DISCIPLINARY PERSPECTIVE BIOLOGY/ECOLOGY

Workshop on Cyberinfrastructure for Workshop on Cyberinfrastructure for Environmental Research and Environmental Research and

EducationEducation

November 1, 2002

Creating a Unique Beast

WHERE WE COME FROM:Edu. Spatial ecology problemsEdu. Computer scienceCom.Applied IS/information policy/ infrastructure develEdu.Science policy; natural resource assessmentsEdu. Genomics/organismic ecologyEdu. Urban LTER – Data managementEdu. Economist/environmental engineering/industrial ecologyEdu.Org? – data management and modelingOrg – Infrastructure developmentEdu.Org- synthesis and analysis

Explicit Example (short term)Remote sensing satellite data – hard to get and needs ground truthing Share data that provide ground truthing – Make both widely available Requires huge amount of storage, infrastructure

Problems of scale and types of data collection – small scale science combined with large scale remote sensing Add temporal comparison complexity

If we had this, global change issue could be addressed more effectively to include atmo; geo; bio; human and social/economic parameters

Needs of this Integrated/Interdiscipliary Science

Relationship of other disciplines for cross ontological ties (once we work through our own metadata)

Digital libraries are working in this area (coordinate with them)

Need to make a commitment to involve social science researchers working in the b/e domain Vocabularies don’t mesh

Develop a Culture of looking at data as a resource – beyond PI need – repurposingEncourage data publishing policy Share lessons learned – evolving Work with “Publishing Community” to insist on georeferencing Support Progress: Work with ESA -- new Journal – Ecological

Archives

Be more explicit about documenting quality – meaningful for the purpose Develop language for communicating accuracy/explicitness

Definition of digital object - static/dynamic/versioning Composite, extensible metadata standard

Planning for life cycle and future uses of dataData and metadata standards must remain as flexible as possible NSF – in addition to final report should check off that data is deposited (Where? See below)Need for a nationally recognized “repository” system/process – global in concept Models: Genbank

Repository needs sustained support – need to contribute to the concept of a model (including economics) for long term access and preservation of data NSF should provide advice and guidance to PIs

More NeedsDevelop tool to help scientist develop experiment which includes database output in standard structure – make it easy to have scientists accomplish this

Need more of this kind of thing to make it easier to contribute to the infrastructure

Accessiblity to lots of cycles when needed for workbench applications (COTS like SAS, MatLab, Excel)

Explicit example (long term)Ecological forecasting

Species occurrence data –What data sets are needed to take current species distributions and project where they’ll be tomorrow Invasives and spread; human or wildlife disease vectors Communities and change Pattern recognition

Truly spatial approaches to economics of resource managementFederal monitoring $650M/year --- make it possible to leverage this investment by developing tools to analyze it

NSF Needs to have initiative to strategically fill in gap between data of individual research questions

and the bigger integrative questionsIf looking for future predictive capability, need to understand what’s needed for this kind of data, andHelp scientists and others contribute useful dataHow to build the data/knowledge grid so that the big questions can be answered by the sum of many distributed research activities (e.g. Heinz Report) Need both bottom up and top down Needs iterative relationship among research and policy and other

communities Better data practice and explicit commitment towards

standardization

Ontologies of questions can lead to understanding among disciplines and user communities (e.g. policy)

If we know the policy question, can it be disambiguated so that metadata can be generated which can then make it transparent that data are availableCan help drive the more fundamental metadata question – how to anticipate what parameters may be needed and how can metadata evolve even ex post facto to enrich

data set for future other purposes.

Need to work with Social Sciences because the vocabularies are so different

Data Discovery IssuesOnce identified, magnitude of task to actually make them usable for a new analysisCan clarify this through formal metadata Schema discovery, interpretation and translation Covering all the parameters: geospatial scales; temporal;

presevation, etc.

Explore the ultimate implications of how to capture metadata to allow for flexible future useNeed ontologies of the research question to ensure metadata can give the answerBring in socioeconomic context (Biocomplexity program tries)

NSF Program to do More Integrative Research Interdisciplinary proposals which requires CS work teams

to get at large scale ecological questions ITR and BDEI have potential but needs more PR to get to the

community Needs focus on studies that push maturation of b/e science

towards predictivity At the same time, help small field stations (staff of 1.5) or

Joe Q Citizen who wants to do data-collection “right” Need large confederation process Need collaborative tools to allow interactions to take place

(DOE Access Grid as an example) Human dimension component of Biocomplexity call needs

additional emphasis

The impact

Focus this NSF Initiative on New Ways Metadata can contribute to Semantic Interoperability

This in turn will refocus researcher time – if the 70% of time they spend repurposing and interoperating data sets can be reduced by X% ….

The increase in scientific productivity could be very great