---
title: 'OTTER: Open Multiwavelength Transient Repository'
url: https://www.emergentmind.com/topics/open-multiwavelength-transient-event-repository-otter
type: topic
---

# OTTER: Open Multiwavelength Transient Repository

The Open mulTiwavelength Transient Event Repository (OTTER) is a publicly available catalog of published transient event metadata and photometry designed to make multiwavelength analyses of astrophysical transients more efficient and effective. Its data schema is optimized for the storage of multiwavelength photometric datasets spanning the entire electromagnetic spectrum, and the infrastructure includes open source software, an application programming interface (API), and a web application for viewing, accessing, and analyzing the dataset. In its initial release, OTTER presents the largest ever photometric archive of tidal disruption events (TDEs), including $\gtrsim 80{,}000$ observations of 232 TDEs spanning from radio to X-ray wavelengths [2509.05405].

## 1. Scope and repository concept

OTTER is defined as an infrastructure for archiving published transient event metadata and photometry in a form tailored to multiwavelength work. The repository is explicitly motivated by the centrality of multiwavelength analyses to the physics of astrophysical transients and by the need to assemble heterogeneous measurements into a unified framework [2509.05405].

A distinguishing property of the repository is that its schema is optimized for photometric datasets across the full electromagnetic spectrum rather than for a single bandpass regime or a narrow class of events. The initial scientific focus is the TDE population, but the infrastructure was built with the goal of archiving additional transient data, including supernovae, gamma-ray bursts, fast blue optical transients, and fast radio bursts, in the future [2509.05405].

A common misconception would be to treat OTTER as only a static TDE list. The released system is broader than that: the TDE catalog is the initial release and the first large-scale scientific demonstration, whereas the underlying repository, software, and upload workflow are intended to support continuing maintenance and future ingestion of newly published data [2509.05405].

## 2. Data model and database architecture

OTTER stores each transient in a single JSON document. The top-level keys are `name`, `coordinate`, `distance`, `date_reference`, `classification`, `host`, and `photometry`. This document-centric model places object metadata and measurement arrays in the same record, allowing a transient to be represented as a single structured entity rather than as a set of disconnected tables [2509.05405].

Within the `photometry` array, entries can encode optical and UV magnitudes, radio measurements, and other wavelength-domain observations through fields such as `mjd`, `uaname`, `wavelength`, `freq`, `value`, `valueerr`, and `flux`, together with associated units and citation keys. The schema also stores correction states in boolean flags: `corr_host` for host-subtraction, `corr_k` for k-correction, `corr_ext` for Galactic extinction, and `corr_mb` for Milky Way broadband applying [2509.05405].

The representation explicitly links filter identity to effective wavelength or frequency and includes the AB-system conversion
\[
F_\nu = 10^{-0.4\,(m_{\rm AB} + 48.6)}\ \mathrm{erg\,s^{-1}\,cm^{-2}\,Hz^{-1}},
\]
with $F_\nu$ defined as the flux density per unit frequency. This makes the schema suitable for analyses that require conversion between magnitude and flux representations or aggregation of observations from different facilities into a common spectral-energy-distribution view [2509.05405].

The backend is an ArangoDB document store. Each JSON document is directly ingested as one ArangoDB document, and documents are automatically sharded across the cluster. The `photometry` array is stored as an embedded sub-document, enabling AQL queries that iterate over a transient’s measurements while filtering by units or wavelength-domain attributes [2509.05405]. This suggests that OTTER prioritizes co-location of event metadata and time-domain measurements over a fully normalized relational design.

OTTER also defines classification semantics at two levels. Each classification entry carries an integer confidence flag $C \in \{0,\dots,4\}$, where $C=0$ denotes an unverified or intermediate candidate, $C=1$ a photometric-only classification including ML algorithms, $C=2$ a spectroscopic classification in a non-refereed venue, $C=3$ a bronze-quality spectrum in a refereed publication, and $C=4$ a silver/gold spectroscopic quality in a refereed publication. In addition, automatically derived meta-flags per transient include `discovery_method` in `{"optical","xray","radio"}`, `spec_classed` in $\{0,\dots,3\}$, and `unambiguous` in `{true,false}`. These flags allow refined sample cuts, such as selecting only unambiguous, gold-spectro TDEs [2509.05405].

## 3. Programmatic and web access

The API is exposed at `https://otter.idies.jhu.edu/api/v1`. Major endpoints include `GET /transients`, which supports parameters such as `name`, `ra`, `dec`, `zmin`, `zmax`, `classification`, and `has_photometry`; `GET /transients/{name}` for the full JSON document of a transient; `GET /transients/{name}/photometry` with query parameters including `filter`, `wave_min`, `wave_max`, `tmin`, `tmax`, and `units=("mag","flux")`; `POST /contributions/upload`; and `GET /contributions/{upload_id}` for vetting status and diffs. `GET /transients/{name}/spectrum` is listed as coming soon [2509.05405].

Authentication uses an API key supplied via the HTTP header `X-OTTER-APIKEY` after free registration. The default rate limit is `500 requests/day, 5 req/min per key`. Pagination is handled through `page` and `per_page` in the query string, with `total_pages` and `total_results` returned in response metadata [2509.05405]. These details indicate that OTTER is designed for direct integration into analysis workflows rather than only manual browsing.

The web application provides a complementary interface. Its home page includes an interactive skymap of all OTTER transients using Leaflet and Aladin Lite. The search page offers a GUI form, a table of results, and export as zip(JSONs). Transient detail pages expose a metadata panel with default values and citation counts, interactive photometry plots, and a citations-and-contribution view. The light-curve display uses log–log axes and band-based color coding, while spectral-energy-distribution snapshots allow selection by $\Delta t$, $t_{\min}$, $t_{\max}$, and either $\nu$ or $\lambda$ [2509.05405].

The contribution interface supports both single-object and bulk JSON upload and performs live validation with Pydantic models. A private vetting dashboard includes a diff viewer together with approve/reject controls [2509.05405]. A plausible implication is that OTTER attempts to couple public accessibility with controlled curation rather than permitting unreviewed direct insertion into the production archive.

## 4. Tidal disruption event catalog

The initial OTTER release is centered on TDEs and is described as the largest ever photometric archive of that class, with $\gtrsim 80{,}000$ observations of 232 TDEs extending from radio to X-ray wavelengths [2509.05405]. This scale is central to the repository’s scientific role because TDE studies often require synchronized treatment of optical, UV, X-ray, infrared, and radio measurements, yet those measurements are typically distributed across separate publications and archives.

The catalog’s internal quality-control structure is encoded through its confidence and meta-flag system. Because classifications can be filtered by verification level, spectroscopy quality, discovery method, and ambiguity status, the same archive can support both permissive population studies and more conservative subsamples [2509.05405]. This directly addresses a recurrent issue in transient-population work: sample definition can dominate downstream inference.

OTTER’s photometric representation is also tuned for heterogeneous TDE phenomenology. The example JSON structure includes both optical AB magnitudes and radio flux-density measurements, each with explicit units, uncertainties, correction flags, and literature provenance. The repository therefore stores the observational context needed for multi-regime modeling rather than only an abstracted light-curve summary [2509.05405].

Another potential misconception is that a large TDE archive automatically implies uniform selection or uniform reduction. OTTER is instead described as a catalog of published transient event metadata and photometry, with citation-linked entries and correction flags indicating whether host subtraction, k-correction, or extinction corrections have been applied [2509.05405]. This suggests that the repository standardizes representation and access while preserving provenance and some aspects of upstream heterogeneity.

## 5. Demonstrated scientific analyses

The repository paper demonstrates four example analyses of the TDE population. The first measures the delay between optical/UV and X-ray peaks in optically discovered TDEs with at least two detections in both bands. The analysis defines $\Delta t_{\rm delay} = t_{\rm peak,X} - t_{\rm peak,UV}$, extracts peak times and uncertainties from adjacent bins, and uses a Kaplan–Meier estimator for the censored $\Delta t_{\rm delay}$ distribution. The reported finding is a median $\Delta t_{\rm delay} \lesssim 300$ days, implying constraints on circularization time of approximately $100$–$200$ days, with censored-data treatment described as essential. The survival function is written as
\[
\hat S(t) = \prod_{t_i\le t}\Bigl(1-\frac{d_i}{n_i}\Bigr),
\]
where $d_i$ is the number of events at $t_i$ and $n_i$ the number at risk [2509.05405].

The second analysis compares host infrared colors and radio environments for extreme coronal line emitters (ECLEs) and non-ECLE TDEs. Using WISE queries via the OTTER API and astroquery, it computes peak $W1-W2$ and peak radio luminosity and applies a two-sample KS test. The reported result is that ECLEs are significantly redder, with $p \approx 10^{-6}$, interpreted as evidence for a dust-rich circumnuclear medium; the paper further states that this suggests dense gas fosters coronal lines and reprocessing [2509.05405].

The third analysis uses MOSFiT to infer SMBH mass $M_{\rm BH}$ from TDE light curves. OTTER photometry is retrieved in `ABmag` units, converted into the form expected by the `tde` MOSFiT model, and fitted with parallel nested sampling. Two example results are provided: AT 2020zso with $\log M_{\rm BH}=6.14^{+0.13}_{-0.24}\ M_\odot$ and AT 2021sdu with $\log M_{\rm BH}=5.53^{+0.22}_{-0.25}\ M_\odot$ [2509.05405]. These examples show that OTTER is designed not merely for retrieval but for direct ingestion into established transient-modeling pipelines.

The fourth analysis validates the FLEET photometric classifier on 83 spectroscopically confirmed TDEs with at least four ZTF $g/r$ points. OTTER is used to extract ZTF light curves, which are then scored by FLEET for probabilities of SN Ia, SLSN, and TDE classes. The findings reported are that the most probable class is TDE for 69% of the spectroscopic TDEs, 89% have TDE in the top-3 probabilities, and jetted TDEs fail as expected [2509.05405]. This case study illustrates OTTER’s utility as a benchmark corpus for classifier testing under explicitly defined sample cuts.

## 6. Ingestion, curation, and extension pathway

OTTER includes a structured contribution workflow. In the web interface, single-object upload requires `your_name`, `your_email`, `transient_name`, `koordinate (ra,dec)`, and `bibcode`. Optional metadata include redshift, distance, classification, and host information. Photometry fields include time, filter, magnitude or flux with uncertainty, wavelength or frequency, units, corrections, and bibcode. Bulk upload uses two files, one for metadata and one for photometry [2509.05405].

Automated checks include JSON schema validation through Pydantic, coordinate-format and unit-consistency checks, and existing name or coordinate deduplication through cone search. After submission, an upload goes to a `Pending` table visible to trusted vetters. Vetters compare the upload against existing data and can approve or reject it. On approval, the data are merged into the backend, identical entries are deduplicated with new citations appended, and rejected contributions leave an audit trail [2509.05405]. This workflow indicates that OTTER treats literature aggregation as a curation problem with explicit provenance and change tracking.

Planned extensions include additional transient classes, with the schema described as agnostic to event type; adding supernovae, gamma-ray bursts, or fast radio bursts would involve defining new classification flags and metadata sub-keys such as `t90` for GRBs. The API and web forms are said to be easily extended via modular Pydantic models. Further plans include storage of spectroscopic metadata such as resolution, wavelength range, and line measurements, linking to WISeREP, and integration of host photometry through Astro Datalab queries and VizieR cross-matches [2509.05405].

The future roadmap also includes on-the-fly MOSFiT fitting for new arrivals, web-hooks for real-time community alerts such as via the Transient Name Server, and a scalability model based on Kubernetes and Docker, with the claim that the setup can scale to hundreds of nodes and that ArangoDB auto-sharding will handle millions of transients [2509.05405]. This suggests that OTTER is intended to evolve from a curated archival resource into a broader platform for analysis and community-facing transient-data services.

Source: https://www.emergentmind.com/topics/open-multiwavelength-transient-event-repository-otter