SADI Semantic Web Services - ‚cause you can't always GET what you want! is a research paper published in 2009 IEEE Asia-Pacific Services Computing Conference (APSCC) (2009). On theSindex it has a DataRank of 3.3. It has been cited 47 times, with 37 citing works in its 1-hop citation network.
SADI-semantic automated discovery and integration- is a set of standards-compliant semantic Web service design patterns that exploit the relatively straightforward interfaces exposed by most bioinformatics services to simplify and partially automate service design and deployment. The SADI design explicitly exposes an important service feature -the semantic relationship between input and output data. SADI services consume and produce instances of OWL classes, where the service's function is to add properties onto the input class until it fulfills the class-membership requirements of the output class. Indexing services based on the properties they add enables discovery of Services that generate the biological features of interest relative to a piece of in-hand data. We show that this design pattern can be used to create a client application with strikingly rich semantic behaviors, such as automated discovery of distributed data resources and the automated orchestration of chains of Web services into complex workflows.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.581
From this paper's citation signal
Citation Network Contribution
2.8
From 33 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 17% comes from its base citations and 83% from the citation network (33 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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