Evidence map›Paper›PMID 29497460›Full record

ArticleJournal on data semantics2018

Ontology for Semantic Data Integration in the Domain of IT Benchmarking.

Matthias Pfaff, Stefan Neubig, Helmut Krcmar

Abstract read
In one paragraph

Article in Journal on data semantics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Matthias Pfaff1fortiss GmbH, An-Institut Technische Universität München (TUM), Munich, Germany.ORCID 0000-0002-6231-9020
Stefan Neubig2Technische Universität München (TUM), Munich, Germany.
Helmut Krcmar2Technische Universität München (TUM), Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A domain-specific ontology for IT benchmarking has been developed to bridge the gap between a systematic characterization of IT services and their data-based valuation. Since information is generally collected during a benchmark exercise using questionnaires on a broad range of topics, such as employee costs, software licensing costs, and quantities of hardware, it is commonly stored as natural language text; thus, this information is stored in an intrinsically unstructured form. Although these data form the basis for identifying potentials for IT cost reductions, neither a uniform description of any measured parameters nor the relationship between such parameters exists. Hence, this work proposes an ontology for the domain of IT benchmarking, available at https://w3id.org/bmontology. The design of this ontology is based on requirements mainly elicited from a domain analysis, which considers analyzing documents and interviews with representatives from Small- and Medium-Sized Enterprises and Information and Communications Technology companies over the last eight years. The development of the ontology and its main concepts is described in detail (i.e., the conceptualization of benchmarking events, questionnaires, IT services, indicators and their values) together with its alignment with the DOLCE-UltraLite foundational ontology.

Indexed as

Domain modelingInformation systemsIT benchmarkingKnowledge representationOntologySemantic data

Identifiers

PMID29497460
PMCPMC5816769

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.