SeaCONEX: Simultaneously Visualizing Ocean Carrier Supply Chain Service Networks and Continuous Vessel Movement Data - OSF
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SeaCONEX: Simultaneously Visualizing Ocean Carrier Supply Chain
Service Networks and Continuous Vessel Movement Data
Mason Leon * Rithika Lakshminarayanan David Saffo Sara Di Bartolomeo
Cody Dunne
Northeastern University
Figure 1: The SeaCONEX Dashboard.
A BSTRACT Keywords: Human centered computing, Geographic visualization,
Geospatial data, Supply chain management, Geographic information
Supply chain disruption and the complexity of maritime and systemst
hinterland freight networks remain key issues around the world.
SeaCONEX is not just a portmanteau of the humble container’s 1 I NTRODUCTION AND P ROBLEM D OMAIN
origin, but a visualization tool that enables users to see the marine
terminal connections for ocean carrier service rotations, investigate The Container Express also known as the CONEX, was deployed
the historical trajectories of vessels assigned to ocean carrier services, by the U.S. military during the Korean War as a modular platform to
and assess deviations from a shortest-path optimal route. In this improve global logistics operations [10]. This containerization con-
paper, we present an approach to integrating ocean carrier service cept was soon reinforced by commercial intermodal1 freight service.
network information with continuous movement data for container On April 20, 1956, Malcolm McLean, “the father of containeriza-
and roll-on/roll-off cargo vessels with reproducibility in mind and tion“, ushered in the modern supply chain era when his SS Ideal
utilizing new open-source industry data standards. We developed X sailed from New York to Houston laden with 58 containers [10].
a multiple-view visualization that presents commercial maritime As containerization took hold, other innovators soon followed suit
freight carrier service connections between marine terminals and with their own proprietary equipment. Even among competitors,
links the spatial temporal movements of vessels assigned to each however, the seamless interchange of cargo across modes required
service over a 90 day period which can be filtered by carrier. A copy uniform design and securement mechanisms. McLean shared his
of this paper along with all supplemental material is available at patent designs with the International Standards Organization (ISO)
https://osf.io/k9nvc/ and common specifications eventually emerged [24].
The modern supply chain is global in scope, incredibly complex,
and essential to the world’s economy. Ocean freight accounts for
* Corresponding author. E-mails: [ leon.m — lakshminarayanan.r — more than 80% of the total world merchandise trade [46]. The sheer
saffo.d — dibartolomeo.s — c.dunne ]@northeastern.edu scale of the maritime industry has led to many opportunities and
challenges as it undergoes digital transformation. This sector rep-
resents a core component of the global supply chain, yet container
liner carrier operations often appear hidden from those outside the
industry. Despite advancements in freight handling and the rise
1 Intermodal: The movement of freight, in a container or on a trailer, by
more than one mode of transportation. The movement can be made from rail
to truck to ship in any order [41]
in logistics information technology, supply chains remain vulnera- Fiorini, Michele et al. [9] present a pipeline using open source GIS
ble to disruption and are plagued by poor visibility and difficulty relational database tools to process raw AIS data and visualize vessel
exchanging cargo and freight network information. routes for maritime spatial planning. As indicated by Wang, Hao
While standards exist for physical intermodal container equip- et al. [48] and Wang, Kai et al. [49], the quantity and poor qual-
ment design, standards regarding the exchange of service informa- ity of AIS data is a challenge when performing exploratory vessel
tion documenting every aspect of a container’s journey throughout movement analysis. Rajabi, Aboozar et al. [45] demonstrate how
the global supply chain are still under development. An increasingly vessel analysis with AIS data can be of great value for “smart port“
difficult question has been in regards to not only standardisation operations and marine terminal scheduling.
and sharing of carrier service information but also the level of data Through the development of open-source geospatial tools and
granularity necessary for stakeholders. For example, the 2020-2021 libraries, Anita Graser discusses the technical complexity required
supply chain disasters and maritime service disruptions have demon- to manipulate spatial temporal data for exploratory analysis is not
strated the need for new approaches to combining different data restricted to the maritime domain [14–19]. In Exploratory Data
sets to analyze supply chain risk. Choke-points in the maritime Analysis (EDA) protocol for identifying problems in continuous
supply chain detrimentally impacted the ability of government and movement data, she demonstrates how to address missing data, pre-
the private sector response to COVID-19 such as the sourcing of cision, consistency, and accuracy problems in an AIS data [13].
personal protective equipment and vaccine manufacturing. Addition- Basole et al. [1] present a visualization tool in their paper that
ally, COVID-19 changes in work, merchandise trade, consumption, enables exploratory analysis of innovations in the global supply
and manufacturing patterns have demonstrated long simmering and chain network of electronics. The approach they use is meant to help
evolving maritime supply chain challenges. The grounding of the make managerial decisions based on actionable insights that reveal
Evergreen Ever Given in the Suez Canal tested an already strained clusters, trends and outliers from the analysis. In their paper on
global supply chain and highlighted a worst case maritime risk transit system maps, Wu et al. [51] present design considerations for
scenario that linked key industry concerns for over-reliance upon computer generated transit maps that are not as easy to understand
the just-in-time-manufacturing strategy, the impact of ultra-large- as human-drawn maps. They found that iterative user testing with
container-vessel (ULCV) deployment, and ocean carrier alliance humans can help improve computer designed maps to a usable state.
consolidation [12] [11]. Stakeholders may have had a better un- Park et al. [44] evaluate the design of a visual analytical system for
derstanding of maritime supply chain impacts using visualization supply chain managers to make decisions. Their application sup-
tools that combine both vessel movement and standardized service ported a number of functions important to decision makers including
network data to provide insights. We present SeaCONEX- a tool network information, industrial activities associated with each port
to help investigate maritime connections between marine terminals, and cost sensitivity.
ocean carrier service rotations, and historical vessel movements.
SeaCONEX combines vessel movement data along with network 3 A H YPOTHETICAL U NITED K INGDOM -B ERMUDA M AR -
connectivity data to present users with a dashboard for investigat- ITIME N ETWORK
ing carrier routes and possible anomalies or discrepancies between
services and vessel operations. We first discuss the specifics of a In this section, we first talk about our client and then describe
case study developed to demonstrate this idea. Then we describe the case study we designed in line with the needs of our client to
the views designed to help users examine maritime supply chain demonstrate our approach. We decided to construct this case study
networks. because some of the data we were provided was proprietary and the
The main contributions of this paper are: amount of data too large to visualize at once.
1. Adapting the Exploratory Data Analysis (EDA) Protocol for
Identifying Problems in Continuous Movement Data to process 3.1 The Customer
and visualize container vessel trajectories, The Volpe National Transportation Systems Center (Volpe) is
2. Extending open-source industry knowledge and standards to a United States Department of Transportation (USDOT) Research
combine inconsistent ocean carrier service information in a Center for advanced logistics and transportation technical expertise
uniform manner to support a container trade network node-link based in Cambridge, MA. Volpe is a fee-for-service organization that
visualization, supports a variety of national strategic transportation projects across
3. Demonstrating a reproducible approach to combining vessel the entire transportation spectrum. For this project we partnered
movement data with ocean carrier service network data in a with Volpe’s Situational Awareness and Logistics Division under the
single visualization tool. Infrastructure Systems and Technology Technical Center.
A key client of the division is the United Kingdom Ministry of
2 R ELATED W ORK Defense (UKMOD). The Volpe team researches, designs, maintains,
An entire field of study, Maritime Informatics2 has recently and develops key multimodal and multi-leg military supply chain lo-
emerged to encompass a variety of existing research areas in or- gistics information assets for UKMOD, allowing the organization to
der to provide a more holistic understanding of the business domain manage mission critical cargo and equipment shipments worldwide
and various approaches to industry data applications. in support of military operations, commitments to allied nations,
A significant focus relates to the study of AIS (Automatic Identi- peacekeeping efforts, and humanitarian aid. Volpe is interested
fication System) [50] data for supply chain operations, port perfor- in innovative visualization tools for their customer to improve the
mance, marine science, maritime economics, and the environmental presentation of logistics data and tools to examine choke-points,
impacts of vessel movements. The processing and storage of AIS performance, and resiliency in the UKMOD supply chain includ-
often involves GIS (Geographic Information System) techniques in ing tracking and understanding vessel movements, and viewing the
addition to large-scale “big-data“ computing concepts. For example, network of port connections.
To provide the end user of our visualization (Volpe) and by exten-
2 Maritime Informatics: the application of information systems to in- sion, their customer (UKMOD), a useful and relevant example for
creasing the efficiency, safety, and ecological sustainability of the world’s how our tool could support the mission, a hypothetical supply chain
shipping industry. It is an applied science, developed by data scientists to scenario (the case study) was developed using accurate geographic
meet the needs of practice and applied by practitioners and data scientists background and real commercial maritime carriers and services. Al-
cooperatively. [25] though the mix of ships and services available in the case study arecommercially operated, they are of similar capabilities and militarily needs and ensure SeaCONEX supported these tasks given the avail-
useful for UKMOD requirements. able data-set. Table 2 contains a task breakdown of high-end user
goals using Brehmer and Munzner’s multi-level task typology [2].
3.2 The Case Study We identified the primary domain tasks to include: (a) examining
service connections within the terminal networks for a carrier(s); (b)
Bermuda is British Overseas Territory reliant on the United King-
examining vessel information and trajectories for a vessel(s) and; (c)
dom for protection and assistance. Should the UKMOD need to send
examining marine terminal information.
supplies or materials to the island by sea, options could include:
Similar to how one might use an interactive tool to explore air-
1. deploying a military or merchant vessel from the UK fleet;
ports and flight connections prior to purchasing a ticket for a trip,
2. chartering or contracting of an available vessel from the interna-
SeaCONEX users want to examine marine terminal and ocean car-
tional market; or
rier connections prior to booking carriage of cargo. A user of Sea-
3. using a commercial cargo carrier with existing service.
CONEX should also be able to view the past movements of vessels
There are no regularly scheduled direct UK-Bermuda ocean shipping assigned to a service. This is important because should the vessels
services. All inbound and outbound oceangoing container cargo on a service appear to have historically made unscheduled stops or
between the UK and Bermuda requires transshipment3 in the US. It deviations from an optimal navigation, the user may be interested in
is important for the UKMOD to be aware of all possible options and another carrier/service offering.
connectivity between the Bermuda Territory and the UK.
For example, during the COVID-19 crisis, global disruptions of
6 V ISUALIZATION D ESIGN
all modes of parcel and cargo shipments impacted Bermuda. As a
result, all mail between the UK and Bermuda since May 18, 2020 Figure 1 shows the final design of SeaCONEX as a dashboard
had been sent via ocean container [4]. Bermudians did not start following usability testing and feedback. Our visualization consists
receiving their 2020 Christmas cards until mid-March 2021 [8]. of four linked views: a carrier filter pane, a vessel table, a node-link
In light of this, the UKMOD needs to evaluate commercial ship- diagram (network map), and a geographic map. The dashboard im-
ping options between the UK and Bermuda. 6 ocean carriers, 9 plements the principles of presenting an overview, filtering, brushing
services, 18 deployed vessels, and their network of marine terminals and linking and details on demand. We will discuss the choices for
were identified for the case study, the details of which are summa- each view.
rized in Table 1. For the purpose of the case study, we assume a The carrier filters pane in Figure 1 encodes the logos for ocean
special partner 3PL coordinates freight forwarding, transshipment, carriers companies. On hover, a user is presented with additional
and drayage between US or European terminals. information about the carrier company and its service. Brushing
links to the other views to filter the corresponding marine terminals
4 DATA and vessels by the selected carrier(s).
The vessel table pane in Figure 1 displays vessels in a tabular for-
The data for the case study fell in to two main categories: service mat with each column corresponding to a ship’s attribute. Brushing
related information and vessel movement information. For a com- allows users to view data in the geographic map for the vessel(s) cor-
plete list of the ocean carrier service data sources, pleas from ocean responding historic geographic movements over the 90 day period.
carrier and some industry websites [3, 5–7, 20–23, 26–40, 42, 43].
The node-link diagram pane in Figure 2 represents a directed
The vessel movement data over a 90 day period (December 16, network graph with marine terminals (nodes) as circles and carrier
2020- March 16,2021) was provided by Volpe. All data originated service connections (edges) as lines with arrows. By default, a user
in a variety of formats, requiring cleaning and transformation into may see terminals represented by a white color and all network
JSON and GeoJSON files representing an entity that might exist in connections, albeit in a faded out manner. Hovering over a marine
a database. This format allowed us to statically host the case study terminal displays details such as the terminal’s identifying code, fa-
materials and interactive visualization on a GitHub Pages site. The cility name, address, and the port it belongs to. The hover interaction
entities include vessels, terminals, carrier service networks connec- also brings attention to the terminal of interest by changing the ter-
tions, searoutes representing the shortest route over the sea between minal’s color to deep red and taking advantage of the pop-out effect.
two terminals, and vessel timestamped trajectories representing the The terminal encoding returns to default when the user interaction
spatial temporal movements of vessels. A look-up table entity of id’s focus changes. A selection in the carrier filters pane changes color
and join relationships was also created for filtering, aggregation, and of the associated terminal nodes to a red outline with a pink fill and
linking in our visualization without requiring a back-end server and brings the connections into focus using color highlighting. When in
API. When applicable, our data schema design, relationships, enti- view, the connections are encoded with a blue or orange color rep-
ties, fields, or data types were adapted from industry best practices as resenting a respective East or West trade lane. This is important to
documented by the Digital Container Shipping Association (DCSA), highlight because a carrier may not visit a facility in both directions.
Ship Message Design Group e.V (SMDG), Bureau International des The force-directed node-link diagram is advantageous for showing
Containers et du Transport Intermodal (BIC), and The Intermodal network data because it removes geographic distance and allows the
Association of North America (IANA). For a more detailed descrip- user to focus clearly on specific nodes and edges connections.
tion about each entity and the fields they contain, please refer to our
The geographic map pane in (Figure 3) also displays marine ter-
supplementary materials at https://osf.io/k9nvc/.
minals in the same encoding as the node-link diagram. The terminal
elements here also feature the same interactivity and linking to the
5 TASK A NALYSIS carrier filter. Instead of displaying graph network edges, this view
We interviewed our partners at the Volpe Center to identify shows connections between terminals as the optimal maritime route
domain-specific tasks the visualization should support. During the calculated using the SeaRoute model from the European Union’s
design process, we shared with the partner, example visualization statistical office. These elements are not visible by default and ap-
tools from industry software leaders as well as domain specific con- pear red for a carrier selection. Although these connections may not
cepts from academia. This helped us better understand the client’s be accurate for navigation, they show the shortest distance between
terminal pairings and provide a base comparison against actual ves-
3 Transshipment: The unloading of cargo at a port or point where it is sel movements (trajectories). A vessel table selection links to this
then reloaded, sometimes into another mode of transportation, for transfer to map view and displays the corresponding vessel(s) trajectory for the
a final destination [41] dataset time period. The trajectory for each vessel is encoded with aTable 1: An overview of the six ocean carriers and services chosen for the case study
Carrier Trade Service Vessel Deployment Num. Ports Num. Marine Terminals
Bermuda Container Lines (BCL) Bermuda Oleander (O) 1 ConRo vessel 2 2
Bermuda International Shipping Ltd. (BISL) Bermuda Bermuda Islander (BI) 1 LoLo vessel 2 2
Somers Isles Shipping Ltd. (SISL) Bermuda Somers Isles (SI) 1 LoLo vessel 2 2
Independent Container Line (ICL) Trans-Atlantic Trans-Atlantic (TAC1) 4 LoLo vessels 5 5
Atlantic Container Line (ACL) Trans-Atlantic Atlantic (A) 5 ConRo vessels 8 10
Hapag-Lloyd USA, LLC (HLUS) Trans-Atlantic US Flag Priority 1/Atlantic 3 (P1/AL3) 6 LoLo vessels 8 8
Table 2: Domain task and abstract tasks identified using Brehmer and Munzner’s multi-level task typology [2]
Analytic Task Search Task Analyze Task
Task Domain Task
(low-level) (mid-level) (high-level)
1 Examine carrier, service, and cargo network, connectivity for the case study. analyze produce derive
2 Examine vessel trajectories (continuous movement data) for vessels belonging to a carrier or service rotation. query consume summarize
3 Examine vessel information for vessels belonging to a carrier or service rotation. query consume summarize
4 Examine marine terminal information for facilities within the cargo network of the case study. analyze consume discover
for those unfamiliar with maritime supply chain operations. Users
found the feature of comparing actual vessel trajectories against ideal
shortest routes useful to understand route deviations and slowdowns
in cargo transportation.
On introducing SeaCONEX to domain experts, the feedback
was favorable. They found the interface easy to use and said that
combining vessel movement data with carrier network information
would help them in future analytical work to support the needs of
the UKMOD.
The Volpe team found our data processing techniques and open
source data standard adoption of great interest. They are interested
learning more about the open source tools we utilized and the in-
dustry standards to help them address information interchange with
cargo carriers. Our partner mentioned that our tool provided valu-
able insight as to how they could enhance the visual appeal of their
logistics tracking software.
Figure 2: Node-link visualization of ports and connections
8 D ISCUSSION
The biggest challenge throughout the project was acquiring carrier
data and formatting it into a standard. Additionally, complicated
AIS data quality issues added difficulty to calculating and generating
vessel trajectories for the visualization.
In the future we would like to integrate more details in the vi-
sualization, such as the details for the cargo carrying capacities of
different vessels for a carrier, vessel and port performance metrics,
and highlighting unexpected vessel port calls.
9 C ONCLUSION
We designed SeaCONEX as a tool to allow logisticians to exam-
Figure 3: Map showing shortest and actual routes for ICL vessels ine nodes and edges in commercial maritime networks and evaluate
deployed on the TAC1 service over the 90 day period movement patterns for vessels deployed to the networks. Using the
service, carrier and vessel information, we presented users with a
visualization that combines two major types of data into a unified
view. Further work in this area could be used to address choke-points
different color allowing users can visually compare the actual paths in maritime networks and optimize scheduling and routing of cargo
for vessels assigned to the same service as well as the optimal route. and freight movement. We hope that the ideas presented in this paper
Lastly, we provide a reset button to clear all user selections on will be useful to future logistics researchers trying to make decisions
the page. about how to best present information in this data-rich domain.
7 E VALUATION 10 ACKNOWLEDGEMENTS
To validate our design, we conducted a small-scale usability We would like to thank the team working on the UKMOD project
testing in a class of 25 students in line with the design study “lite“ from the Volpe National Transportation Systems Center, U.S. De-
methodology [47]. This helped us identify bugs, refine our design, partment of Transportation for the opportunity to collaborate this
and arrive at a more polished product for our partner. project. We would also like to thank the students in the course for
Users relayed to the team that they could easily find ports and giving us valuable feedback that helped refine our design.
routes. We also understood that the purpose of the tool is hard to un-
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