Exploiting RDF Open Data Using NoSQL Graph Databases

Bouhali, Raouf; Laurent, Anne

doi:10.1007/978-3-319-23868-5_13

Cited by 10 publications

(5 citation statements)

References 3 publications

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“…However, it only covers the predefined data in the data model and does not allow the investigator to manipulate data relationships interactively. In a further approach, Aggarwal and Davis (2018) attempted to standardise and integrate evidence data by converting relational and RDF models into data graphs by leveraging the (Bouhali and Laurent (2015) method. The approach first transforms RDF models by exporting databases into a CSV file format to allow the user to select the schema and transform it into a Neo4j data graph.…”

Section: Analysis Of the Current State Of The Artmentioning

confidence: 99%

A Unified Forensics Analysis Approach to Digital Investigation

Alshumrani

Clarke

Ghita

2023

iccws

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Digital forensics is now essential in addressing cybercrime and cyber-enabled crime but potentially it can have a role in almost every other type of crime. Given technology's continuous development and prevalence, the widespread adoption of technologies among society and the subsequent digital footprints that exist, the analysis of these technologies can help support investigations. The abundance of interconnected technologies and telecommunication platforms has significantly changed the nature of digital evidence. Subsequently, the nature and characteristics of digital forensic cases involve an enormous volume of data heterogeneity, scattered across multiple evidence sources, technologies, applications, and services. It is indisputable that the outspread and connections between existing technologies have raised the need to integrate, harmonise, unify and correlate evidence across data sources in an automated fashion. Unfortunately, the current state of the art in digital forensics leads to siloed approaches focussed upon specific technologies or support of a particular part of digital investigation. Due to this shortcoming, the digital investigator examines each data source independently, trawls through interconnected data across various sources, and often has to conduct data correlation manually, thus restricting the digital investigator’s ability to answer high-level questions in a timely manner with a low cognitive load. Therefore, this research paper investigates the limitations of the current state of the art in the digital forensics discipline and categorises common investigation crimes with the necessary corresponding digital analyses to define the characteristics of the next-generation approach. Based on these observations, it discusses the future capabilities of the next-generation unified forensics analysis tool (U-FAT), with a workflow example that illustrates data unification, correlation and visualisation processes within the proposed method.

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Section: Analysis Of the Current State Of The Artmentioning

confidence: 99%

A Unified Forensics Analysis Approach to Digital Investigation

Alshumrani

Clarke

Ghita

2023

iccws

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“…It imports a simplified ontology version in the graph and enables queries with taxonomic reasoning. 5) Instance data population into Neo4j with [18] and by following RDF to LPG translation rules [19].…”

Section: ) Ontology Population Into Neo4j By Translating Owl/rdf Into Lpg Withmentioning

confidence: 99%

Towards a Semantic Data Harmonization Federated Infrastructure

Martínez-Costa

Abad-Navarro

2021

Studies in Health Technology and Informatics

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Data integration is an increasing need in medical informatics projects like the EU Precise4Q project, in which multidisciplinary semantically and syntactically heterogeneous data across several institutions needs to be integrated. Besides, data sharing agreements often allow a virtual data integration only, because data cannot leave the source repository. We propose a data harmonization infrastructure in which data is virtually integrated by sharing a semantically rich common data representation that allows their homogeneous querying. This common data model integrates content from well-known biomedical ontologies like SNOMED CT by using the BTL2 upper level ontology, and is imported into a graph database. We successfully integrated three datasets and made some test queries showing the feasibility of the approach.

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“…Different works have addressed the follow-up question on how the performance of NoSQL engines perform compared to RDF engines [13,12,14]. While most of them scale more gracefully than the RDF stores, the findings in these works also point out weaknesses of NoSQL engines in dealing with complex SPARQL queries involving several joins or containing complex filters on large volume of data [12].…”

Section: Introductionmentioning

confidence: 99%

Efficient querying of multidimensional RDF data with aggregates: Comparing NoSQL, RDF and relational data stores

Ravat

Song

Teste

et al. 2020

International Journal of Information Management

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This paper proposes an approach to tackle the problem of querying large volume of statistical RDF data. Our approach relies on pre-aggregation strategies to better manage the analysis of this kind of data. Specifically, we define a conceptual model to represent original RDF data with aggregates in a multidimensional structure. A set of translations rules for converting a well-known multidimensional RDF modelling vocabulary into the proposed conceptual model is then proposed. We implement the conceptual model in six different data stores: two RDF triple stores (Jena TDB and Virtuoso), one graph-oriented NoSQL database (Neo4j), one column-oriented data store (Cassandra), and two relational databases (MySQL and PostGreSQL). We compare the querying performance, with and without aggregates, in these data stores. Experimental results, on real-world datasets containing 81.92 million triplets, show that preaggregation allows for reducing query runtime in all data stores. Neo4j NoSQL and relational databases with aggregates outperform triple stores speeding up to 99% query runtime.

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Exploiting RDF Open Data Using NoSQL Graph Databases

Cited by 10 publications

References 3 publications

A Unified Forensics Analysis Approach to Digital Investigation

A Unified Forensics Analysis Approach to Digital Investigation

Towards a Semantic Data Harmonization Federated Infrastructure

Efficient querying of multidimensional RDF data with aggregates: Comparing NoSQL, RDF and relational data stores

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