BioMOBY: An open source biological web services proposal
BioMOBY: An open source biological web services proposal is a research paper published in Briefings in Bioinformatics (2002). On theSindex it has a DataRank of 0.883. It has been cited 360 times.
Abstract
BioMOBY is an Open Source research project which aims to generate an architecture for the discovery and distribution of biological data through web services; data and services are decentralised, but the availability of these resources, and the instructions for interacting with them, are registered in a central location called MOBY Central. BioMOBY adds to the web services paradigm, as exemplified by Universal Data Discovery and Integration (UDDI), by having an object-driven registry query system with object and service ontologies. This allows users to traverse expansive and disparate data sets where each possible next step is presented based on the data object currently in-hand. Moreover, a path from the current data object to a desired final data object could be automatically discovered using the registry. Native BioMOBY objects are lightweight XML, and make up both the query and the response of a simple object access protocol (SOAP) transaction.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
DataRank Breakdown
Base Score Contribution
0.883
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
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.