Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1004.4296

Analysis of Graphs for Digital Preservation Suitability

Charles L. Cartledge·Michael L. Nelson
View original source ↗Read source document ↗Export metadata ↓

Abstract

We investigate the use of autonomically created small-world graphs as a framework for the long term storage of digital objects on the Web in a potentially hostile environment. We attack the classic Erdos - Renyi random, Barab'asi and Albert power law, Watts - Strogatz small world and our Unsupervised Small-World (USW) graphs using different attacker strategies and report their respective robustness. Using different attacker profiles, we construct a game where the attacker is allowed to use a strategy of his choice to remove a percentage of each graph's elements. The graph is then allowed to repair some portion of its self. We report on the number of alternating attack and repair turns until either the graph is disconnected, or the game exceeds the number of permitted turns. Based on our analysis, an attack strategy that focuses on removing the vertices with the highest betweenness value is most advantageous to the attacker. Power law graphs can become disconnected with the removal of a single edge; random graphs with the removal of as few as 1% of their vertices, small-world graphs with the removal of 14% vertices, and USW with the removal of 17% vertices. Watts - Strogatz small-world graphs are more robust and resilient than random or power law graphs. USW graphs are more robust and resilient than small world graphs. A graph of USW connected web objects (WOs) filled with data could outlive the individuals and institutions that created the data in an environment where WOs are lost due to random failures or directed attacks.

Explore related subjects

cs.DL

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Charles L. Cartledge, Michael L. Nelson. 2010-04-24. Analysis of Graphs for Digital Preservation Suitability. https://arxiv.org/abs/1004.4296

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

The illusion of neutrality in metric-based research evaluation

Venue prestige and citation counts are two widely used, albeit imperfect, signals of research quality. When the two signals conflict, evaluators must decide how much weight to assign each. Yet, it remains unknown how researchers across disciplines trade off these two signals when evaluating research outcome. To fill this gap, we surveyed 869 researchers using paired choices between hypothetical departmental hiring rules that assigned different weights to venue prestige and citation counts, asking which would produce better science. Among 795 respondents whose choices were largely internally consistent, choices placed nearly equal aggregate weight on the two signals. This apparent balance concealed substantial individual heterogeneity: nearly two in five respondents occupied the most venue-heavy or citation-heavy intervals. Moreover, respondents on average chose more citation-heavy rules than they believed their departments used in hiring. By revealing the subjective judgments that arise when research indicators conflict, our findings reinforce calls for greater caution when quantitative indicators are used to evaluate research.

cs.DL↗
arXiv2026

Reading the Data Back: Enriching Variable-Level Metadata for Model-Data Consistency Checks

Purpose: Research data repositories often lack variable-level metadata. Model-choice screening, checking whether a reported model suits the values of its outcome variable, also requires summaries of those values and links to the analyses that use them. We ask how repositories can represent and acquire them as metadata with evidence and review histories. Methods: We propose a metadata application profile compatible with the Data Documentation Initiative Cross-Domain Integration (DDI-CDI) model, linking versioned variables and empirical profiles to reported analyses, estimators, and analysis roles. Extraction provenance and review decisions are recorded separately. We evaluate streaming data profiling, deterministic extraction from Stata and R code, and language-model extraction of analysis records from papers. Results: A worked export of one replication package illustrates the profile: it passes shape and interchange checks and answers four queries, one of which returns the analyses that raise no alert. Screening 4,868 replication datasets from six political-science journals links outcomes to profiled columns in 1,440 deposits and flags 965, including 14 of the 21 deposits with a hand-verified linear model on a count, proportion, binary, or ordinal outcome. AI-assisted adjudication yields 55% precision on a near-balanced sample of 119 count and proportion candidates; screening rules were developed on the same corpus. Conclusion: The profile makes analysis-variable relationships queryable while preserving evidence and review history; screening yields review candidates with context. Code, metadata, and measurements are released.

cs.DL↗
arXiv2026

From Code Archival to Knowledge Graph: Bridging Software Heritage, COAR Notify and Wikidata

Software is a first-class scientific object, yet validated links between source code and the scholarly record remain largely absent from the Linked Open Data (LOD) cloud, isolating archived artefacts from semantic discovery. This paper presents an end-to-end reconciliation pipeline that harvests, validates, and models publication-to-repository pairs from sources where the link between a paper and its source code is explicit and editorially verified: the software-centric journals JOSS, SoftwareX, and IPOL, together with the reproducibility reports of the SIGMOD Availability and Reproducibility Initiative (ARI). This yields a curated corpus of 4,397 $\langle$DOI, repository-URL$\rangle$ pairs. We design two distinct application profiles grounded in Wikidata classes (one for scholarly articles, one for software instances) aligned with the schema.org and CodeMeta vocabularies. This architectural separation enables rule-based reconciliation at two granularities: lightweight, inline publication references or standalone, first-class Wikidata software nodes equipped with SWHIDs, Software Heritage's content-addressed identifiers. A read-only lookup against Wikidata shows that only 82 of the harvested repositories were already modelled there; human-reviewed batches have since created 4{,}182 new software items cross-linked to their articles. We further show that payloads of the emerging COAR Notify protocol, an external effort we do not develop, map natively onto our input format, so the same backend could later serve a live enrichment stream. Our core contribution is a pair of application profiles that turn Wikidata into a connector between the scholarly record and archived source code; we openly release all code, application profiles, and harvested datasets.

cs.DL↗