Development Roadmap

From Salish Sea Wiki

The Development Roadmap describes our speculative long-range vision for the platform. It is organized into three spiraling areas of work: Social Engagement, Archive Integration, and Data Exploration & Mapping. We anticipate that incremental improvement of the platform across these three systems will result in synergy that increases the functions of the platform and its knowledge community over time. This roadmap aims to present a network of interrelated and incremental projects that can engage educational institutions and varied partners in shared work.

Three areas of work:

  • Social Engagement - the platform must include an evolving social process, increasingly integrated into diverse economic, social and cultural events and experiences.
  • Knowledge Recovery - the platform is used to count at multiple pathways of knowledge loss, and to organize a wide range of poorly curated government archives.
  • Data Exploration & Mapping - our ability to create meaning from aggregated data will integrate artificial intelligence, visualization, and integrated use of spatial data.

We are exploring project scopes, funding, partnerships, and creative collaborations across this development roadmap. Projects are presented as opportunities that you might engage through your community or institution. We are specifically designing modular efforts that can engage paid internships so that platform development supports workforce development.

Initial Phase

Work to date has centered on NOAA and WDFW funding and technical assistance programs to experiment with knowledge architecture and data structure. Based on these experiments, we are completing an upgrade in data structure, establishing a management framework, and are ready to begin partner outreach and expand usage (See Development Log).

Second Phase

This second phase of development integrates three areas of development. Social integration work experiments with methods for engaging our community of practice in knowledge co-creation. Knowledge recovery targets specific mechanisms of knowledge loss or stagnation where application of effort increases knowledge flow. Data exploration and mapping creates feedback between social engagement and knowledge recovery to increase awareness of place-based knowledge.

Social Engagement

  1. Retirement Intervention - professional retirement without intentional knowledge management and apprenticeship results in a massive loss of knowledge from the professional community of practice. Individuals leaving the institutional workforce after a long period of service often have sharp reflections on what has changed and what has not, what were important turning points and what remains unresolved. SCOPE: identify a pool of respected professionals at retirement. Used experienced peers to capture long-form video interviews. Use engaged student projects to convert the concepts and materials identified through the interview process into structured wiki content.
  2. Knowledge Hackathons - Knowledge is often organized within a community that doesn't spend time together assessing shared understandings and questions. We can use existing networks (for example Funding System grant programs and PSEMP) to stimulate topical retreats. SCOPE: assemble members within a specific community of practice into a day-long retreats. Train volunteer scribes familiar with development of content using our Style Guide. Complete group discussion punctuated by content development to document collective knowledge and questions. Pre-retreat preparations may improve performance. Develop and improve standard methods for the one-day knowledge hackathons. Spin-off grant proposals for efforts building on the model used in Science Sprints to Support Regulation.
  3. Conference Integration - Professional conferences provide a critical knowledge sharing environment, however they have very poor knowledge synthesis and retention strategies. Existing conferences could be identified as partners to test conference integration methods. SCOPE: train a community of individuals to integrate the presentations and proceedings of a conference into wiki knowledge. Pre-analysis of conference content could be integrated into conference proposal data management and proceedings.
  4. Grant Program Partnerships - funding programs have an exceptional potential to encourage knowledge synthesis through very lightweight requirements integrated into funding agreements. The genesis of the platform was supported by coordination with the ESRP and NOAA funding programs. SCOPE - evaluate knowledge generation among private, state, and federal funding programs, and define a low-cost program integration opportunity. Start with smaller funding organizations that target knowledge creation or culture change and currently broadcast low-quality information to a general audience (for example NFWF or Bullitt Foundation or National Estuary Program).
  5. Social Media Engagement - The talk page functions supported on the mediawiki platform are mismatched to modern social media norms, however the stable evolutionary character of wiki data provide a valuable counterpoint the transient flows of social media streams. SCOPE - find a mission-allied social media platform (for example, Hylo), and develop seamless login (Developers|OAuth Extension) and drive cross traffic between the wiki, into a social media engagement environment to reinforce social engagement strategies.
  6. Social Media Integration - Sharing contributions allows individuals to promote their accomplishments, while driving traffic back to the wiki platform to reinforce the potential for knowledge co-creation. SCOPE - review extensions and establish a seamless social media posting capability from any page, and into key regional professional social media environments.
  7. Market Development - Production of page content is work. Use by readers can indicate the value of that work. Building an incentive system by which producers of valued content could be rewarded in a simple currency could create incentives for knowledge co-creation. External partners could value this currency through a variety of mechanisms. SCOPE - Develop a simple prototype crypto-currency that can be associated with user account activity, and exported into a wallet system. Include a page quality evaluation process, so that contributors to pages may produce future dividends. Evaluate how knowledge organization can be rewarded through funding programs.

Knowledge Recovery

  1. Automated Document Archiving - create seamless mechanisms using existing software for converting an annotated bibliography and a set of PDFs into a curated wiki archive. SCOPE: Adapt Cargo framework and existing page import tools to harvest data from tabular data that includes document links. A user will be able to fill out a table and point to cloud hosted PDFs and efficiently create a set of new pages associated with uploaded documents. This tool can continue to evolve, extracting category options from the wiki to inform the development of the tabular data used to create additional platform entries.
  2. Archive Assessment & Integrated Search - Existing agency repositories may contain several decades of technical work that is otherwise inaccessible. SCOPE: Identify technical ecosystem archives such as the PRISM - RCO Project Information System or the Ecology Document Archive and evaluate their API search potential. Develop mechanisms for crawling and searching these related archives based on title or content. This could dramatically increase accessibility of these existing resources. These content could be used to train LLMs to enable rapid cursory analysis to summarize and identify potential resources buried in agency databases that can be reorganized into place-based knowledge.
  3. Place-based Effort Profiling - the funding system drives definition of two to four year "projects" which undermines understanding of longer-term Landform Scale ecosystem restoration efforts that are typically composed of multiple projects over time (see Standard Conservation Project Description.) SCOPE - identify Landform Scale conservation efforts, and document chronologies, and learning over time that can be applied to similar efforts in other places. Integrate with Grant Program Partnerships and Conference Integration described above. (For example see, Snohomish Estuary chronology.)

Data Exploration and Mapping

  1. Spatial Data Hosting - Place pages are each associated with a polygon that is more or less distinct (see Maps). Enabling the association of spatial polygons with wiki pages, and serving these polygons from the wiki could allow for spatial analysis and presentation of wiki data, as well as intuitive browsing capabilities using maps. SCOPE - establish a simple spatial data standard (likely using GeoJSON) that allows for polygons to the stored and served to mapping platforms as wiki data, where polygons are attributed with Cargo page data.
  2. Initial Mapper Integration - Map-based visualization of wiki place pages is a high priority for increasing the intuitive recognition of the value of a place-based knowledge management system. SCOPE - Aggregate spatial data described in Spatial Data Hosting above, and present on a simple on-line mapping tool that is integrated into wiki pages, and can be used to visualize places using page data (for example with a symbology based on category or the quantity of page content). Increase versatility over time. Increase accessibility of the data service to desktop or web-based mapping system.
  3. Backend Spatial Analysis - An accumulation of spatial data allows for discovery of relationships among places. SCOPE - Using Spatial Data Hosting and Mapper Integration, complete back end spatial analyses and updates, and return those summary data to be stored as place page data (allowing further mapping of relationships and symbolic representation of place attributes). This would result in an increase in graph data (this landform is within this watershed that is near that watershed, and this watershed is like that watershed) that could be used for visualization or automated page linking. Place page polygons can consult existing large data repositories (percent impervious, light pollution, forest cover, stream and shoreline attributes) and generate data that can be represented as data associated with place pages and used for recursive and interactive visualization (see File:Cereghino 2014 DRAFT integrated spatial assessment units.pdf).
  4. Onboard LLM Integration - Government-regulated restoration and regulatory activity develops extremely high volumes of written material, but with poor mechanisms for iteration of synthesis, resulting in a surplus of documents. Large language models provide an alternative to expensive human labor to evaluate and deconstruct concepts and evidence presented in a large volume of documents. SCOPE - develop an online interface for integration of large language models into the wiki platform. Develop the ability to train of the model using constrained sources both on the platform and in adjacent archives (identified by Archive Assessment and Integrated Search above).
  5. Graph Data Development and Visualization - Wiki data are naturally receptive to development of graph data, thorough analysis of categorization and links among pages, including references. As platform content increases, visualization methods provide rapid strategies for making meaning of accumulated information. SCOPE: Use SQL data queries to construct graph data, and experiment with user-driven visualization to enable rapid summary and assessment of data density in different areas of the platform. Augment and compare queries to LLM analyses to identify areas for knowledge synthesis.