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Semelhante a Agencies and nonprofits collaborate to improve salmon data access
Semelhante a Agencies and nonprofits collaborate to improve salmon data access (20)
Agencies and nonprofits collaborate to improve salmon data access
- 1. State of the Salmon – Agency Partnerships Initiative (API) Fisheries agencies and nonprofits working together to improve salmon data access
- 2. build knowledge across borders
- 5. is there anything you can do about it?
- 9. timeline 2007 <1 yr planning grant 2008 implementation grant received to start the API (3 agency projects + SalDAWG) 2010 grant period closes
- 14. Coho CUs in Pacific/Yukon 43 CUs
- 20. Salmon Data Access Working Group (SalDAWG)
- 21. Sample – partnership roles and responsibilities
- 23. Sample – partnership roles and responsibilities we each have our own goals for the project and product
- 30. messaging “ Research cannot flourish if data are not preserved and made accessible.” Editorial Nature 461 , 145 (10 September 2009) | doi:10.1038/461145a; Published online 9 September 2009
- 31. messaging investing in a process, not just products
- 34. we gratefully acknowledge the support of the Gordon and Betty Moore Foundation to learn more, contact Cathy State of the Salmon Project Manager 503.467.0791 | [email_address] Photos courtesy of Wild Salmon Center and Ecotrust staff. Do not reproduce.
Notas do Editor
- Hi there. So I saw the theme for this year’s OFWIM conference, “ Doing More With Less: Leveraging Resources and Technology Through Partnerships” and thought, hey, that sounds familiar. I work on a program called State of the Salmon with two nonprofits based in Portland, Oregon and we’ve been doing work along these lines. Today I’d like to introduce our project, the SoS-API, how we got into this type of work, our objectives, introduce the particular projects that are underway, illustrate how the partnerships works in practical terms, and finally, wrap up with some lessons learned to date and how my messaging to funders and leaders has evolved.
- Our program, SoS, works throughout the native distribution range of wild Pacific Salmon – from CA to AK to the RFE and south to Japan. We are consumer of observational field data. Our tag line has been “knowledge across borders” and knowledge in salmon conservation and management is predicated on quantitative data. E.g., if you are opening/closing a salmon gillnet fishery you want to know how many fish have made it upriver to spawn and if that’s enough to maximize sustained yield next year, and so on. So if we got started in 2003 with the intention of synthesizing data from around the North Pacific to a paint a rim-wide picture of status and trends.
- We set out to do our work in 5 easy steps.
- Er, o.k., it didn’t work like that. Now our assumptions and methods weren’t that naïve but we did have a very top-down approach. We ran into A LOT of trouble identifying available data, getting it, and/or ascertaining its utility for our research applications. Result: we weren’t conducting assessments at the rate we envisioned Result: we weren’t delivering on our grant awards in the time/manner originally promised. Result: we were frustrated and our major funder was frustrated
- After several discussions about the challenges we were facing, our program officer asked a simple and fundamental question “ is there anything that can be done to help address data opacity?” We mulled it over and said. . .
- “ Sure,” The feedback we’d always gotten from our agency colleagues is that data mgmt is priority #47 in a list of 50 things to do each day. It’s not that it’s not important, they’d tell us, we just don’t have the resources to throw at it. Why not leverage resources via partnership to build data systems/web tools for agency use?
- So our theory of change morphed into one more viral. Let’s accelerate the rate of change by demonstrating the power of changed data management practices instead of just discussing them. Let’s demo or pilot possible solutions, build test cases, run through a proof of concept, all in ways that facilitate the successful changes being picked up and carried forward by others. Preferably by designing tools and apps that allow one to add code to extend its functionality instead of requiring a full on hack or modification to the original design (not expansion, an extension)
- just: make it suck less
- In 2007 we received a 9 month planning grant to explore the viability of different partnerships and projects. The planning grant was critical. Some project ideas and partnerships flopped. Once we nailed down 3 prospective projects we commenced with an implementation grant. This was received in July ’08 so we’ve been underway with SoS-Agency Partnerships Initiative (API) for just over a year now and the grant period closes at the end of 2010. I’ll next introduce the 4 elements of the initiative: the 3 partnerships and the killer acronym – SalDAWG.
- Perhaps the easiest way to introduce the 3 different agency projects is with an overview of what type of data each are working with. This table shows the projects to the right and indicates which species are included along with what metrics or data types.
- To give you a sense of the kinds of inefficiencies they’re facing, this is a sample work flow that one of the Cordova biologists runs through every time he needs to summarize aerial survey counts. The data are recorded or reprocessed in 5 different mediums. It’s clunky, it’s time-consuming, it’s a pain. So we’re starting with the data capture and query systems and then next look at work flow support tools.
- This slide is a little hard on the eyes but the message is fairly simple: DFO has a new conservation & mgmt policy that is divvying up the landscape into “conservation units” or CUs for every Pacific salmon species (top left and lower right). The WSP directs DFO to track the status of each and every CU using a benchmark framework (seen at top right). A lot of different data are required to establish benchmarks and track the fate of CUs. So we’ve hired a consulting team to pull together the most reliable monitoring activities and, working in close consultation with DFO biologists, develop the methodology and estimates for escapement and harvest rate by CU for the entire region.
- The ODFW project is the most discreet of the 3 with the shortest timeline. The beta version of the web site will be presented at a conference this November in Portland by Jeff Rodgers, the odfw lead. The next few slides are screenshots of the web site to move us from the theoretical and to a real-live product.
- This is the home page where you enter the site by selecting the species or area of interest.
- ODFW has defined 6 conservation criteria for coastal coho and these are reported at several different reporting levels (from population up to ESU). Using google maps you navigate down to the unit of interest. What you see here are those 6 criteria with a snapshot of results for persistence and habitat at a pre-determined scale. If you click on the “view more information” link
- It takes you to a new page with expanded information on that metric. Here we’re looking at adult abundance. The page is cut off but if you were to scroll down there’d be additional info such as a description of the analytical methods used.
- The site also has some basic administrative features so that Jeff and his staff can schedule email reminders to monitoring project staff to update their data in the backend database system.
- Finally, the fourth element of the Initiative is a Salmon Data Access Working Group comprised of people who write things like, “metadata power.”. Actually, it’s a mix of developers, programmers, biologists, and managers. It includes the members of the 3 agency projects plus others doing similar world elsewhere. Meetings once/year during this 3 year grant period, SalDAWg is intended to help the partners i.d. best practices or tools for adoption in the projects while building community to increase standardization and interoperability across borders.
- Thus far I’ve given you a little history of the API and introduced its 4 project areas. At this point, I’d like to shift gears a little and focus on how the partnerships actually work and lessons acquired to date. Up on the screen is an excerpt from the ’08 grant proposal. I crafted a roles and responsibilities outline for each of the projects. This was from ODFW.
- One of the major characteristics of all 3 partnerships is that the agencies or clients are essentially outsourcing the work that needs to be done. I knew going into this that given resource constraints, we’d be taking on the management of grants and contracts.
- But this is a partnership. Unlike a traditional client-contractor scenario, we’re bringing our own expectations and goals to the table, along with the agency. There are vested interests in the outcomes by both parties so the work we agree upon is the work we both agree is important. There are concessions and compromises, which is inevitable when you have several cooks in the kitchen.
- What this means in practice is that we’re jointly conceptualizing the project and we, the ngo, is writing the grant proposals, organizing meetings, working directly with the funder.
- The nature of the relationship and the work also means that these roles and responsibilities change over time. Given it’s not a client-contractor relationship, and we each have unique capacities we bring to the table, any changes to our operating environment (i.e., politics, funding streams, etc) or to the terms of our engagement are, I think, easier to navigate but it does require a little extra time to make decisions.
- Between the planning grant and the implementation grant, I’ve been at this for just over 2 years so I thought I’d throw in some lessons learned to date. If I give this presentation a year from now, I imagine the bulleted points will change a bit but that’s part of the fun. It’s all one big learning curve! These two items are risks in any venture but they consistently stand out in a partnership. Leadership speaks to a number of things: ability to articulate a vision for where the org needs to go and, hence, define a succinct business need, ability to leverage money, staff time and commitment, ability to clearly identify the customers, ability to make things happen. And, of course, there’s always more work to do than there is time. But this can be either exacerbated or ameliorated by a lack of leadership.
- Management entities can be slow to adopt new technologies or new behavior. So it’s pretty important to create low-risk development environments whereby you can learn as you go, you can take time to review and reprioritize, scale back if needed, all without risk of total and complete failure. For example, in the ODFW project, we’re not going to make the kind of inroads on metadata that has been my rallying cry for awhile now but we are going to serve lots of data plus basic visualization tools about the recovery of coho in an organized format for the first time.
- What’s tractable might not be entirely clear until you’re ¼ or ½ way through the project so this is a bit nebulous but the point is, “take small bites and chew well” Customers and stakeholders are different. Customers are the people that decide whether a product is a success or failure. Stakeholders are the people you’d like to also satisfy but they are second tier. Easy example is with ADFG. If the area management biologists don’t use the systems then the whole thing was a bust. If they are using it and it’s helping them and they like it but the area processors aren’t happy with the web interface, it’s a red flag but it doesn’t mean the project failed.
- Regular demonstrations of success are essential. Deliver on showy or instantly satisfying products while continually pushing on the less attention-grabbing but highest priority issue: data management. Invest just enough in slick GUIs to garner the enthusiasm and interest you need from decision-makers in order to garner more funds to re-invest back into managing for the maximum utility of and access to your data. Honestly, because technology changes so rapidly, others such as private companies or nonprofits are often better positioned to create whiz-bang web sites to explore and visualize data. But they can’t build it if the data aren’t there or can’t be understood and that’s the purview of the data producers.
- Because I’m gearing up to write a new grant proposal, I’m thinking a bit about messaging so I thought I’d throw a few slides into the mix along these lines. Of course, the most important reason to steward our data is captured by this quote.
- So if we think of data management as part and parcel of science we can better appreciate that it’s a dynamic, ongoing, iterative, PROCESS. It’s not a situation where you build a new database system and walk away for 2 or 3 years. Technology changes on a rapid basis so you will you have to regularly make decisions about whether you migrate data into new software or steward the old technology as long as possible or give up on the old data entirely. Who’s going to make those decisions?
- Yes, it’s important for biologists to be trained in proper data management and it sure is helpful if database developers understand the nature of the data in their systems but it’s unrealistic, in many cases, to expect to be able to properly collect, analyze, and manage one’s data with say, 250 biologists, and one programmer. It takes a team, preferably representing a variety of disciplines, possibly library scientists, professional information managers, programmers and developers, data technicians, field researchers, as well as the analysts. Probably more staff and types of skillsets than are presently budgeted for.
- And my final soap box message aims straight at the heart of our shared challenge: It’s a big complex world out there and we each face a dizzying array of challenges, imagine if managers didn’t have to find solutions all on their own, within the walls of their organization, imagine the potential of tapping into the imagination and intelligence of people from anywhere in the world. Scientist’s often cite a fear of misuse of their data as a reason to not share their data but on the flip side is the promise of innovation, discovery, and progress. Imagine what’s in the art of the possible if you create open spaces for data sharing and knowledge creation. That’s the kind of risk that can’t be managed for but it comes with the highest rewards. It’s exciting to be working in a very small way towards realizing that possibility.