Manifest is an investigative toolkit intended for researchers, journalists, students, and scholars interested in visualizing, analyzing, and documenting supply chains, production lines, and trade networks.
Feature Overview
Overview of Manifest interface, with Manifest document and map visualization.
Popup with clustered points on map visualization.
Graph visualization showing connections within a Manifest document.
Flow visualization showing connections and composition within a Manifest document.
Chord visualization showing connections and composition within a Manifest document.
List visualization for advanced sorting of nodes with a Manifest document.
Manifest documents are represented as JSON files and can be downloaded at any time.
Manifest documents with quantitative variables (like this one) can be visually scaled to compare values.
Nodes in Manifest documents can be categorized to support quick filtering (here, only nodes with the category #inbound are shown).
Nodes can also be filtered by searching for arbitrary text matches (here, a search for "fuel").
Other layers can be loaded on top of Manifest documents. Here a layer showing current marine traffic has been loaded.
Project Goals
Professional logistics platforms developed by companies like SAP, Oracle, and IBM are incredibly complex, suited to global networks with hundreds of suppliers in dozens of countries. These systems interface with numerous data sources, with powerful capabilities for controlling the world's material distribution in the name of "supply chain management." Manifest is not one of these. Similarly, there are many tools available for detailed statistical evaluation, graph analysis, and geospatial modeling. And while Manifest can work in concert with these tools, its primary purpose is to:
Provide common data standards for describing and sharing supply chains or other material networks, along with a simple editor modeled on these standards.
Develop a flexible geospatial viewer for supply chain data that is transparent, interactive, and simple to understand, with support for specialized data views (graph relationships, etc.).
Support basic analytic tools for evaluating and comparing critical supply chain measures.
The result, we hope, is a system flexible enough to meaningfully support a variety of different projects advancing the critical study of logistics.
Design Principles
This flexibility is intended to allow someone using Manifest to map high level connections the same way they might catalogue fundamental details, or to include "materials" not normally present in an industrial logistics platform. It also means that Manifest should be as capable of producing rich supply chain narratives as it is facilitating supply chain analysis. In pursuit of these goals, Manifest has been developed with a number of core design principles:
Manifest is not a database. While we can host Manifest documents and other datasets, the primary workflow for creating and viewing documents happens in the browser, where the Manifest neither sees nor stores the data.
Supply chains in Manifest are not required to be complete, nor are they limited to discrete and self-contained accounts. Rather the interface was developed to support viewing multiple supply chains (or fragments of supply chains) in order to understand relationships between them.
Manifest data tends to be descriptive, rather than rigidly structured. To this end, the Manifest format is designed to be open and general enough to contain information across a range of different contexts, irrespective of the rendering of a particular supply chain or single piece of data.
The goal is a system that rejects the collected and complete in favor of the distributed, the partial, and the temporary.
Project Team
Matthew Hockenberry, Project Director, Assistant Professor of Communication and Media Studies, Fordham University
Colette Perold, Project Codirector, Assistant Professor of Media Studies, University of Colorado Boulder
Ingrid Burrington, Research Coordinator, University of Delaware
Lennox Anderson, Student Developer, University of Colorado Boulder
Karina Garcia, Research Assistant, Fordham University
Project Alumni
Christian Kyle Madlansacay, Fordham University
Kimberly Ternan, Fordham University
Advisory Board
Nicole Starosielski, Associate Professor of Media, Culture, and Communication, New York University
Shannon Mattern, Penn Presidential Compact Professor of Media Studies and Art History, University of Pennsylvania
Chris Csíkszentmihályi, Associate Professor of Information Science, Cornell University
Tamara Kneese, Project Director, AIM Lab, Data & Society
Grant Whytoff, Digital Humanities Strategiest, Center for Digital Humanities, Princeton University