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CosmoHub: Interactive exploration and distribution of astronomical data on Hadoop

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Pau Tallada, Jorge Carretero, Jordi Casals, Carles Acosta-Silva, Santiago Serrano, Marc Caubet, Francisco J. Castander, Eduardo César
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Martín Crocce, Manuel Delfino, Martin Eriksen, Pablo Fosalba, Enrique Gaztañaga, Gonzalo Merino, Christian Neissner, Nadia Tonello

Instrumentation and Methods for Astrophysics · Submitted 4 Mar 2020

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets.

how it is stated · asserted 1.00 read the record →

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arXiv ID2003.03217 (version 2)
Pith IDEUMI7AQU, Pith's permanent record of this paper and its review
CitationCarles Acosta-Silva, Christian Neissner, Eduardo C\'esar, Enrique Gazta\~naga, Francisco J. Castander, Gonzalo Merino, Jordi Casals, Jorge Carretero, Manuel Delfino, Marc Caubet, Mart\'in Crocce, Martin Eriksen, Nadia Tonello, Pablo Fosalba, Pau Tallada, Santiago Serrano. "CosmoHub: Interactive exploration and distribution of astronomical data on Hadoop." arXiv:2003.03217 (2020). https://pith.science/paper/EUMI7AQU
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 7,169 input tokens.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.32 · human participants 0.09 · controlled comparison 0.03 · randomized assignment 0.01 · states quantitative result 0.98 · compares with prior results 0.17 · mentions code or data availability 0.62.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmology seeks to unveil the nature of both dark matter and dark energy mapping the large-scale structure of the Universe, through the analysis of massive amounts of astronomical data, progressively increasing during the last (and future) decades with the digitization and automation of the experimental techniques. CosmoHub, hosted and developed at the Port d'Informaci\'o Cient\'ifica (PIC), provides support to a worldwide community of scientists, without requiring the end user to know any Structured Query Language (SQL). It is serving data of several large international collaborations such as the Euclid space mission, the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS) and the Marenostrum Institut de Ci\`encies de l'Espai (MICE) numerical simulations. While originally developed as a PostgreSQL relational database web frontend, this work describes the current version of CosmoHub, built on top of Apache Hive, which facilitates scalable reading, writing and managing huge datasets. As CosmoHub's datasets are seldomly modified, Hive it is a better fit. Over 60 TiB of catalogued information and $50 \times 10^9$ astronomical objects can be interactively explored using an integrated visualization tool which includes 1D histogram and 2D heatmap plots. In our current implementation, online exploration of datasets of $10^9$ objects can be done in a timescale of tens of seconds. Users can also download customized subsets of data in standard formats generated in few minutes.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. contribution 1.00 0.91 0.27 asserted 1.00
s1 Recent Cosmology seeks to unveil the nature of both dark matter and dark energy mapping the large-scale structure of the Universe, through the analysis of massive amounts of astronomical data, progressively increasing during the last (and future) decades with the digitization and automation of the experimental techniques. background 1.00 0.05 0.04 asserted 0.98
s2 CosmoHub, hosted and developed at the Port d'Informaci\'o Cient\'ifica (PIC), provides support to a worldwide community of scientists, without requiring the end user to know any Structured Query Language (SQL). contribution 0.90 0.58 0.07 asserted 1.00
s3 It is serving data of several large international collaborations such as the Euclid space mission, the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS) and the Marenostrum Institut de Ci\`encies de l'Espai (MICE) numerical simulations. contribution 0.78 0.54 0.05 asserted 1.00
s4 While originally developed as a PostgreSQL relational database web frontend, this work describes the current version of CosmoHub, built on top of Apache Hive, which facilitates scalable reading, writing and managing huge datasets. method 0.78 0.75 0.10 asserted 1.00
s5 As CosmoHub's datasets are seldomly modified, Hive it is a better fit. method 0.56 0.64 0.06 asserted 0.99
s6 Over 60 TiB of catalogued information and $50 \times 10^9$ astronomical objects can be interactively explored using an integrated visualization tool which includes 1D histogram and 2D heatmap plots. result 0.52 0.81 0.15 asserted 1.00
s7 In our current implementation, online exploration of datasets of $10^9$ objects can be done in a timescale of tens of seconds. result 0.98 0.93 0.09 asserted 0.84
s8 Users can also download customized subsets of data in standard formats generated in few minutes. contribution 0.60 0.77 0.08 asserted 0.98

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from analysis of existing data 0.54.

What was examined, and what was not

sources read
  • arXiv listing abstract v2
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We present CosmoHub (https://cosmohub.pic.es), a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmology seeks to unveil the nature of both dark matter and dark energy mapping the large-scale structure of the Universe, through the analysis of massive amounts of astronomical data, progressively increasing during the last (and future) decades with the digitization and automation of the experimental techniques. CosmoHub, hosted and developed at the Port d'Informaci\'o Cient\'ifica (PIC), provides support to a worldwide community of scientists, without requiring the end user to know any Structured Query Language (SQL). It is serving data of several large international collaborations such as the Euclid space mission, the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS) and the Marenostrum Institut de Ci\`encies de l'Espai (MICE) numerical simulations. While originally developed as a PostgreSQL relational database web frontend, this work describes the current version of CosmoHub, built on top of Apache Hive, which facilitates scalable reading, writing and managing huge datasets. As CosmoHub's datasets are seldomly modified, Hive it is a better fit. Over 60 TiB of catalogued information and $50 \times 10^9$ astronomical objects can be interactively explored using an integrated visualization tool which includes 1D histogram and 2D heatmap plots. In our current implementation, online exploration of datasets of $10^9$ objects can be done in a timescale of tens of seconds. Users can also download customized subsets of data in standard formats generated in few minutes.

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Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

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