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Temporal Logistics & Inventory Movements Dataset

Dataset Overview

This dataset contains detailed, time-indexed records of logistics, warehouse, and inventory operations.
Each row represents a single operational event (e.g., stock movement, transfer, shipment, or document line) enriched with multiple temporal attributes, spatial warehouse references, and administrative metadata.

The structure is particularly suited for temporal analysis, allowing the reconstruction and study of:

  • Event sequences over time
  • Operational workflows and delays
  • Inventory life-cycles (production → storage → movement → shipment)
  • Temporal correlations between documents, movements, and logistics activities

Temporal Dimension and Analysis Potential

The dataset includes several complementary date and time fields, enabling both coarse-grained and fine-grained temporal studies:

  • Daily / periodic analysis
    Using movement, production, expiration, and document dates to analyze trends, seasonality, and workload distribution.

  • Event sequencing and process mining
    By ordering records via timestamps, it is possible to reconstruct operational pipelines (e.g., inbound → storage → transfer → outbound).

  • Duration and latency measurement
    Comparing start/end dates and movement timestamps allows estimation of:

    • Storage time per lot or item
    • Transfer and handling delays
    • Time-to-shipment and time-to-completion
  • Traceability over time
    Temporal alignment of lots, articles, documents, and shipments enables end-to-end traceability across the supply chain.

  • Anomaly and exception detection
    Time gaps, overlaps, or unexpected sequences can highlight bottlenecks, inefficiencies, or data inconsistencies.


Analytical Use Cases

Typical analyses supported by this dataset include:

  • Time-series analysis of inventory movements
  • Lead-time and throughput evaluation
  • Lot aging and expiration risk monitoring
  • Operational performance monitoring by day, hour, or period
  • Historical reconstruction of warehouse and shipping activities

Scope

This dataset is designed for:

  • Temporal analytics and forecasting
  • Process mining and operational intelligence
  • Logistics and warehouse optimization studies
  • Auditability and historical analysis of inventory flows

It is not limited to static inventory snapshots, but instead provides a dynamic, event-driven view of logistics operations over time.

Dataset Structure Documentation

This dataset represents transactional and logistical records, likely related to warehouse management, shipping, inventory movements, and document tracking.
Each row corresponds to a single operational record (e.g., shipment, movement, or document line).


Columns Description

Identifiers and Core References

  • id: Unique internal identifier of the record.
  • cont: Container or batch identifier.
  • dtmo: Movement date.
  • caus: Causal code indicating the reason/type of movement.
  • segno: Sign of the movement (e.g., debit/credit, in/out).
  • conf: Configuration or confirmation flag.
  • udc: Logistic unit or handling unit code.
  • lotto: Lot or batch number.
  • extra: Extra or custom flag/field.

Warehouse / Location Information

  • stab: Plant or warehouse code.
  • maga: Warehouse area or main storage identifier.
  • area: Specific storage area.
  • cors: Aisle identifier.
  • posi: Position or bin location.
  • cell: Cell or slot within the position.

Transferred Location Fields

(Values after a transfer or movement)

  • stab_trf: Destination plant/warehouse.
  • maga_trf: Destination warehouse area.
  • area_trf: Destination area.
  • cors_trf: Destination aisle.
  • posi_trf: Destination position.
  • cell_trf: Destination cell.

Article / Item Information

  • arti: Main article or item code.
  • arti1 – arti6: Additional or related article codes.
  • qt_pezzi: Quantity in pieces.
  • qt_conf: Quantity per package.
  • tipo_nomi: Type/category of item naming.
  • nomi: Item name or description reference.

Program and Processing

  • prog: Program or process identifier.
  • prog_trf: Program identifier for transfer operations.
  • ragg: Aggregation or grouping code.
  • solo_per_host: Flag indicating host-only processing.

Document and Administrative Data

  • tipo_docu: Document type.
  • anno_docu: Document year.
  • nume_docu: Document number.
  • riga_docu: Document line number.
  • anno_viag: Travel/shipment year.
  • viaggio: Travel or shipment identifier.
  • uten: User or operator ID.
  • term: Terminal or workstation identifier.

Dates and Time Fields

  • dtlo: Lot date.
  • dt_scad: Expiration date.
  • dt_iniz: Start date.
  • dt_fine: End date.
  • dt_prod: Production date.
  • dt_movim_host: Movement date recorded by host system.
  • d_rest: Residual or remaining date.
  • oramo: Time of the movement (HH:MM:SS).

Shipping and Logistics

  • tipo_sped: Shipping type.
  • rest: Residual quantity or status flag.
  • cpv_movim_cont: Container movement reference code.
  • posi: Physical position involved in shipping.

Notes

  • Date fields may appear in localized formats (e.g., 09-gen-24).
  • Masked values (e.g., XXXXXXXXXX) indicate anonymized or sensitive information.
  • Empty fields represent optional or non-applicable data for specific records.

Example Use Cases

  • Warehouse movement tracking
  • Shipment and logistics analysis
  • Inventory and batch traceability
  • Document and operational auditing

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