Javier Letelier

dblp:320/0784 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data integration and cleaning · 77% Query processing and optimization · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data integration and cleaning
heterogeneous data source integration
0.212016
Mixed-instance querying: a lightweight integration architecture for data journalism · Proc. VLDB Endow. 2016

Methods — techniques the papers use, named apart from their topics

data linking · 0.2
YearPublicationVenuePosition
2016 Mixed-instance querying: a lightweight integration architecture for data journalism
abstract
As the world's affairs get increasingly more digital, timely production and consumption of news require to efficiently and quickly exploit heterogeneous data sources. Discussions with journalists revealed that content management tools currently at their disposal fall very short of expectations. We demonstrate T atooine , a lightweight data integration prototype, which allows to quickly set up integration queries across (very) heterogeneous data sources, capitalizing on the many data links (joins) available in this application domain. Our demonstration is based on scenarios we study in collaboration with Le Monde, France's major newspaper.
Raphaël Bonaque, Tien Duc Cao, Bogdan Cautis, François Goasdoué, Javier Letelier, Ioana Manolescu, Oscar Mendoza, Swen Ribeiro, Xavier Tannier, Michaël Thomazo
Proc. VLDB Endow.5