Reliable Granular References to Changing Linked Data

Abstract

Abstract. Nanopublications are a concept to represent Linked Data in a granular and provenance-aware manner, which has been successfully applied to a number of scientific datasets. We demonstrated in previous work how we can establish reliable and verifiable identifiers for nanopublications and sets thereof. Further adoption of these techniques, however, was probably hindered by the fact that nanopublications can lead to an explosion in the number of triples due to auxiliary information about the structure of each nanopublication and repetitive provenance and metadata. We demonstrate here that this significant overhead disappears once we take the version history of nanopublication datasets into account, calculate incremental updates, and allow users to deal with the specific subsets they need. We show that the total size and overhead of evolving scientific datasets is reduced, and typical subsets that researchers use for their analyses can be referenced and retrieved efficiently with optimized precision, persistence, and reliability.

Data Quality Issues in Current Nanopublications

“…We first aim to replicate Figure 1 from [5] which presents a stacked bar chart of the count of triples in each part of a nanopublication broken down by dataset. The raw count of the number of nanopublications by dataset is given in row 1 of Table 1 shows us that DisGeNET is published as significantly more nanopublications than the other datasets, but this is expected due to the underlying size of each of the datasets.…”

“…We will now investigate the breakdown of triples within the different parts of the nanopublication as was done by Kuhn et al Figure 4 represents the average number of triples in each part of the nanopublication for each dataset, i.e. is equivalent to the stacked bar chart from [5]. By unstacking the bar chart, it is easier to compare the different components of the nanopublications across the datasets.…”

“…In this paper we were motivated to replicate some of the analysis presented in [3] and [5]. This involves reusing a subset of the data on the nanopublication network.…”

“…We will now briefly describe the data used with a summary given in Table 1. Full details of the datasets and how they are generated can be found in [3], [5]. We will provide a fuller discussion of Table 1 [8], OpenBEL large and small corpus 5 version 20131211 [10], and LIDDI 6 version 1.02 [11].…”

“…However, the benefit is that each claim is published with provenance and publication information pertinent to the claim. Kuhn et al [5] introduced Figure 1. Example Nanopublication derived from [1].…”