Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards a context-dependent numerical data quality evaluation framework   This paper focuses on numeric data, with emphasis on distinct characteristics
like varying significance, unstructured format, mass volume and real-time
processing. We propose a novel, context-dependent valuation framework
specifically devised to assess quality in numeric datasets. Our framework uses
eight relevant data quality dimensions, and provide a simple metric to evaluate
dataset quality along each dimension. We argue that the proposed set of
dimensions and corresponding metrics adequately captures the unique quality
antipatterns that are typically associated with numerical data. The
introduction of our framework is part of a wider research effort that aims at
developing an articulated numerical data quality improvement approach for Oil
and Gas exploration and production workflows that is based on artificial
intelligence techniques.

10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph