BRAVO CELEDÓN, MARÍA LORETO

Preferred name
BRAVO CELEDÓN, MARÍA LORETO
Main Affiliation
Email
bravo@udd.cl
ORCID
0000-0001-7299-9317
Scopus Author ID
8392203200
Goggle Scholar

Settings

Now showing 1 - 10 of 12
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
      1Scopus© Citations 48
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    A dataset to assess mobility changes in Chile following local quarantines
    (2023)
    Luca Pappalardo
    ;
    Giuliano Cornacchia
    ;
    Navarro Aranguiz, Víctor
    ;
    BRAVO CELEDÓN, MARÍA LORETO  
    ;
    FERRES, LEONARDO ADRIÁN  
    Fighting the COVID-19 pandemic, most countries have implemented non-pharmaceutical interventions like wearing masks, physical distancing, lockdown, and travel restrictions. Because of their economic and logistical effects, tracking mobility changes during quarantines is crucial in assessing their efficacy and predicting the virus spread. Unlike many other heavily affected countries, Chile implemented quarantines at a more localized level, shutting down small administrative zones, rather than the whole country or large regions. Given the non-obvious effects of these localized quarantines, tracking mobility becomes even more critical in Chile. To assess the impact on human mobility of the localized quarantines, we analyze a mobile phone dataset made available by Telefónica Chile, which comprises 31 billion eXtended Detail Records and 5.4 million users covering the period February 26th to September 20th, 2020. From these records, we derive three epidemiologically relevant metrics describing the mobility within and between comunas. The datasets made available may be useful to understand the effect of localized quarantines in containing the COVID-19 pandemic.
      6Scopus© Citations 12
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Product,
      10
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
      1Scopus© Citations 8
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Adoption-Driven Data Science for Transportation Planning: Methodology, Case Study, and Lessons Learned
    (2020)
    Eduardo Graells-Garrido
    ;
    Vanessa Peña-Araya
    ;
    BRAVO CELEDÓN, MARÍA LORETO  
    The rising availability of digital traces provides a fertile ground for data-driven solutions to problems in cities. However, even though a massive data set analyzed with data science methods may provide a powerful and cost-effective solution to a problem, its adoption by relevant stakeholders is not guaranteed due to adoption barriers such as lack of interpretability and interoperability. In this context, this paper proposes a methodology toward bridging two disciplines, data science and transportation, to identify, understand, and solve transportation planning problems with data-driven solutions that are suitable for adoption by urban planners and policy makers. The methodology is defined by four steps where people from both disciplines go from algorithm and model definition to the development of a potentially adoptable solution with evaluated outputs. We describe how this methodology was applied to define a model to infer commuting trips with mode of transportation from mobile phone data, and we report the lessons learned during the process.
      3Scopus© Citations 7
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Product,
      1
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Consistency and trust in peer data exchange systems
    (2016)
    LEOPOLDO BERTOSSI
    ;
    BRAVO CELEDÓN, MARÍA LORETO  
    We propose and investigate a semantics for <jats:italic>peer data exchange systems</jats:italic> where different peers are related by data exchange constraints and trust relationships. These two elements plus the data at the peers' sites and their local integrity constraints are made compatible via a semantics that characterizes sets of <jats:italic>solution instances</jats:italic> for the peers. They are the intended – possibly virtual – instances for a peer that are obtained through a data repair semantics that we introduce and investigate. The semantically correct answers from a peer to a query, the so-called <jats:italic>peer consistent answers</jats:italic>, are defined as those answers that are invariant under all its different solution instances. We show that solution instances can be specified as the models of logic programs with a stable model semantics. The repair semantics is based on null values as used in SQL databases, and is also of independent interest for repairs of single databases with respect to integrity constraints.
      46Scopus© Citations 15
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Evaluation of home detection algorithms on mobile phone data using individual-level ground truth
    (2021)
    Luca Pappalardo
    ;
    FERRES, LEONARDO ADRIÁN  
    ;
    Manuel Sacasa
    ;
    Ciro Cattuto
    ;
    BRAVO CELEDÓN, MARÍA LORETO  
    Inferring mobile phone users’ home location, i.e., assigning a location in space to a user based on data generated by the mobile phone network, is a central task in leveraging mobile phone data to study social and urban phenomena. Despite its widespread use, home detection relies on assumptions that are difficult to check without ground truth, i.e., where the individual who owns the device resides. In this paper, we present a dataset that comprises the mobile phone activity of sixty-five participants for whom the geographical coordinates of their residence location are known. The mobile phone activity refers to Call Detail Records (CDRs), eXtended Detail Records (XDRs), and Control Plane Records (CPRs), which vary in their temporal granularity and differ in the data generation mechanism. We provide an unprecedented evaluation of the accuracy of home detection algorithms and quantify the amount of data needed for each stream to carry out successful home detection for each stream. Our work is useful for researchers and practitioners to minimize data requests and maximize the accuracy of the home antenna location.
    Scopus© Citations 35  3
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
      3Scopus© Citations 40
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Product,
    Dataset - Evaluation of home detection algorithms on mobile phone data using individual-level ground truth
    (GitHub, 2020)
    BRAVO CELEDÓN, MARÍA LORETO  
    ;
    FERRES, LEONARDO ADRIÁN  
    This is the implementation of the 5 algorithms described in Vanhoof, M., Reis, F., Ploetz, T., & Smoreda, Z. (2018). Assessing the quality of home detection from mobile phone data for official statistics. In Journal of Official Statistics (Vol. 34, pp. 935–960). https://doi.org/10.2478/jos-2018-0046 that we used in our paper.
      3