DataCal calculates projected data volumes for scientific field campaigns from instrument specifications and sampling schedules — producing funder-ready figures for your Data Management Plan.
Each travelling dot follows a real process path. Inside the Calculate box, equations run against your instrument parameters. The result emerges as a calculated volume and travels to the output it belongs to.
Every output is generated from the same calculation — each formatted for a different audience and purpose.
Formatted text for the data volume section of your funder's DMP template. The section name, question wording, and source citation are specific to each funder.
Machine-actionable Data Management Plan in JSON format. The byte_size fields are calculated values, not researcher estimates.
Storage volume requirements by instrument, by expedition leg, and by research group. Includes a recommended total allocation with redundancy margin.
Calculated near-real-time transmission requirements per leg, in Mbps, with a satellite link recommendation based on the required throughput.
DataCal is designed as a three-phase lifecycle tool. Phase 1 is live. Phases 2 and 3 are in design.
Before the campaign
Calculate projected data volumes from instrument specifications and sampling schedules. Produce DMP-ready figures, maDMP JSON, storage plans, and bandwidth budgets.
During the campaign
Compare actual data generation against the Phase 1 plan. Receive deviation alerts before storage or bandwidth limits are exceeded.
After the campaign
Accumulate calibration data per instrument type across expeditions. Feed accuracy improvements back into future Phase 1 planning defaults.
DMP output designed for
DataCal is an independent tool and is not affiliated with, endorsed by, or approved by any of the organisations listed above.
* BMBF has no universal DMP template. Requirements vary by funding call (Bekanntmachung). Contact us for guidance on your specific BMBF programme.
DataCal was conceived from direct experience with the data management challenges of large-scale scientific expeditions — not from a product studio.
DataCal's developer co-authored the official data policy for the MOSAiC expedition — 300+ researchers, 20 countries, 375 days, ~150 TB of field data. Published on Zenodo, 2019.
Contributions to the MOSAiC expedition data infrastructure are referenced in Nature Scientific Data (2022). The field data planning approach used in that expedition directly informs DataCal's calculation methods.
DataCal exports are designed to support FAIR data principles. maDMP output follows the RDA DMP Common Standard v1.1 with calculated byte_size fields. Compatible with EOSC, PANGAEA, and Zenodo submission workflows.
DataCal is developed by Anu Ajjan — business analyst, software developer, and data science advisor based in Bremen, Germany. Independent IT consulting practice: I-Gate IT Solutions. Questions, collaboration proposals, or pilot enquiries: anuajjan.com
Early access
DataCal Phase 1 is complete and under validation. We are seeking feedback from researchers, data managers, and computing centre staff ahead of the first institutional pilot.
DataCal is provided on a best-effort basis without warranty or guaranteed update schedule. This is a pre-release research tool.
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