Unleashing the potential of collaboration – archaeological detection in the 21st Century
Speakers – Anthony Beck/David Stott Computers, the internet and mobile phones have changed how archaeologists work. More importantly it has changed how everybody can access, use and contribute to archaeology. This has altered public expectations on modes of engagement and resource access. This is resulting in an increased demand for access to this data. This phenomena is not solely about archaeology and heritage but is reflected in many areas of society. Some governments have recognised that taxpayers, as funders of data, should be allowed to access and utilise this data more easily. This has underpinned the Open Data movement. At the same time companies and institutions, like Google and NASA, started making large datasets available on the internet. Some of these organisations provided Application Programming Interface (API's) and other services so that software applications could be built around their data. Such software services made it easier for people to use this data to make new things (derive content) and in turn share these things with their communities. This produced the crowd-sourcing and citizen-science movements. Crowdsoucing is where products, ideas, or content are created by soliciting contributions from a large group of people online. The community mapping system called Open Street Map is a good example of crowdsourcing. Other people want to be more active. Projects like Galaxy Zoo, Ancient Lives and Old Weather have helped free data trapped in books or help scientists collect and analyse data. National Geographic have sponsored a project to help detect archaeological sites in Mongolia using high spatial resolution satellite images (exploration.nationalgeographic.com/mongolia/home). With lots of people working together a big problem can turn into a small problem. These people are 'citizen scientists'. This presentation will describe these movements in more detail and provide examples of their implications for the heritage sector. A vision will then be set out for the future of a collaborative framework for heritage management. This will be framed in the implications it has for practice, engagement, research, curation and policy. Public participation is welcomed!
Recommended
Recommended
More Related Content
Similar to Unleashing the potential of collaboration – archaeological detection in the 21st Century
Similar to Unleashing the potential of collaboration – archaeological detection in the 21st Century (20)
More from DART Project
More from DART Project (20)
Recently uploaded
Recently uploaded (20)
Unleashing the potential of collaboration – archaeological detection in the 21st Century
- 2. Housekeeping – update this • Presentation is available on: – Slideshare:
- 7. Archaeology is led by
- 9. Theories structure this evidence
- 19. The past is a foreign place • Archaeological knowledge acquisition is a dynamic process • Dynamic feedback allows theories/practice to be tested or revised Interpretation Synthesis
- 20. • Primary data – Excavation records – Remote sensing transcriptions – NMP – Lab Analysis – Specialist reports • Decoupled synthetic data – Site reports – SMR – NMR
- 24. Implications of silo-ed data • No synergy • Cripples the knowledge frameworks • Less effective – Research – Impact – Policy – Engagement Interpretation Synthesis X
- 28. Open data
- 33. Make better decision based on the best available evidence.Make better decision based on the best available evidence. >K2 <U2 Known knowns Known unknowns Unknown unknowns
- 35. Open contributions Think of an Open Archaeology Map!
- 44. Open processing - SaaS http://www.earthlook.org/demos/demo_items/wcps.php
- 66. What is the impact on detection
- 70. Where do we want to be?
- 72. Think provision not possession
Editor's Notes
- Understand complex relationships in the fragmented archaeological record Archaeology as human ecology
- Data Rich Data Archiving - Building the silo
- Formal structures inhibit collaboration and access Informal networks established to make the data work effectively
- Additional drops of data/evidence does not affect the structure of the knowledge landscape
- The nature of knowledge From a policy perspective there are different levels of knowledge awareness know what we know (the data we have access to) know there are things we don't know (the relevant data which is not accessible) and recognise there are things that we are unaware of which may be extremely important (the potential knowledge advances gained by integrating all data, collaborating with different domains and future research avenues). Ideally we want to increase the size of the accessible knowledge so that policy can be formed from a position of ‘perfect’, or ‘near-perfect’, knowledge.
- Formal structures inhibit collaboration and access Informal networks established to make the data work effectively