@article{LopezVazquez2022a,
title = {Building a Gold Standard Dataset to Identify Articles About Geographic Information Science},
author = {Carlos López-Vázquez and María Ester Gonzalez-Campos and Miguel A. Bernabé-Poveda and Daniela Moctezuma and Esther Hochsztain and María A. Barrera and Carlos Granell-Canut and María F. León-Pazmiño and Pablo López-Ramírez and Villie Morocho-Zurita adn Javier Moya-Honduvilla and María T. Manrique-Sancho and Marcela E. Montiveros and Rocío Narváez-Benalcázar and José de Jesús Pérez-Alcázar and Yuri Resnichenko and Diego Seco. },
doi = {https://doi.org/10.1109/ACCESS.2022.3150869},
issn = {2169-3536},
year = {2022},
date = {2022-02-10},
journal = {IEEE Access},
volume = {10},
pages = {19926-19936},
abstract = {To know the overall regional or international scientific production is of vital importance to many areas of knowledge. Nevertheless, in interdisciplinary areas such as Geographic Information Science (GISc) it is not enough to just count papers published in specific journals. Most of them, as is the case of the International Journal of Remote Sensing (IJRS), welcome GISc papers but are not exclusive to that area so the production assignable to authors in the region must consider not only affiliation but also whether or not each paper falls into the theme of GISc. IJRS publishes far more papers than any other GISc journal, so it is important to assess quantitatively how many of them are of GISc. In this work, a representative sample of IJRS articles published over a period of almost 30 years was analyzed using a specific GISc definition. With these data, a manual classification methodology through a set of experts was carried out, and a dataset was built, analyzed, and statistically tested. As a result we estimate that between 47 and 76% of the IJRS articles can be considered from GISc, with a confidence level of 95%. Aside from the primary goal, this set could be used as a gold standard for future classification tasks. It constitutes the first GISc dataset of this kind, that may be used to train artificial intelligence systems capable of performing the same classification automatically and in a massive way. A similar procedure could be applied to other interdisciplinary fields of knowledge as well.},
keywords = {Geographic Information Systems (GIS), GIScience},
pubstate = {published},
tppubtype = {article}
}

@article{Blanford2022a,
title = {Lockdown lessons: an international conversation on resilient GI science teaching},
author = {Justine I. Blanford and Forrest Bowlick and Anthony Gidudu and Michael Gould and Amy L. Griffin and Bandana Kar and Karen Kemp and Mairéad de Róiste and Stefano deSabbata and Diana Sinton and Josef Strobl and Nicholas Tate and Fred Toppen and David Unwin },
doi = {https://doi.org/10.1080/03098265.2021.1986687},
issn = {0309-8265},
year = {2022},
date = {2022-01-15},
journal = {Journal of Geography in Higher Education},
volume = {46},
number = {1},
pages = {7-19},
abstract = {We report the findings from two global panel “conversations” that, stimulated by the exceptional coronavirus pandemic of 2020/21, explored the concept of resilience in geographic science teaching and learning. Characteristics of resilient teaching, both in general and with reference to GISc, are listed and shown to be essentially what might in the past have been called good teaching. Similarly, barriers to resilient teaching are explored and strategies for overcoming them listed. Perhaps the most important conclusion is a widespread desire not to “bounce back” to pre-COVID ways, but to use the opportunity to “bounce forward” towards better teaching and learning practices.},
keywords = {GI teaching, GIScience},
pubstate = {published},
tppubtype = {article}
}

@article{Granell2018,
title = {Reproducible research and GIScience: an evaluation using AGILE conference papers},
author = {Daniel Nüst and Carlos Granell-Canut and Barbara Hofer and Markus Konkol and Frank O Ostermann and Rusne Sileryte and Valentina Cerutti},
url = {https://doi.org/10.7717/peerj.5072},
doi = {10.7717/peerj.5072},
issn = {2167-8359},
year = {2018},
date = {2018-01-01},
journal = {PeerJ},
volume = {6},
pages = {e5072},
keywords = {AGILE, Data science, GIScience, Open access, Open science, Reproducible research},
pubstate = {published},
tppubtype = {article}
}

@article{Trilles2017,
title = {Deployment of an open sensorized platform in a smart city context },
author = {Sergio Trilles-Oliver and Andrea Calia and Óscar Belmonte and Joaquín Torres-Sospedra and Raul Montoliu and Joaquín Huerta-Guijarro and
},
doi = {http://dx.doi.org/10.1016/j.future.2016.11.005},
issn = {0167-739X},
year = {2017},
date = {2017-02-28},
journal = {Future Generation Computer Systems},
volume = {76},
pages = {221-233},
abstract = {The race to achieve smart cities is producing a continuous effort to adapt new developments and knowledge, for administrations and citizens. Information and Communications Technology are called on to be one of the key players to get these cities to use smart devices and sensors (Internet of Things) to know at every moment what is happening within the city, in order to make decisions that will improve the management of resources. The proliferation of these “smart things” is producing significant deployment of networks in the city context. Most of these devices are proprietary solutions, which do not offer free access to the data they provide. Therefore, this prevents the interoperability and compatibility of these solutions in the current smart city developments.
This paper presents how to embed an open sensorized platform for both hardware and software in the context of a smart city, more specifically in a university campus. For this integration, GIScience comes into play, where it offers different open standards that allow full control over “smart things” as an agile and interoperable way to achieve this. To test our system, we have deployed a network of different sensorized platforms inside the university campus, in order to monitor environmental phenomena.},
keywords = {environmental monitoring, GEOEvent, GIScience, Internet of things, Open-hardware, senviro, Smart Cities},
pubstate = {published},
tppubtype = {article}
}

@article{Degbelo2016,
title = {Opening up Smart Cities: Citizen-Centric Challenges and Opportunities from GIScience},
author = {Auriol Degbelo and Carlos Granell-Canut and Sergio Trilles-Oliver and Devanjan Bhattacharya and Sven Casteleyn and Christian Kray},
url = {http://hdl.handle.net/10234/159507},
doi = {10.3390/ijgi5020016},
issn = {2220-9964},
year = {2016},
date = {2016-01-01},
journal = {ISPRS International Journal of Geo-Information},
volume = {5},
number = {2},
pages = {16},
abstract = {The holy grail of smart cities is an integrated, sustainable approach to improve the efficiency of the city's operations and the quality of life of citizens. At the heart of this vision is the citizen, who is the primary beneficiary of smart city initiatives, either directly or indirectly. Despite the recent surge of research and smart cities initiatives in practice, there are still a number of challenges to overcome in realizing this vision. This position paper points out six citizen-related challenges: the engagement of citizens, the improvement of citizens' data literacy, the pairing of quantitative and qualitative data, the need for open standards, the development of personal services, and the development of persuasive interfaces. The article furthermore advocates the use of methods and techniques from GIScience to tackle these challenges, and presents the concept of an Open City Toolkit as a way of transferring insights and solutions from GIScience to smart cities.},
note = {IF: 0.371 - 49/49 (Q4) Geography, physical
0.371 - 29/29 (Q4) Remote Sensing
},
keywords = {citizen participation, GEO-C, GIScience, open data, RyC-Casteleyn, RyC-Granell, Smart Cities},
pubstate = {published},
tppubtype = {article}
}