Extracting Flood Maps from Social Media for Assimilation

Brangbour, Etienne; Bruneau, Pierrick; Marchand-Maillet, Stéphane

doi:10.1109/escience.2018.00045

Cited by 4 publications

(7 citation statements)

References 7 publications

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“…The session comprised 10 oral abstract presentations, one keynote talk, and six short poster pitches. Contributions were selected after a peer review on their scientific merit and innovative nature and published in the conference proceedings (Bari, 2018;Behrens et al, 2018;Bendoukha, 2018;Brangbour et al, 2018;Garcia-Marti et al, 2018;Haupt et al, 2018;Hut et al, 2018;Jansson et al, 2018;Pelupessy et al, 2018;Ramamurthy, 2018;Schultz et al, 2018;Stringer et al, 2018;van Haren et al, 2018;. The 16 session participants were either presenters or involved in the organization of the session and represented disparate science domains as well as computer and data sciences.…”

Section: Methodsmentioning

confidence: 99%

“…Outputs from NOAA weather and climate prediction models are freely available. The European Center for Medium-range Weather Forecasts (ECMWF) provides researchers with a free and easy-to-use version of the Integrated Forecasting System (IFS), which is one of the main global NWP systems (Carver, 2019). It allows IFS to be used by a much wider community, and the academic community contributes to improving the forecast model with new developments.…”

Section: Open Sciencementioning

confidence: 99%

“…Two studies include data that are not common in meteorological or climate research. Citizen data such as social media posts (Brangbour et al, 2018) and observations from amateur weather stations (van Haren et al, 2018) can lead to new perspectives on local conditions beyond data from traditional meteorological stations.…”

Section: Open Datamentioning

confidence: 99%

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Open weather and climate science in the digital era

et al. 2020

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Abstract. The need for open science has been recognized by the communities of meteorology and climate science. While these domains are mature in terms of applying digital technologies, the implementation of open science methodologies is less advanced. In a session on “Weather and Climate Science in the Digital Era” at the 14th IEEE International eScience Conference domain specialists and data and computer scientists discussed the road towards open weather and climate science. Roughly 80 % of the studies presented in the conference session showed the added value of open data and software. These studies included open datasets from disparate sources in their analyses or developed tools and approaches that were made openly available to the research community. Furthermore, shared software is a prerequisite for the studies which presented systems like a model coupling framework or digital collaboration platform. Although these studies showed that sharing code and data is important, the consensus among the participants was that this is not sufficient to achieve open weather and climate science and that there are important issues to address. At the level of technology, the application of the findable, accessible, interoperable, and reusable (FAIR) principles to many datasets used in weather and climate science remains a challenge. This may be due to scalability (in the case of high-resolution climate model data, for example), legal barriers such as those encountered in using weather forecast data, or issues with heterogeneity (for example, when trying to make use of citizen data). In addition, the complexity of current software platforms often limits collaboration between researchers and the optimal use of open science tools and methods. The main challenges we observed, however, were non-technical and impact the practice of science as a whole. There is a need for new roles and responsibilities in the scientific process. People working at the interface of science and digital technology – e.g., data stewards and research software engineers – should collaborate with domain researchers to ensure the optimal use of open science tools and methods. In order to remove legal boundaries on sharing data, non-academic parties such as meteorological institutes should be allowed to act as trusted agents. Besides the creation of these new roles, novel policies regarding open weather and climate science should be developed in an inclusive way in order to engage all stakeholders. Although there is an ongoing debate on open science in the community, the individual aspects are usually discussed in isolation. Our approach in this paper takes the discourse further by focusing on “open science in weather and climate research” as a whole. We consider all aspects of open science and discuss the challenges and opportunities of recent open science developments in data, software, and hardware. We have compiled these into a list of concrete recommendations that could bring us closer to open weather and climate science. We acknowledge that the development of open weather and climate science requires effort to change, but the benefits are large. We have observed these benefits directly in the studies presented in the conference and believe that it leads to much faster progress in understanding our complex world.

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Section: Methodsmentioning

confidence: 99%

Section: Open Sciencementioning

confidence: 99%

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Open weather and climate science in the digital era

et al. 2020

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“…Contributions were selected after a peer review on their scientific merit and innovative nature and published in the conference proceedings (Bari; Behrens et Map and openly available in-situ meteorological observations (Haupt et al, 2018;Garcia-Marti et al, 2018;Bari, 2018;Schultz et al, 2018, and references therein). Also, citizen data like social media posts increasingly leads to new findings (Brangbour et al, 2018) and observations from amateur weather stations can lead to new perspectives on local weather conditions beyond data from traditional meteorological stations (van Haren et al, 2018). All of these studies show that advances in scientific understanding are made with open data and often with combinations of data which are not common in meteorological or https://doi.org/10.5194/gc-2019-22 Preprint.…”

Section: Towards Open Weather and Climate Sciencementioning

confidence: 99%

“…al. ;Bendoukha;Brangbour et al;Garcia-Marti et al;Haupt et al;Hut et al;Jansson et al;Pelupessy et al;Ramamurthy;Schultz et al;Stringer et al; van Haren et al;van den Oord et al, 2018). In a synthesis session we observed several developments towards open research practices and discussed challenges and opportunities.This section presents the common findings and highlights of the conference session.3.1 OPEN DATAMany studies reported in the proceedings of the conference include open data from different sources in their analyses which clearly enrich their research.…”

mentioning

confidence: 95%

Weather and Climate Science in the Digital Era

Vos¹,

Hazeleger²,

Bari³

et al. 2019

Preprint

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Abstract. The need for open science has been recognized by the communities of meteorology and climate science. However, while these domains are mature in terms of applying digital technologies, these are lagging behind where the implementation of open science methodologies is concerned. In a session on <q>Weather and Climate Science in the Digital Era</q> at the 14th IEEE International eScience conference domain specialists and data and computer scientists discussed the road towards open weather and climate science. The studies presented in the conference session showed the added value of shared data, software and platforms through, for instance, combining data sets from disparate sources, increased accuracy and skill of simulations and forecasts at local scales, and improved consistency of data products. We observed that sharing data and code is important, but not sufficient to achieve open weather and climate science and that here are important issues to address. At the level of technology, the implementation of the FAIR principles to many datasets used in weather and climate science remains a challenge due to their origin, scalability, or legal barriers. Furthermore, the complexity of current software platforms limits collaboration between researchers and optimal use of open science tools and methods. The main challenges we observed, however, were non-technical and impact the system of science as a whole. There is a need for new roles and responsibilities at the interface of science and digital technology, e.g., data stewards and research software engineers. This requires the personnel portfolio of academic institutions to be more diverse, and in addition, a broader consideration of the impact of academic work, beyond publishing and teaching. Besides, new policies regarding open weather and climate science should be developed in an inclusive way to engage all stakeholders, including non-academic parties such as meteorological institutions. We acknowledge that open weather and climate science requires effort to change, but the benefits are large. As can already be observed from the studies presented in the conference it leads to much faster progress in understanding the world.

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CIME: Context-aware geolocation of emergency-related posts

2021

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Information extracted from social media has proven to be very useful in the domain of emergency management. An important task in emergency management is rapid crisis mapping, which aims to produce timely and reliable maps of affected areas. During an emergency, the volume of emergency-related posts is typically large, but only a small fraction is relevant and help rapid mapping effectively. Furthermore, posts are not useful for mapping purposes unless they are correctly geolocated and, on average, less than 2% of posts are natively georeferenced. This paper presents an algorithm, called CIME, that aims to identify and geolocate emergency-related posts that are relevant for mapping purposes. While native geocoordinates are most often missing, many posts contain geographical references in their metadata, such as texts or links that can be used by CIME to filter and geolocate information. In addition, social media creates a social network and each post can be enhanced with indirect information from the post’s network of relationships with other posts (for example, a retweet can be associated with other geographical references which are useful to geolocate the original tweet). To exploit all this information, CIME uses the concept of context, defined as the information characterizing a post both directly (the post’s metadata) and indirectly (the post’s network of relationships). The algorithm was evaluated on a recent major emergency event demonstrating better performance with respect to the state of the art in terms of total number of geolocated posts, geolocation accuracy and relevance for rapid mapping.

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Extracting Flood Maps from Social Media for Assimilation

Cited by 4 publications

References 7 publications

Open weather and climate science in the digital era

Open weather and climate science in the digital era

Weather and Climate Science in the Digital Era

CIME: Context-aware geolocation of emergency-related posts

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