Seedlabs

OneMark: Touch-First Mobile Explorer for Million-Row Datasets

A mobile app that lets analysts explore millions of data rows using touch gestures instead of lists of text.

A mobile app (or embeddable 'explore mode' for mobile BI apps) where any dataset opens as a single aggregate mark that analysts sculpt into facets with six touch gestures — never rendering raw rows, so huge datasets stay fluid on a phone.

Computer ScienceData Visualization and Analytics
Cognitive-Adaptive Visual AnalyticsMobile business intelligence and field analytics (retail merchandising, insurance field operations)

Concept

A mobile app, or an embeddable exploration mode for existing mobile BI apps, built on Aggregate Query Sculpting (AQS). Every dataset opens as one visual mark — a single aggregate of the entire table (e.g., total revenue across all transactions). The analyst then sculpts that mark with six touch gestures mapped to the P6 operations: tap an attribute to pivot (facet the aggregate), drag to partition facets across the screen, long-press to peek inside a subset via an aggregate view, pinch subsets together to pile them, pull a subset out to project it onto a fresh canvas, and flick to prune it away.

The wedge is field analytics: retail category managers walking stores, insurance adjusters on site, and sales reps between meetings currently get static mobile dashboards with pre-built filters. OneMark gives them full ad-hoc faceted querying on a phone. Because every state is an aggregate — never raw rows — million-row datasets stay fluid on small screens with no overplotting and no scroll-and-squint tables. The single-mark start also keeps initial cognitive load minimal (one mark instead of a wall of charts), matching the theme finding that excessive visual complexity limits working memory.

Why now

Paper [0] demonstrates DATAOPSY, a working AQS prototype with fluid interaction validated on both desktop and touch-based mobile devices, across two case studies and three application examples — the interaction technique is proven on the exact form factor this product targets, not just a workstation demo. Its 'born scalable' design (starting from a single mark aggregating the entire dataset) means the initial mobile view is one cheap aggregate, sidestepping the rendering and overplotting problems that keep big-data exploration off phones today. Older corpus work [5] argues mobile and ubiquitous computing are poised to transform visualization and data-driven decision-making, and [6] shows analysts already want gesture- and speech-driven visualization while on the move — the demand side exists; [0] supplies the missing query technique.

Written by GLM · 9 Oct 2026

AI assessment

Backed by 3 papers89

A highly focused, technically grounded tool that solves the 'big data on small screens' problem by replacing row-rendering with a gesture-based aggregate sculpting interface.

Evidence strength
5/5
The idea is directly derived from the DATAOPSY prototype which specifically validated the P6 operations on touch-based mobile devices across multiple case studies.
Market pull
4/5
Field analysts in retail and insurance have a clear pain point with static mobile dashboards, and the named beneficiaries are the primary owners of the BI ecosystem.
Novelty & moat
4/5
Unlike the listed catalog ideas which focus on navigation or layout, this introduces a fundamentally different interaction grammar (AQS) for data manipulation.
Feasibility
4/5
The core logic is already prototyped in the research; the primary challenge is the engineering of the gesture-to-query mapping and backend aggregation.
Wedge clarity
5/5
The 'field analytics' wedge is sharp and specific, targeting users who need ad-hoc exploration while physically moving through a site.
Simplicity / focus
5/5
The product is a single, cohesive interaction model (one mark $ ightarrow$ sculpt) rather than a broad platform of unrelated features.

Scored by Gemma 4 · 9 Oct 2026. Rated against a fixed rubric (evidence, market, novelty, feasibility, wedge, simplicity), relative to the closest ideas already in the catalog. A prior estimate to compare ideas before real-world signal arrives.

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Who benefits

  • Domocompany

    Domo is a mobile-first BI vendor whose pitch is business data anywhere; an AQS exploration mode gives its app full ad-hoc faceted querying on phones instead of pre-built cards, directly extending its core use case.

  • Microsoft (Power BI Mobile)company

    Power BI Mobile serves millions of business users who today mostly consume static report pages; an AQS 'explore' mode would differentiate the mobile app by letting users pivot and peek into full datasets on the go.

  • Qlikcompany

    Qlik's associative engine already supports faceted aggregate exploration; AQS's P6 gestures provide a touch-optimized interaction layer that fits its exploration-centric product on mobile.

  • Walmartcompany

    Store and category managers walking floors need ad-hoc answers from millions of transaction rows; a single-mark start with touch sculpting replaces fixed mobile dashboards with on-the-spot querying.

Research it builds on

  1. Data Analytics Anywhere and Everywhere
    Niklas Elmqvist · 2023 · 20 citations
    All ideas from this paper →
  2. Wizualization: A “Hard Magic” Visualization System for Immersive and Ubiquitous Analytics
    Andrea Batch, Peter Butcher, Panagiotis D. Ritsos et al. · 2023 · 18 citations
    All ideas from this paper →
  3. Dataopsy: Scalable and Fluid Visual Exploration using Aggregate Query Sculpting
    Md Naimul Hoque, Niklas Elmqvist · 2023 · 4 citations
    All ideas from this paper →
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feasibility