Most data that is generated out of science is not intended to be used on broader scale problems outside of their own research or their own specific domain. Let’s stick with geoscience to check this ‘hypothesis’ out and check on the ‘so what?’ factor.
Current grant and programmatic funding models are not designed to develop shared services or interoperable data for the geosciences. There are few true shared services that are managed and extended to the community as products and services should be. “We broadly estimate that 20% of users of a dataset might be experts in the field for which it was created, while 80% might be others.” There is currently limited to no incentive for most geoscientists to think beyond immediate needs. “The culture of collaborative Science is just being established.” Finally, there is no current clear way to build and sustain the large and diverse geosciences community.
The key we believe starts not with the tech, the money, the management, the govnernance, but with stakeholder alignment which can be “the extent to which interdependent stakeholder orient and connect with one another to advance their separate and shared interests”.
The Geoscientist community – Big Head and Long Tail. Geoscientists with affiliated government institutions, academic and international partners. Data Scientists, Data and Information Stewards, Curators and Administrators (content and metadata), Data Product and Service Managers , Citizen Earth Science participants, Emerging Geoscientists found in the STEM community – (K-12)
Additionally, the supply chain roles from:
- Data and Information Suppliers – NSF funded centers and systems. Programmatic producers of geoscience related data and information – i.e. Earth Observation systems like Landsat or MODIS or specialized information systems that produce value added products like NAWQA. Indonesia NSDI, DOI Authoritative data sources and services
- Cyber Infrastructure community/Development Collaborators – Basic and Applied Research and Development, Software and System Engineers, Data Manager and Analysts
- Infrastructure Management /Collaborators – IT Service Management (ITSM) – Managers and Operators of the shared infrastructure and key software services in industry, commercial, government, Research, and Cost-Sharing FFRDCs
- Consumers reached out to via end user workshops., Public Policy, Regulatory, Legal and Administrative Analysts, Private Sector , Academia (non-participating state), Other science disciplines
- Executive Sponsorship and Geoscience Various and Cross-Cutting Governance Community too numerous to get into in this blog at least
The stakeholder themes we have seen in data are generally the same.
These challenge echoes the organizing themes of the Xentity supported developing 7-years ago for DOI Geospatial Services Architecture:
- “I know the information exists, but I can’t find it or access it conveniently”, has its analog in “Considerable difficulties exist in finding and accessing data that already exists”
- “I don’t know who else I could be working with or who has the same needs”, has its analog in “Duplication of efforts across directorates and disciplines, disconnect between data and science; data graveyard –useless collection of data…”
- “If I can find it, can I trust it?”, has its analog in “There is a need to evaluate consistency /accuracy of existing data.
A start on this, to jump into boring consulting theory, is to Develop a clear line of sight to address stakeholder needs and community objectives.
This ensures the analysis engages all the necessary dimensions and relationships within the architecture. Without a strategy like this, good solutions, business or technical, often suffer from lack of adoption or have unintended consequences and introduce unwanted constraints. The reason for this is the lack of alignment. Technology innovators tend not to share the same view of what is beneficial nor does the Geoscientist who is accustomed to enabling a single or small set of technology directives.
How does one create the shared enterprise view? Using the Line of Sight, our approach at least to architecture transformation and analysis creates the framework and operating model. It connects business drivers, objectives, stakeholders, products and services, data assets, systems, models, services, components and technologies. Once the linkages have been established, the team will create the conceptual design using 40-50 geoscience domain investment areas. This will effectively describe the capabilities of the existing IT portfolio. The architecture and the portfolio will be designed to support governance, future transition planning.
Sample Ecosystem Edge Analysis
Human Edges (adaptive systems)
Data and Information Edges
Computing and Infrastructure Edges
Citizen scientists/ STEM and Professional scientists
Data Supply and Information Product/Services
Centralization and federation of computing infrastructure
Geoscience as consumer and producer of data and information
Possessing the data and access the data
Commodity Computing vs. Analytical Computing
Individual science and collaborative science
Macro Scale data vs. Micro Scale data
Mission driven systems and shared services access
Science Ideation: Piecemeal or segmented vs. holistic
Five data dimensions – spatial (x,y,z), temporal and scale
Domain Systems vs. Interoperability Frameworks
Individual vs. Collective Impact and credit
Authoritative sources vs. free for all data
Systems vs. Managed Services
Governance rigidity and flexibility
Data and models vs. Product
Big Head and Systematic Data Collection, vs. project components
Earth Science and Cyber-infrastructure and Engineering
Long Tail vs. Big Head Data
The Line of Sight allows for exploring the complexities of geoscientist “ecosystem edges” and architect for greater interaction and production in the geosciences. Those in the “Long Tail” encounter the same cross domain access, interoperability, management barriers as the “Big Head”. Neither have the incentive to develop common enabling data interoperability services, scalable incentive solutions, common planning approaches or increase the participation of the earth science community. Xentity’s believes architecture is an enabling design service. It is used to empower the user community with the tools to expand its capacities. In this case, Xentity will provide the operating model and architecture framework in a conceptual design to bring together the currently unattended edges. In the long run, the models will provide the emerging governance system the tools to develop investments strategies for new and legacy capabilities.
The Broader Impact
At its core, we believe the geoscience integration challenge is to exploit the benefits and possibilities of the current and future geoscience “ecosystems edge effect”. In the ecosystem metaphor, the conceptual design approach will target the boundary zones lying between the habitats of the various geoscience disciplines and systems. What is needed is an operating model, architectural framework and governance system that can understand the complexities of a geoscientist shared environment and successfully induce the “edge effect”. It needs to balance the well performing aspects of the existing ecosystem with new “edges” to generate greater dynamism and diversification for all geosciences.
An Operating Model example: Collaborative geoscience planning could make a good demonstration case for the benefits of the “edge effect”. A lot of science efforts are driven by large scale programs or individual research groups who have very little knowledge of who else may be working in the same environmental zones, geographies or even on related topics. A shared planning service could put disparate projects into known time, location and subject contexts and accelerate cross domain project resource savings and develop the resulting interdisciplinary cross pollination required to understand the earth’s systems. An Enterprise geoscience initiative could provide a marketplace for geoscientist to shop around for collaborative opportunities. The plans can be exposed in a market place to other resources like citizen scientists or STEM institutions. The work can be decomposed so that environments like Amazon’s Mechanical Turk can post, track and monitor, distributed tasks.
By recognizing these edges, the architecture will create greater value or energy from the disciplines and improve the creativity, strength and diversity of ideas, and mitigate disruption. The ecosystem-like design that balances the Big Head with the Long Tail will enable more cost effective geoscience projects and create a higher return on IT investments while collapsing the time to conduct quality impactful science. Most importantly, this will accelerate the realization of the sciences’ impact on other dependent scientific initiatives or time to develop and implement policy. Xentity sees the potential to use this and other “ecosystem edges” to transform how geoscience is currently conducted.
Xentity believes a geoscientist, emerging (STEM) or emeritus would be willing to participate in cross-cutting, shared service model based on how well these edges are architected and governed. If designed and operated effectively, the edges will create an environment that will address the two key barriers to adoption: trust and value. In essence, we see the scientists as consumers and producers.
- As consumers of data, information and knowledge products and technology services, they are continuously looking to create more knowledge and contribute to social benefit.
- As producers they contribute data, information and knowledge back into their colleagues’ knowledge processes.
In fact, the predominant challenge for such an approach is that the share-service will be develoepd by the community who themselves are a consumer. Just like any other consumer, they will have expectations when they purchase or use a product or a service. If one cannot uphold the terms and conditions of product quality or a service agreement; you lose the consumer. So, how does the architecture ensure these “edges” develop and evolve? It must ensure:
How to earn Geoscientists’ Trust:
The scientists need to know that they will have highly reliable technical services and authoritative data that are available and perform well when they request them. Most importantly, they will need to influence and control who and how they conduct the work within the shared environment. They need to ensure the quality of the science and appropriate credit.
How to demonstrate the value to the Geoscientist:
The scientists need the provider to correct products or services that will eliminate the most significant barriers and constraints to doing more and higher quality science – research, analysis and experimentation – with less effort.
In the short term, the shared service challenge is to earn the scientists trust and identify the optimal suite of products and services to provision value from the “community resources” as defined in Layered Architecture. For land elevation products up to 80% of the requests are for standardized products. If done correctly, the governance system, operating model and architecture framework will develop the trust and value recognition from the shared community. In the longer term, the models and framework will guide the redirection of its limited resources towards an interoperable set of systems, processes and data.
Great, but even if we create this, how do we fund?
See the next part on “Will geoscience go for a shared service environment” which discusses ways to address funding, ways to engage, encourage, enable, and support execution of these enterprise capabilities for geoscientists.