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9 gennaio 2020 ENTER2020 – Research Track - Dr. Davide Calvaresi
Semantic Data Models for Hiking Trail
Difﬁculty Assessment
University of Surrey
Jean-Paul Calbimonte, Simone Martin, Davide Calvaresi,
Nancy Zappelaz, and Alexandre Cotting

9 gennaio 2020 ENTER2020 – Research Track - Dr. Davide Calvaresi 2

Hiking - increasingly popular activity
Introduction
infrastructures, technologies, maintenance, information

Hiking - increasingly popular activity
Introduction
infrastructures, technologies, maintenance, information
ACCESSIBLE

Introduction

Contribution
Explore
the semantic data models representing features of hiking trails,
targeting in particular
Obstacles and Difficulties
for specific classes of users
Effort + Technique + Risk
French Hiking Federation classification methodology - https://www.ffrandonnee.fr

Contribution
Explore
the semantic data models representing features of hiking trails,
targeting in particular
Obstacles and Difficulties
for specific classes of users
Effort + Technique + Risk
(e.g., emotions-related)

Hacking Trail Difﬁculties
Understanding of the difficulties linked to the User Perception

previous experiences, background,
fitness level, age, etc

Motor condition, related to specific
equipment, etc

Motor condition, related to specific
equipment, etc
Recipients?
hikers and tourism industry

Trail Difﬁculties Classiﬁcation
P1: Self-assessment
P2: Multi-Criteria evaluation
P3: Effort assessment
P4: Technique assessment
P5: Risk assessment
P6: Profile recommendation
P7: Semantic modeling

Difﬁculties Assessment Model
Effort, Technique, Risk
P1,P2,P3,P4
P5,P6,P7
concepts from

hiking world concepts from

leisure industry

P1,P2,P3,P4
P5,P6,P7
concepts from


leisure industry
Physical activity
(energy)
Motion
(motor tasks)
Psychology
(correlations)

P1,P2,P3,P4
P5,P6,P7
concepts from


leisure industry
French Hiking Federation
classification methodology10
Physical activity
(energy)
Motion
(motor tasks)
Psychology
(correlations)

French Hiking Federation
classification methodology10
Physical activity
(energy)
Motion
(motor tasks)
Psychology
(correlations)

What hiking tracks are available within a given region?
What are the coordinates of a particular hiking track?
What is the total distance of a given hiking track?
What is the accumulated ascents and descents of a given track?
Which interest points are near my current location in this track?
Which tracks require a mild physical effort according to my capability?
Which tracks require advanced technical skills?
Which segments of a given track have steep slopes?
Which tracks have a low-risk difficulty and high-effort difficulty?
Which tracks are similar to a particular hiking trail in terms of overall difficulty?

Semantic Model for Difﬁculty Assessment
Modelling a tourist trip according to schema.org. The standard trip can be used as a starting point for representing a hiking trail, as it
already includes all geographical information, although it lacks specific elements such as slope information, gradient, difficulties, etc.

Modelling a tourist trip according to schema.org. The standard trip can be used as a starting point for representing a hiking trail, as it
already includes all geographical information, although it lacks specific elements such as slope information, gradient, difficulties, etc.

Modelling of a Hiking Track, extending from schema.org. The model includes several technical information regarding the characteristics of the
trail, as extracted from its geographical representation. It also includes detailed slope information and the interest and difficulty points.

Modelling Difficulty points, as extensions to a schema.org Place.
The model includes the main three different types of difficulty, related to
effort, risk, and technique. The model is not strongly linked to any particular
type of calculation, such as the IBP index, and it could use different
types of scores.

Discussion
careful analysis of:
needs, requirements, and perceptions
of the various stakeholders

Discussion
of the various stakeholders regional tourist ofﬁces,
local development authorities,
health professionals,
mountain guides, and
potential hikers

Discussion
Deploy the Model
Feed the Model with data
of the various stakeholders regional tourist ofﬁces,
potential hikers

Discussion
Deploy the Model
seamless mapping:
- users’ health/capability/preferences
- recommended/suggested paths
regional tourist ofﬁces,
potential hikers

Discussion
Deploy the Model
Enhancing the adherence between
hikers’ needs and tourism offers
(reducing risks, increasing of fun, increasing trust)
seamless mapping:
- users’ health/capability/preferences
- recommended/suggested paths
regional tourist ofﬁces,
potential hikers

Discussion
multi-disciplinary and multi-party
interaction
manual vs semi-automated
(CORRECT/VALIDATE) data collection
Building and Training AI models
Matter of business

Conclusions
Subject to any legal implication?
Scaling and spreading the proposed model
Need for personalization based on the real users’ capabilities
Planning a sustainable (manual/semi-automatic) classiﬁcation
Serving the tourism industry with more tailored solutions (exploiting AI/ML)
Base future tourism product on the proposed model and data-format
Identiﬁed and modeled crucial hikers “dimensions”

Questions?
Davide Calvaresi
davide.calvaresi@hevs.ch

9 gennaio 2020 ENTER2020 – Research Track - Dr. Davide Calvaresi25 gennaio 2019 ENTER2019 – Research Track - Dr. Davie Calvaresi 41
Government, Law Institutions
Insurance Providers
E/O/S
Remote Tourism
Agency (origin)
3rd
Party
Tourist(s)
E/O/S
Travel Company
3rd
Party
E/O/S
Local Organization
(destination)
3rd
Party

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Semantic Data Models for Hiking Trail Difficulty Assessment

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Semantic Data Models for Hiking Trail Difficulty Assessment