Look at specific datasets
See the content, source, access route and whether the licence is clear, before you go further.
Open the public dataset libraryTurn scattered data
into usable value.
The data you need is often scattered across government portals, statistical agencies, international organisations and academic databases.
Five core capabilities
From finding data to keeping it usable
Dataset Discovery
See what already exists, then decide if it fits
Browse the library by topic. Use the guides to see where this kind of data usually lives.
EconomicsEconomics and social scienceMacro, trade, survey and development data.
HealthPublic health and medicinePopulation, health and epidemiology data.
GeospatialGeospatial and remote sensingRemote sensing, population and land-use data.
Machine learningMachine learning and corporaImage, text and multilingual corpora.
Find sources from the question
Where this kind of data usually sits, whether you need to apply, and what is commonly missing.
View data-finding guidesDataset Search
State the conditions, then judge whether it can be obtained
You need not know the platform names first. Tell Xiaoju the intended use and the conditions that must be met; it confirms the requirement, then searches.
Search across sources
Combine specialist terms, synonyms and several search routes to gather candidates.
Check against conditions
Judge each candidate: met, close, unconfirmed or clearly unsuitable.
Show sources and gaps
List publishers, source pages and visible access routes. File, licence and use limits still needing human checks are marked.
Prepare a report
Organise matches, close candidates, leads, exclusions, sources, gaps and next steps.
- Basic Search — FreeA quick look at whether related public data exists, with main candidates and clear gaps.
- Complete Search Report — RMB 10 per run / 1 creditExpands terms and search paths for a fuller candidate list and item-by-item judgement. It does not include manual downloads, file-content, field or sample checks, or a final licensing opinion.
- Human Deep Verification — Quoted separatelyChecks actual access routes, file structures, fields, samples, licence conditions and access requirements for priority candidates.
- Custom Dataset — Quoted after assessmentCollection, cleaning, integration, labelling, quality control and formal delivery when public data cannot be used as-is.
- Results can be viewed online, saved in the workspace, revisited by version, exported to Word and sent by email; PDF export is available when the runtime supports it.
Custom Datasets
When public data is not enough, prepare it to the required standard
When volume, fields, time, geography, format, labels or quality fall short, we can continue collection, cleaning, preparation and checks against explicit technical requirements.
Confirm feasibility and acceptance first
First assess sources, feasibility, processing, main risks and acceptance criteria. A sample can confirm the direction before formal work begins.
Define deliverables by the agreed scope
Deliverables can include primary data, a field dictionary, source notes, README, processing definitions, sample checks, exception notes, version records and agreed scripts or tools.
Custom work is more than a batch of files. Sources, fields, methods and scope should be clear, and you should be able to accept the result as agreed.
Database Services
Turn a one-off delivery into a data system you can keep using
When data needs ongoing updates, shared access, repeated queries or long-term maintenance, it can be built into a thematic database.
Data modelField systemMulti-source ingestionData standardisation and relationshipsData quality rulesQuery and management interfaceAPIScheduled updatesLocal, intranet or private deployment
Database services are delivered by project. Scope, deployment environment, update approach, maintenance period and acceptance criteria are confirmed before the project begins.
AI Agent Customization
Turn repeat data work into a stable workflow
Turn existing processing experience, quality standards and operating rules into a dedicated agent that can run repeatedly. Suitable for cleaning, matching, extraction, review, batch work and recurring reports.
Agents fit stable, repetitive, rule-based work. Research design, exceptions, quality decisions and final acceptance stay with people.
Why DeepSData
Every step sets out the basis, the limits and the next step
Real search
Show only data candidates and sources that were actually found; do not manufacture matches.
Checked against your conditions
Explain which required conditions are met, close, unsuitable or still unconfirmed.
Sources in the open
When licences, fields, quantities or access conditions cannot be verified, we say so. We do not treat unverified information as a certain conclusion.
Results you can accept
Search reports, data files, field notes and processing definitions are delivered as agreed and can be checked against clear standards.
Project services
Selected project experience
Real user feedback
Feedback from completed projects
The dataset split was handled carefully. The training and validation sets had highly consistent distributions with no obvious shift.
The raw data had many formatting problems. They cleaned everything up and standardized the character encoding to UTF-8, so it was ready to use.
The delivery documented the data-processing rules as well. It gives our team a useful reference for building similar datasets in the future.
Across tens of thousands of records, we could hardly find omissions or obvious labelling errors. The quality control was solid.
The delivered dataset could be used for model training immediately. I did not need to write another preprocessing script.
Formats, encodings and naming conventions were consistent across delivery batches, so the files merged without conflicts.
The de-identification was thorough. Information that could identify a specific person or address was removed or transformed.
For multimodal data, the image-to-text relationships were maintained accurately with no obvious mismatches or missing pairs.
Start a consultation
Unsure where to begin?
Describe the task and the conditions that must be met. Xiaoju will advise whether to begin with existing material, a search or custom preparation.