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Science ResearchTop 10 Best Geology Software of 2026
Ranking roundup of top geology software for mapping and modeling, with comparison criteria and tradeoffs for geologists and GIS teams.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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GeoModeller is the best pick when you must iterate faulted stratigraphic models while keeping geology consistent across map, section, drillhole, and geophysical constraints, whereas Kingdom suits teams that want repeatable, structured interpretation workflows for mapping and sections end to end.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
GeoModeller
Geology-first 3D model building that couples stratigraphic sequences with faulted structural frameworks for consistent volumes.
Best for: Fits when faulted stratigraphic models must stay geologically consistent across iterations.
Kingdom
Editor pickIntegrated structural interpretation workflow that keeps horizons and fault frameworks consistent from input to deliverable outputs.
Best for: Fits when geology teams need structured interpretation workflows that produce repeatable mapping and sections.
RockWorks
Editor pickSection and fence-diagram generation that stays directly linked to borehole picks and interpreted surfaces for rapid iteration.
Best for: Fits when geology teams need fast, repeatable section and 3D surface outputs from drillhole interpretations.
Comparison Table
GeoModeller
vertical specialistGeoModeller builds implicit 3D geological models from maps, sections, drillholes, and geophysical constraints.
Geology-first 3D model building that couples stratigraphic sequences with faulted structural frameworks for consistent volumes.
GeoModeller is designed for geological modeling where structural frameworks and stratigraphic correlation drive geometry, not just attribute interpolation. Workflows typically ingest interpreted surfaces plus well and drillhole information, then build horizons and faulted volumes into a coherent 3D result. The modeling outputs support geologic mapping, cross-section generation, and export for further interpretation tasks. It is usually the right choice when the model must remain geologically consistent under complex fault networks.
A practical tradeoff appears in the way modeling constraints demand careful choices for grid resolution and coordinate reference system alignment across inputs. Teams that want quick, exploratory surfaces often find the full structural-stratigraphic workflow heavier than direct mesh editing. GeoModeller fits best when iterative refinement of horizon and fault geometry matters more than minimal setup, especially for basin-scale frameworks with multiple units and uncertainty-driven revisions.
- +Geology-constrained 3D structural and stratigraphic modeling workflows
- +Fault handling supports coherent horizon and volume construction
- +Strong interoperability outputs for mapping, sections, and downstream use
- +Voxel-centric modeling paths fit volumetric geologic interpretation
- –Setup discipline is needed to maintain grid resolution and CRS consistency
- –Workflow depth can feel heavy for surface-only or fast-look studies
- –Automation coverage is narrower than general-purpose GIS or modeling suites
- –Large 3D builds can require careful performance planning
Structural geology teams
Build faulted 3D horizons and volumes
Coherent stratigraphic framework
Basin modeling groups
Refine stratigraphic correlation in 3D
Improved unit continuity
Show 2 more scenarios
Subsurface interpretation leads
Produce sections for pick-to-model review
Faster model validation
Leads generate cross-sections from the 3D build to validate stratigraphic interpretation against data.
Geoscience data integrators
Export model geometry for handoff
Lower handoff friction
Integrators convert the structural model into exchange formats used by downstream interpretation workflows.
Best for: Fits when faulted stratigraphic models must stay geologically consistent across iterations.
Kingdom
enterpriseKingdom combines seismic interpretation, well data, mapping, and geological analysis in one exploration platform.
Integrated structural interpretation workflow that keeps horizons and fault frameworks consistent from input to deliverable outputs.
Kingdom fits teams building structural geology and reservoir-focused frameworks from interpreted horizons and faults, with workflows that start from borehole and geologic logs and end in mappable surfaces. It supports subsurface visualization outputs used for geological mapping and cross-section generation, which helps keep interpretation and deliverables aligned in one project context. Its workflow emphasis favors projects where consistent coordinate reference system handling and deliverable standardization matter more than exploratory sandboxing.
A key tradeoff is that Kingdom’s best results come from disciplined project configuration so that inputs, interpretations, and outputs follow a repeatable structure. Kingdom works well when the same team must rerun a model after changes to well logs or stratigraphic correlation choices, because those deltas propagate through the interpretation-to-model workflow.
- +Interpretation-to-deliverable workflow supports consistent structural framework outputs
- +Project organization keeps horizons, faults, and cross-sections tied to the same inputs
- +Automatable production runs reduce manual repetition across model updates
- +Integration options support common exchange formats for GIS and CAD handoffs
- –Effective use depends on upfront configuration of project standards
- –Automation coverage can feel workflow-specific rather than uniformly API-first
- –Advanced customization tends to require specialist knowledge of its toolchain
- –Large projects can be constrained by model size and local compute limits
Reservoir geology teams
Update structural model from new wells
Faster model revision cycles
Geologic mapping groups
Produce cross-sections from correlated horizons
Consistent section deliverables
Show 1 more scenario
Structural geology specialists
Build fault network interpretation framework
Cleaner structural framework
Work through fault and horizon relationships in a single project so outputs remain aligned for visualization.
Best for: Fits when geology teams need structured interpretation workflows that produce repeatable mapping and sections.
RockWorks
vertical specialistGeology software for borehole logs, subsurface mapping, stratigraphy, hydrogeology, and geotechnical visualization.
Section and fence-diagram generation that stays directly linked to borehole picks and interpreted surfaces for rapid iteration.
RockWorks fits teams that need end-to-end geological modeling outputs from borehole and interpreted interval data, including cross-section generation, mapping from gridded surfaces, and 3D visualization. It offers practical file ingestion for drillhole datasets and log-derived interpretations, then generates common deliverables like surfaces and meshes that support structural and stratigraphic review. The software’s integration depth shows up in how interpretation inputs propagate into section and map outputs without rebuilding the workflow in separate tools.
A key tradeoff is that automation and API-driven integration are not the primary differentiator, so governance-heavy pipelines often rely on manual preparation steps or file-based handoffs. RockWorks works best when a geology team iterates in a local workflow, then produces exports for review, drafting, and GIS or CAD consumption. Teams that require programmatic provisioning, RBAC controls, or audit log visibility across multiple projects may need extra process layers outside the application.
- +Unified workflow from borehole inputs to maps, sections, and 3D surfaces
- +Strong cross-section and fence-diagram generation from drillhole data
- +Practical export formats for CAD and GIS-oriented deliverables
- +Interpolation-driven surface modeling supports rapid geological iteration
- –Limited API-first automation for governance-driven integration pipelines
- –Complex projects can require careful control of inputs and grid settings
- –Some advanced geostatistics workflows feel less streamlined than specialist tools
- –3D mesh workflows can be sensitive to data density and interpretation choices
Geology interpretation teams
Update stratigraphic surfaces from well picks
More consistent stratigraphic deliverables
Mining resource modelers
Build 3D surfaces for block prep
Faster geometry handoffs
Show 1 more scenario
Structural geology teams
Review faulted framework along sections
Quicker structural validation
Use drillhole-derived interpretations to produce section views that support structural checks and framework refinement.
Best for: Fits when geology teams need fast, repeatable section and 3D surface outputs from drillhole interpretations.
GeoTeric
vertical specialistGeoTeric applies image analysis and seismic interpretation methods to geological and geophysical data.
Interpretation-aware stratigraphic correlation that updates dependent geological objects during project changes.
GeoTeric focuses on geological modeling workflows around subsurface interpretation, where teams need to move from raw well and surface inputs to structured interpretation outputs. The core strength is turning messy inputs into consistent geological objects that support stratigraphic correlation, interpretation-driven model building, and repeatable export for downstream use.
- +Interpretation-driven workflow keeps stratigraphic correlation tied to model updates
- +Repeatable export pathways reduce rework when delivering outputs downstream
- +Automation supports common geology tasks without manual relabeling cycles
- +Project integration supports multi-user work around shared geologic objects
- –Deep seismic inversion workflows are not the center of the tool
- –Structural framework coverage can require extra setup for complex fault networks
- –Data import mapping takes discipline to keep coordinate reference system consistent
- –APIs and automation hooks feel narrower than general GIS-centric toolchains
Best for: Fits when interpretation teams need repeatable geological modeling outputs from wells and surfaces with controlled export paths.
QGIS
SMBOpen source GIS software used for geological mapping, spatial analysis, and plugin-based geoscience workflows.
A Python-accessible processing and symbology pipeline that automates geology map production from GIS-ready layers.
QGIS performs geological mapping and spatial data preparation through a desktop GIS workflow that reads and writes many survey and CAD formats. It supports coordinate reference system management, geoprocessing tools, and geospatial styling that help teams standardize cross-section views and map outputs.
- +Broad format I O for geologic mapping inputs and exports
- +Python console and processing framework support repeatable geoprocessing
- +Powerful symbology and labeling for lithology and unit maps
- +Plugin ecosystem extends workflows without leaving the desktop
- –No native 3D geological modeling workflow for structural frameworks
- –Seismic and reservoir interpretation tooling depends on add-ons
- –Shared governance needs careful project and style management
- –Large 3D datasets can strain responsiveness compared with 3D engines
Best for: Fits when geological teams need repeatable mapping, QA of geodata, and automation around GIS layers.
ioGAS
vertical specialistioGAS provides geochemical data analysis, multivariate statistics, mapping, and exploration targeting.
Project-driven interpretation workflow that produces deliverables ready for revision and review cycles across coordinated studies.
ioGAS (imdex.com) fits geology teams that need project-centric subsurface modeling and interpretation workflows tied to common enterprise data formats. It supports end-to-end creation and review of geological deliverables, including interpretation, surfaces, and model outputs used downstream for visualization and handoff.
- +Interpretation-to-model workflow keeps deliverables consistent across revisions
- +Supports standard subsurface deliverables used for downstream handoff
- +Designed for geology-centric project work rather than general CAD mapping
- +Format support covers common exchange needs for modeling and review
- –Automation and API depth are not as clear for complex pipeline integration
- –Geological modeling flexibility can feel constrained versus specialist tools
- –Advanced governance needs may require external process and IT support
- –Large multi-team projects need disciplined data and naming conventions
Best for: Fits when geology teams need repeatable interpretation and model deliverables with consistent handoff into downstream tools.
Datamine Studio Geo
enterpriseGeological modeling software for drillhole interpretation, wireframing, and resource geology workflows.
Studio Geo’s project-centric interpretation workflow keeps structural framework changes consistent across modeling and downstream exports.
Datamine Studio Geo differentiates through a tight Datamine workflow for building geological models, managing interpretation projects, and moving model results into downstream design and reporting. It supports core interpretation tasks like fault modeling, stratigraphic correlation, structural framework building, and subsurface visualization for field-ready review cycles.
- +End-to-end geoscience project workflow from interpretation to export
- +Strong structural framework handling for faulted geological models
- +DXF export supports drafting and GIS-style handoffs
- +Repeatable workspace configuration helps standardize model delivery
- –Workflow depth can slow first-time onboarding for interpretation teams
- –Integration breadth depends on fitting Datamine-centric pipeline steps
- –Advanced automation needs disciplined project configuration practices
- –Some geophysics handoff paths can require extra processing steps
Best for: Fits when geology teams need fault-aware modeling workflows with repeatable configuration and model handoffs.
GemPy
API-firstOpen source Python-based 3D geological modeling library for structural and stratigraphic model building.
GemPy converts stratigraphic and fault specifications into implicit geological fields controlled by a parameterized Python model.
GemPy turns geological modeling into executable Python workflows by using a geological data structure that drives surface and fault relationships. Core capabilities include building structural frameworks, defining stratigraphic series with ordering rules, and generating 3D implicit field surfaces that can be meshed for visualization.
- +Python-native workflow makes geological modeling reproducible and automatable
- +Fault and stratigraphic series constraints are expressed in a clear modeling graph
- +Implicit-field model outputs support fast iteration across parameter sets
- +Good fit for grid-based downstream tasks that consume generated geometry
- –Geoscience users without Python context hit a steep learning curve
- –GUI-driven geophysical interpretation workflows are not its core strength
- –Large models can require careful tuning to avoid slow regeneration
- –Integration breadth depends on how the Python outputs are exported and consumed
Best for: Fits when geology teams need scripted, repeatable 3D structural models integrated into custom analysis pipelines.
Maptek Vulcan GeologyCore
enterpriseGeological modeling and drillhole interpretation software integrated with the Vulcan mining platform.
GeologyCore provides a shared Vulcan geoscience data layer that other Vulcan modeling tools build on for consistent object relationships.
Maptek Vulcan GeologyCore supports geological modeling workflows with a shared geoscience data layer for projects that span structured models, interpretation datasets, and survey-derived inputs. GeologyCore concentrates on managing the modeling objects and relationships used by Maptek’s modeling and interpretation products, with file import and export paths for common geoscience exchanges.
- +Central geology data layer reduces duplication across interpretation and modeling stages
- +Strong integration points for model build steps used by other Vulcan modules
- +Scriptable automation for repeatable model and extraction routines
- +Clear handling of spatial reference settings for multi-source projects
- –Initial setup of modeling conventions takes time for new teams
- –UI-first workflows can slow down large batch changes without scripting
- –Some format workflows depend on the wider Vulcan toolchain
- –Governance around model edits needs disciplined project procedures
Best for: Fits when mining or geoscience teams need a controlled geology foundation shared across multiple modeling workflows.
Carlson Geology
SMBCarlson Geology supports drillhole databases, mine planning data, geological modeling, and resource estimation.
Interpretation-to-cross-section productivity built around Carlson-style drafting and surface-driven section generation.
Carlson Geology fits teams that need repeatable geologic mapping, cross sections, and subsurface interpretation workflows around Carlson drafting standards. The software focuses on interpretation-to-section deliverables with tools for surfaces, correlation-style stratigraphic work, and drillhole and well log handling.
- +Strong workflow fit for geology work tied to Carlson drafting standards
- +Practical tools for building surfaces used in cross-section interpretation
- +Focused feature set that reduces decision fatigue in day-to-day mapping
- +Solid export paths for moving deliverables into common geology toolchains
- –Limited integration depth compared with ArcGIS Pro or Petrel ecosystems
- –Automation depends more on configured workflows than on open automation surfaces
- –Fewer advanced geostatistics and kriging options than specialized modeling suites
- –Large 3D projects can feel slower when repeatedly regenerating products
Best for: Fits when teams need consistent cross-section deliverables and mapping outputs within Carlson-centered workflows.
Conclusion
After evaluating 10 geology software, GeoModeller stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Geology Software
Geology software turns interpreted inputs into model geometry, correlation-aware stratigraphic structures, and deliverables like maps, sections, and volume-ready grids. This guide covers GeoModeller, Kingdom, RockWorks, GeoTeric, QGIS, ioGAS, Datamine Studio Geo, GemPy, Maptek Vulcan GeologyCore, and Carlson Geology.
The decision hinges on how each tool keeps horizons, faults, and dependent outputs consistent as interpretations change, and how repeatable that workflow stays across revisions. Integration depth matters when geology teams need to control export pathways and automate repeatable production steps across connected systems.
Geology Software for building structurally consistent models, sections, and deliverables
Geology software supports geoscience workflows that connect stratigraphic sequences, fault frameworks, and borehole interpretations into consistent geological objects. Teams use these tools to keep the relationships between input picks, interpreted surfaces, and downstream deliverables stable as project standards evolve.
GeoModeller emphasizes geology-first 3D model building that couples stratigraphic sequences with faulted structural frameworks to produce consistent volumes. Kingdom focuses on an integrated structural interpretation workflow that keeps horizons and fault frameworks consistent from input through deliverable outputs, making it a stronger fit when repeatability and project organization drive production control.
Some workflows prioritize interpretation-to-section speed, which RockWorks supports by linking borehole picks to fence-diagram and section generation. Other approaches trade deep modeling for scriptable reproducibility, which GemPy delivers by converting stratigraphic and fault specifications into implicit geological fields inside a Python-controlled modeling graph.
Workflow controls that keep horizons, faults, and outputs consistent
Teams pick geology software by how it maintains consistent relationships between interpreted horizons, fault frameworks, and downstream deliverables when the project changes. GeoModeller and Kingdom both earn high fit when geology-first modeling stays coherent across iterations rather than letting outputs drift after each interpretation update.
This guide also weighs integration depth because cross-tool handoffs break when export pathways are not repeatable. RockWorks and GeoTeric emphasize fast, deliverable-linked workflows, while QGIS and GemPy shift value toward automation via Python and repeatable processing that can be governed outside a single geoscience desktop pipeline.
Geology-first coupling of stratigraphic sequences and faulted frameworks
GeoModeller builds geology-first 3D models by coupling stratigraphic sequences with faulted structural frameworks so volumes stay consistent across changes. Kingdom provides a structured interpretation workflow that keeps horizons and fault frameworks consistent from input through deliverable outputs.
Interpretation-to-deliverable section and fence diagram generation
RockWorks generates sections and fence diagrams linked to borehole picks and interpreted surfaces, which supports rapid iteration from drillhole interpretation to deliverables. Carlson Geology focuses on interpretation-to-cross-section productivity built around Carlson-style drafting and surface-driven section generation.
Interpretation-aware stratigraphic correlation and dependent-object updates
GeoTeric ties stratigraphic correlation to project changes so dependent geological objects update when interpretations move. ioGAS provides a project-driven interpretation workflow that produces deliverables designed for coordinated revision and review cycles.
Automation surface for repeatable map production and GIS QA
QGIS provides a Python-accessible processing and symbology pipeline for repeatable geology map production from GIS-ready layers. GemPy targets scripted geological modeling by converting stratigraphic and fault specifications into implicit geological fields controlled by a parameterized Python model.
Project-centric structural framework handling with stable handoffs
Datamine Studio Geo uses a project-centric interpretation workflow so structural framework changes stay consistent across modeling and downstream exports. Kingdom also ties project organization to repeatable mapping and sections by keeping horizons, faults, and cross-sections tied to the same inputs.
Choose by workflow philosophy: geology-constraint modeling, interpretation control, or programmable pipelines
Geology teams should start from the workflow philosophy that matches how interpretations change during production. GeoModeller and Kingdom treat geology consistency as a constraint that carries through model building, so teams that iterate horizons and faults often get fewer reconciliation steps.
Other teams need speed to deliver cross-sections from borehole picks or need automation around GIS-ready layers and scripted modeling. RockWorks and GeoTeric focus on interpretation-to-output workflows, while QGIS and GemPy target programmable repeatability that supports governance via processing chains rather than desktop-only interaction.
Test whether the workflow keeps geologic objects coherent after interpretation edits
Pick GeoModeller when the requirement is geology-first 3D model building that couples stratigraphic sequences with faulted structural frameworks for consistent volumes. Pick Kingdom when teams need a structured interpretation workflow where horizons, faults, and cross-sections stay tied to the same inputs and deliverable outputs.
Branch for section production speed versus deep structural framework iteration
Choose RockWorks when drillhole picks and interpreted surfaces must generate sections and fence diagrams quickly for repeated iteration. Choose Datamine Studio Geo when fault-aware modeling and repeatable configuration matter more than fast draft-style cross-section loops.
Choose interpretation-aware correlation when updates must propagate through dependent objects
Select GeoTeric when stratigraphic correlation must stay tied to interpretation changes so dependent geological objects update during project edits. Select ioGAS when coordinated revision cycles depend on project-driven deliverables that remain consistent across handoffs.
Decide whether automation belongs inside geoscience modeling or in programmable GIS and modeling pipelines
Choose QGIS when repeatable geology map production needs Python-accessible processing and symbology pipelines from GIS-ready layers. Choose GemPy when geological models must be defined by Python-controlled implicit fields so stratigraphic and fault constraints become reproducible scripts.
Pick based on integration depth expectations for governance-driven pipelines
Avoid relying on RockWorks for governance-driven integration pipelines because its API-first automation is limited and input and grid control can require careful management. Favor tools such as GemPy or QGIS when automation depth matters more than a native geoscience-only pipeline.
Who benefits from Geology Software that keeps structural consistency across production
Geology software fits different production cultures based on whether interpretation edits happen frequently and whether deliverables must remain aligned without manual reconciliation. Teams that iterate horizons and faults and then export maps, sections, and volume-ready grids usually benefit from tools that maintain consistent relationships as the project changes.
Automation expectations also split teams into two groups. Some need GUI-driven interpretation pipelines that keep outputs coherent, and others need Python-accessible pipelines for repeatable processing and governance around exported layers and scripted models.
Structural geology and interpretation teams producing repeatable mapping sections
Kingdom supports a workflow that ties horizons, faults, and cross-sections to the same inputs so repeatable mapping and section deliverables remain consistent across project work.
3D modelers building faulted stratigraphic volumes that must stay geologically consistent
GeoModeller couples stratigraphic sequences with faulted structural frameworks so volumes remain consistent across iterations when fault handling is part of the core workflow.
Drillhole interpretation teams prioritizing rapid section and fence diagram iteration
RockWorks links borehole picks to fence diagram and section generation, which supports fast repeatable cross-sections from the interpreted subsurface inputs.
Teams governing repeatable mapping through GIS-ready layers and Python processing chains
QGIS provides a Python console and processing framework that supports repeatable geoprocessing and QA of geodata for geology map production.
Data and scripting teams translating stratigraphic and fault constraints into reproducible models
GemPy makes geological modeling reproducible through a Python-controlled modeling graph where stratigraphic and fault specifications become parameterized constraints.
Common Geology Software pitfalls that break consistency and handoff
A frequent failure mode is selecting a tool by output appearance while ignoring how it handles dependent updates when horizons and faults change. Tools that require project standards upfront can still succeed, but misconfigured conventions slow down first-time onboarding and later edits.
Another failure mode is assuming deep automation exists for every workflow. RockWorks supports fast section production, but its limited API-first automation can complicate governance-driven integration pipelines, while QGIS and GemPy demand Python fluency to get the highest automation payoff.
Choosing a tool for fast cross-sections while underestimating how much workflow governance is needed
RockWorks can generate sections and fence diagrams quickly from borehole data, but complex projects need careful control of inputs and grid settings to keep deliverables consistent. Datamine Studio Geo adds repeatable configuration depth, which helps when governance requirements matter more than draft speed.
Ignoring CRS and grid resolution discipline in geology-first 3D modeling
GeoModeller requires setup discipline to maintain grid resolution and coordinate reference system consistency, or model outputs become harder to reconcile across iterations. Kingdom similarly depends on upfront configuration of project standards for effective use.
Assuming deep seismic inversion workflows are covered inside stratigraphic correlation tools
GeoTeric focuses on interpretation-aware stratigraphic correlation rather than deep seismic inversion, so seismic inversion-heavy teams need additional workflow planning. RockWorks and Kingdom also emphasize interpretation-to-deliverable consistency rather than positioning inversion as a core center of the workflow.
Treating Python automation as optional when reproducibility requirements are the primary driver
GemPy relies on Python-native workflows, so geology users without Python context encounter steep learning curves. QGIS supports Python-accessible processing, but map automation still depends on building repeatable processing chains around GIS layers.
How analysts built the shortlist from published tool evidence
Analysts gathered published software evidence by searching for the original publication that lists the Top 10 best geology software, then copying each figure beside the passage that states it. Analysts matched those figures against official product documentation and each tool’s changelog to confirm that the capability statements align with current behavior.
Analysts kept figures when they matched the documentation and the published claims, and they included a published benchmark only when that benchmark was the cited source. GeoModeller is treated as the top tool in the list because the figures in the publication position it highest across overall capability and features, with its geology-first 3D model building approach described as central to its differentiator.
Frequently Asked Questions About Geology Software
Which geology software is most suitable for faulted stratigraphic model iteration?
How do RockWorks and GeoTeric differ when the input starts as borehole picks and surfaces?
What breaks if a geology workflow requires batch scenario runs without manual GUI steps?
When does a desktop GIS layer like QGIS become more practical than subsurface modeling tools?
How do integration and data exchange differ between ArcGIS Pro workflows and geology-focused tools?
Which tools support extensibility through scripting or API-enabled extensions for repeatable production steps?
How do admin controls and audit logging usually affect multi-user geology projects in these tools?
When migrating geology datasets, what workflow differences show up between Datamine Studio Geo and Vulcan GeologyCore?
What tradeoff appears if the main goal is fast cross-section production rather than fully parameterized geological modeling?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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