1. Cloud, Mobile and Big Data Technologies in Responsible Land Administration Geoffrey C Hay MARCH 2016

2. Technical details Hay, G. C. (2014). Architecture for instrument-centred land administration applications, University of Otago. http://hdl.handle.net/10523/4985 http://hdl.handle.net/10523/4985 Instrument-centred concept relates to:  The translation of domain ‘prescriptive’ instruments into technical implementation.  The implementation of prescribed transaction instruments as integrating workflow processes and the ‘fixing’ of a domain. The architecture relates to the organisation of temporal, semantic, spatial, and process perspectives of information.

3. Introduction  Responsible Land Administration –The goals of LA: social and economic development, address poverty, hunger, tenure security, secondary rights, and the rights of women, children and the vulnerable –with IT systems that are effective, up-to-date, evidential, authentic, inclusive, sustainable, and respectful to land administration and tenure. –That supports and aligns with the ever-changing needs and capabilities of individuals, government and society. –acknowledges differences, variation and the ‘continuum’, and involves all in representation, consultation and participation. –leverages technology to more faithfully represent and maintain the links between people, land, and state.  Mobile devices, and particularly, location aware smart devices support participation and contribution, and a more socially aligned treatment. –Inscription, maintenance and retrieval and potentially definition –Claims can be made regarding land and supported by photos, location information –Counter-claims and assertions –Contributions to knowledge and understanding  Potentially, many other and varied sources of information and many perspectives and models of information. Public and official records as well as automated and machine sources  Issues: –Lies and corruption –Pre existing understanding, or evolving/emerging understanding –Volume, variation and velocity –The link between ‘prescription’ and the development/deployment of IT solutions –Space-Time-Meaning – missing dimensions

4. Vision  For the people: A more socially aligned participative treatment and implementation of LA. –Can property objects and people, and the linkages be organised in a similar fashion to Facebook or LinkedIn? –Can be we move away from predefinition (technological constraints) and acknowledge variation and emergence? –Can the public contribute to the meaning? For the state: The concept of a ‘data infrastructure’, a LA ‘platform’ (PaaS), i.e. LAPaaS. –Can we gain more capability and at the same time reduce the difficulties and costs of developing, deploying and maintaining solutions. –Can we integrate data and services across organisational boundaries (logical centralisation) –Can ideas of sharing and cooperation between states be achieved?

5. Conclusions  The ‘cloud’ technologies provide the basis for a more comprehensive, complete, and ‘responsible’ concept of land ‘administration’ – and the visions of land management and administration ‘as a service platform’, and a social media model of interaction.  Support for evolution and variability, emergence, and volume are the essential technical problems (the problem of ‘fixing’ or predefinition).  Key issue is the ‘model’ –how to represent without ‘fixing’ – temporal/semantic model provides a solution –Cloud aligned model  Processes are where we commit to (fix) specifics  Can ignore issues of storage capacity, processing capacity, while being mindful of complexity

6. What does the “Cloud” solve?  Logical Centralisation of: –Data, processing, meaning, maintenance  Highly available and fast –Less problems of failure,  Highly scalable –Increased load, increased processing load  Unlimited Storage and Processing capacity  Centralisation of infrastructure, platform, software maintenance, –Evolvable and adaptable – with appropriate models –Access to advance services –Integration across datasets and organisational boundaries  Cost is operational expenditure rather than capital –Opportunities for sharing of services, infrastructure, development

7. The ‘missing’ dimensions Aside from the spatial dimension…  Time –Processes –Evolution –Emergence  Meaning –What –Why –Relations, associations  Time and meaning are critical to the faithful representation of a domain and especially to more effective automation, e.g. support for adjudication

8. c StructureProcesses Terminology c Link between prescriptions Rules, parties

9. Methodology and implied architecture Laws, traditions, shared agreed understandings Terminology – Semantic descriptions ( “entities, attributes” only) Structure “schema” Processes “transactions”

10. Append-only strategy for everything  Includes –Instance data (parcels, plots, documents...) –Meta-data (schema, SDI) –Processes (workflows, services, application software!) versioning How to do append-only (non-delete)?  Append-only, Time referenced events that ‘carry’ facts.  Amendments to state (rather than overwrite) facts amend previous facts  Meta-data are also append-only and mirrors the law/agreed understandings  Processes are implemented by ‘workflows’ which interact with humans through task clients  Transactions are (Web) applications that interact with services and humans  Concept of ‘prune’ relating to archiving, authentic destruction. Pruned nodes are proxied. Bi-temporal multi-linear object histories. Identities are made up of temporal attributes. 10

11. Temporal Model e 1 rdf:type core:Event e 1 core:hasProcess p 1 e 1 core:hasIdentity U 1 e 1 core:hasTransactionTime t 1 e 1 core:hasFact f 1 e 1 core:hasFact f 2 e 1 core:hasFact f 3 e 1 core:hasFact f 4 f 1 rdf:type core:Fact f 1 core:hasEvent e 1 f 1 rdf:type core:Immutable f 1 core:hasValidTime t 2 f 1 core:hasIdentityType core:LegalProperty f 2 rdf:type core:Fact f 2 core:hasEvent e 1 f 2 rdf:type core:Immutable f 2 core:hasValidTime t 2 f 2 core:hasBoundary SO 1 f 3 rdf:type core:Fact f 3 core:hasEvent e 1 f 3 rdf:type core:Immutable f 3 core:hasValidTime t 2 f 3 hasLegalDescription “Lot 1” f 4 rdf:type core:Fact f 4 core:hasEvent e 1 f 4 core:hasValidTime t 2 f 4 hasLegalTitle O 1 e 2 rdf:type core:Event e 2 core:hasProcess p 2 e 2 core:hasIdentity U 1 e 2 core:hasTransactionTime t 3 e 2 core:hasFact f 5 f 5 rdf:type core:Fact f 5 core:hasEvent e 2 f 5 core:hasValidTime t 4 f 5 hasLegalTitle O 2 f 5 core:supersedes f 4 Resource Description Framework (RDF) Subject ->Predicate ->Object Extends the concept of the Social Tenure Domain Model (STDM)

12. 12 Architecture

13. Automation in fraud detection, dispute resolution, adjudication, prevention of corruption  Append-only protects data from interference and aligns well with cloud/big data concepts, e.g. replication.  Automated processes as the ONLY means to achieve change – cannot be subverted  Queries and retrieval are also processes  Semantics add meaning to documents and claims. Automated reasoning and inference (consequence) can be used in determination  Big data analytics proven in BI so why not in LA?  Redundancy in data -> truth analysis  Supporting and conflicting ‘claims’ and assertions –LinkedIn, Facebook

14. Linking Open Data cloud diagram 2014, by Max Schmachtenberg, Christian Bizer, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/

15. Valuation Ref: 26760-26101 Rating Valuation: $280,000 Land Area: 0.1297 ha Rating Differential: Residential Land Use: 91 Residential : Single Unit Total Annual Rates: $1,932.48 Valuation Ref: 26760-26102 Rating Valuation: $75,000 Land Area: 0.0688 ha Rating Differential: Residential Land Use: 99 Residential : Vacant Total Annual Rates: $224.33 Open Land Info Thank you.