型的结果吗?
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引用次数: 2
期刊
Journal of Spatial Information Science
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