* 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

Outline

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

Project Background

-  Leisure detecting in Flanders: from prohibited practice (1993) to legitimate hobby (2016)

-  Low reporting rate remains

Source:  Flanders  Heritage  

Project Background

Two major challenges: 1)  Gaining detectorist trust and enthusiasm 2)  Accessibility and usefulness of data for researchers and heritage

managers

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)

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

Human-Centered Design

User panels based on Community Maturity Model (Community Roundtable Network, 2014)

Human-Centered Design

Current State of Progress

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

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)?

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.

Role?

•  modelling knowledge about finds

•  deriving technical requirements for tendering the MEDEA platform

•  monitoring implementation of the data model & the API’s

Data structure

Four main principles •  interoperability •  extensibility

•  accesibility

•  reusability    

Data structure

Use of standards •  ICOM-CIDOC standards

•  CDS Archaeological Sites and Monuments •  ObjectID

•  CIDOC-CRM ontology

•  Implementations •  Arches

•  Ariadne •  finds.org.uk

•  CAI    

Data model

search   find   object   classificaBon  

noBfi-­‐  caBon  

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  

Data model

design

Database system

Neo4j: why? •  native graph database technology

•  open source license

•  well supported web API & query language    

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

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

Demo

Demo

Demo

Demo

Demo

code?