Presentation given by Pieterjan Deckers of the Vrije Universiteit Brussel at the ARIADNE winter school about MEDEA, an online platform for recording metal-detected finds. The presentation describes the background to the project and its approach.

1. * Foto: Ace Stock
MEDEA
MEDEA: the goals and development
process of an online platform for
recording metal-detected finds data
P. Deckers, B. Lemmens, L. Bleumers,
N. Vanderperren, J. Pierson, D. Tys

2. Outline
1. Background
2. Platform outline and goals
3. Human-Centered Design (HCD)
4. Data model
5. Current state of progress

3. Project Background
- Leisure detecting
in Flanders: from
prohibited
practice (1993) to
legitimate hobby
(2016)
- Low reporting
rate remains
Source:
Flanders
Heritage

4. Project Background
Two major challenges:
1) Gaining detectorist trust and enthusiasm
2) Accessibility and usefulness of data for researchers and heritage
managers

6. Outline of the
Platform
- Crowd-sourcing in heritage:
feedback loop (e.g. Dunn &
Hedges 2013); collaborative, not
just contributory (Shirk et al 2012)
- Open Archaeology: `a
transparently accessible
knowledge base that can be used
for many different scales of
enquiry by many different
audiences' (Beck & Neylon 2012,
494)

7. Human-Centered Design
Key challenges: gaining trust, adapting to priorities and sensibilities
of intended user groups
⇒ Crowd-sourcing in development: ‘co-created’ project through
human-centered design (Steen 2012)
=> Iterative process involving multiple phases of user interaction

8. Human-Centered Design
User panels based on Community Maturity Model
(Community Roundtable Network, 2014)

9. Human-Centered Design

10. Current State of Progress

11. Resources and References
Project repository on CEST (CultureelErfgoedStandaardenToolbox)
https://www.projectcest.be/wiki/Publicatie:MEDEA
Project publications
Ruelens, S., Bleumers, L., Pierson, J., Marchal, C., Deckers, P., Tys, D.,
Lemmens, B., 2015. MEDEA. An online platform for the voluntary recording
of metal-detected finds in Flanders. Report: User requirements and
scenario of the MEDEA platform. Vrije Universiteit Brussel.
Deckers, P., Bleumers, L., Ruelens, S., Lemmens, B., Vanderperren, N.,
Marchal, C., Pierson, J., & Tys, D., 2016. MEDEA: Crowd-Sourcing the
Recording of Metal-Detected Artefacts in Flanders, Open Archaeology 2
(doi:10.1515/opar-­‐2016-­‐0019).
Deckers, P., forthcoming. Legislation, policy and practice of a hobby:
archaeological metal detecting by amateurs in Flanders, in: Campbell, S.,
Thomas, S., White, L. (Eds.), Competing Values in Archaeological Heritage.
Springer.
Contact
pdeckers@vub.ac.be

12. Why
ARIADNE?
• International availability to researchers
• North Sea Area Finds Recording Group
• Portable Antiquities Scheme (England/Wales)
• Portable Antiquities Netherlands
• Digitale Metalldetektorfund (Denmark)
• MEDEA
• Possibility of an intermediate ’portal’ space?
• Make use of/develop common tools (search, visualisations, …)
• How to expose data at more detailed levels (esp. typological)?

13. Acknowledgements
Our advisory board: J. Bungeneers, prof. dr. W. De Clercq, S.
Decraemer, dr. A. Dobat, W. Hantson, dr. M. Lewis, E.
Meylemans, dr. J. Naylor, dr. S. Thomas, prof. dr. J. Van
Heesch.
…and the numerous detector users and archaeologists who
are contributing to the project.

14. Role?
• modelling knowledge about finds
• deriving technical requirements for tendering the MEDEA platform
• monitoring implementation of the data model & the API’s

15. Data structure
Four main principles
• interoperability
• extensibility
• accesibility
• reusability

16. Data structure
Use of standards
• ICOM-CIDOC standards
• CDS Archaeological Sites and Monuments
• ObjectID
• CIDOC-CRM ontology
• Implementations
• Arches
• Ariadne
• finds.org.uk
• CAI

17. Data model
search
find
object
classific
aBon
noBfi-­‐
caBon

18. Data model
search
find
object
collec-­‐
Bon
noBfi-­‐
caBon
dimensions
inscripBons
materials
features
photo
search
area
find
spot
locaBon
publica-­‐
Bon
person
produc-­‐
Bon
Bme-­‐span
type
classifi-­‐
caBon
techniques

19. Data model

20. design

21. Database
system
Neo4j: why?
• native graph database technology
• open source license
• well supported web API & query language

25. evaluation?
• pro:
• data model one-on-one in database >> no normalisation needed
• user-friendly interface
• intuitive query language
• well documented software
• con:
• still complex data model
• still complex queries
• learning curve for developers

26. API?
two REST APIs
• native neo4j API
• use case: complex questions by researchers, using the graph structure
• query language: CYPHER
• data representation: JSON
• simple JSON endpoint:
• use case: simple questions by developers, using ‘flat’ data representation
• query language: MEDEA specific query language
• data representation: flat data for 12 main nodes in the MEDEA data
model

27. Demo

28. Demo

29. Demo

30. Demo

31. Demo

32. code?