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New Frontiers in Mapping Biodiversity Specimen Data Gail E. Kampmeier Illinois Natural History Survey Institute of Natural Resource Sustainability University.

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Presentation on theme: "New Frontiers in Mapping Biodiversity Specimen Data Gail E. Kampmeier Illinois Natural History Survey Institute of Natural Resource Sustainability University."— Presentation transcript:

1 New Frontiers in Mapping Biodiversity Specimen Data Gail E. Kampmeier Illinois Natural History Survey Institute of Natural Resource Sustainability University of Illinois at Urbana-Champaign 7th International Congress of Dipterology Symposium: Getting Diptera taxonomy up-to-date: New frontiers & the Web

2 What Does this Mean for Dipterists?  Short-term goals  Publication  Looking for trends  Where do species exist relative to one another? In geologic time  Finding outliers in your data (data cleaning)  Planning collecting expeditions for fresh specimens  Providing checklists of species  Meeting the terms of a grant or project

3 Long-term Goals  Synergy of combining your data with that of others  Analyze trends with diverse & more comprehensive data sets  Reveal how species respond to environmental changes  Contributes to land management decisions  Indicators of environmental health  Range expansion or extinction  Potential for invasive species  Google, LifeMapper, DesktopGARP, OpenModeler, & Spire: ELVIS  Many other uses  Improve the ease of sharing data

4  Ratified in October 2009, the DwC includes not only descriptive political & geographical terms, but extensive ability to record georeferencing terms  Verbatim  Interpreted  Datum  Uncertainty  Precision  Protocol  Sources  Status Standards: Darwin Core (DwC)

5 Fitness-for-Use  For some applications, data quality may be low (e.g., accurate to the county/province level) but adequate for the scale of the question being asked: Does this species occur in Costa Rica?  However, Does this species occur with this soil type or habitat type? will require more accurate & precise data

6 Data Cleaning Services to Detect, Flag, & Correct Where  Initial data not accurate and/or precise  Misspellings/non-standard abbreviations  Incomplete/ambiguous locality/collecting event descriptions  Errors introduced during data entry  Decimal point misplaced  Wrong hemisphere or doesn’t match locality string  Latitude/Longitude values flipped  Errors converting to decimal lat/long data-errors.html data-errors.html  Geodetic datum unspecified or incorrect from GPS measurements (see why this is important: earth.html) earth.html

7 Why Should We Care? The Issues:  Errors erode confidence in user community  Data errors cause misinterpretation of results when used in analyses  Duplication of effort  Lack of awareness/coordination of efforts  Territoriality of politically-based funding sources  Beta, Demo, Proposed…  Ephemerality of politically-based funding sources  Multistep process  Detecting anomalous data by expanding Temporal coverage Species distribution models; checklists Languages of existing tools, (oeste = west = W = O)  Reporting errors to data provider  Resolving/correcting errors at source

8 Early Tools for Retrospective Georeferencing  Paper gazetteers & maps  Helpful for legacy datasets particularly where political boundaries have changed or entities are not well documented  Require expert knowledge to interpret  Desktop gazetteers – Microsoft Encarta (late 1990’s only) (PC only)  Fuzzy spelling accepted  Would measure displacements

9 Current Tools for Georeferencing  Online Gazetteers  Getty Thesaurus of Geographic Names (TGN)  Annotated lists of gazetteers  Online Mapping  Google Maps  Google Earth  – create albums with photos  Automated Georeferencing  BioGeoMancer Classic & Workbench

10 GEOLocate Parque Nacional Santa Rosa, Liberia, Stor Santa Rosa

11 Georeferencing - Prospective  GPS (Global Positioning System) unit or mobile phone  Taken to the field – calibration errors possible; geodetic datum not set or noted  Single reading taken at start, while collector roams wide area  Specimens mobile or collected in flight  Precision & uncertainty of measurement 30 m uncertainty is considered normal for GPS reading GPS precision for decimal degrees, 0.00001precision  Logging into your database on the go  From iPhone to Filemaker Go

12 GBIF (Global Biodiversity Information Facility)  Best known  Provides leadership & some seed funding to support  Standards development  Global catalog of taxonomic names  Biodiversity data mobilization

13 Label data Record provenance & Taxonomic Name

14 AntWeb in Google Earth Community showcase Only ants

15 Atlas of Living Australia (ALA)  Public launch of their geospatial portal planned for October 2010  Environmental & contextual data linked to georeferenced specimens & observations 250 layers from the Australian Environmental GIS library Partnering with ERIN (Environmental Resources Information Network) Australia was pioneer in digitizing its collections, convincing politicians of the economic sense of linking the museum holdings

16  Audience for ALA is very broad, hope to answer Where is this thing? What things occur in this area – with 6 different ways to define “area”  Will exist in the cloud  Will include links to Biodiversity Heritage Library (BHL) Citizen science Video images Keys DNA – Dan Faith’s phylogenetic diversity  Will have Creative Commons licensing From Skype with Lee Belbin, ALA Geospatial Team Leader; misinterpretations derived are my own. --gk

17 Is the Future in the Cloud? J.A. Olson (2010) Data as a Service: Are we in the clouds?  Daas (Data as a Service)  Clearinghouse style environment – remote data storage & maintenance usually provided by companies – generally less useful to biodiversity community except for archiving  Biodiversity community might use US Geological Survey & statewide GIS clearinghouses that provide downloadable mapping layers

18 Crowd Sourcing in the Cloud  Collaborative projects where all participants can see, use, & contribute data  “Most crowd-based projects are more likely to be locally created and have details and features that commercial data sets do not have. They can be created by groups within a government agency, or groups of researchers, or even a combination of these from around the world working on a project together. Large or small, I believe that crowd sourcing will become the mainstream of scholarship in the near future.” J.A. Olson  Caveat: What happens when it rains?

19 VertNet: Vertebrate Biodiversity Data in the Cloud  Combines global networked information systems for  Mammals - MaNIS  Birds – ORNIS  Amphibians & Reptiles – HerpNET  Fishes – FishNet 2  Working with GBIF to enhance biodiversity data mobilization  Seen a shift from skepticism to enthusiasm for data sharing  Networks facilitate access & sharing of data contributors, who are the primary & authoritative source for information over which they have custody  Incentives: Improve data quality Sharing the task of converting textual locality descriptions into formats for mapping

20 VertNet: A New Model in the Cloud  Consolidating services utilizing Google App Engine  Contributors will use a web-based administrative interface to create a provider in the cloud  More scalable, responsive, & sustainable than traditionally maintained contributor server installations  Estimated 16-fold reduction in annual operating costs  Not yet live

21 DiscoverLife: Operates as a Cloud  John Pickering asks “Why try to get taxonomists to spend their time conforming to standards?”  Artificial Language processor has “standards”  ~40 routines run on data, including language recognition  Upload a file, send a CD or an email attachment or point to access your data as Excel® ASCII, tab- delimited text, UTF-8, or with entity codes  Will work with data providers to improve accuracy  Will send data to GBIF at request of provider  already maps all of GBIF’s data through an MOU*)  Funded in part through NBII**  Maps 22K points/sec; tested with >3M points * Memorandum of Understanding; ** National Biological Information Infrastructure

22 Mapping Multiple Species

23 Access to Specific Records

24 Using Discover Life’s Albums

25 Map your records & see details

26 Techie Solutions for Mapping  Using Google Spreadsheets with Google Maps for Flash (via Yahoo Pipes ) google.html google.html  Google Earth Spreadsheet Mapper  DIVA-GIS  FOSS4G (Free & Open Source Software for Geospatial) conference – resources, talks, etc. from 2009  ArcGIS Online  World Wind Java SDK  Comparison of selected web map services  Biodivertido

27 In Which Direction Should the Diptera Community Head?  Assume that the following are desired:  Sharing Able to map multiple taxa Restrict datasets mapped  Ease of use  Data cleaning & reporting  Attribution of data provenance  Links to community assets such as keys, photos/images  Speed of access

28 References & Resources  Chapman, A.D. & J. Wieczorek, eds. (2006) Guide to practices for georeferencing  Georeferencing & GIS Resources  BioGeomancer  Constable, et al. (2010) VertNet: A new model for biodiversity data sharing. PLoS Biology 8(2):e1000309  Integrated Publishing Toolkit (IPT) software/ipt/ software/ipt/  DiscoverLife  Boakes, E.H. et al. (2010). Distorted views of biodiversity: Spatial and temporal bias in species occurrence data. PLoS Biology 8(6):e1000385  European Commission INSPIRE Geoportal http://www.inspire- http://www.inspire-

29 References & Resources  Hill A.W., J. Otegui, A.H. Ariño, & R.P Guralnick (2010). Future directions and recommendations for enhancing fitness-for-use across the GBIF network. Copenhagen: Global Biodiversity Information Facility. 29 pp. anticipated resources/download-publications/bookelets/ resources/download-publications/bookelets/  Georeferencing Workshops (presentations, videos, exercises)  Chapman, A.D. (2005). Principles of Data Quality, version 1. Copenhagen: Global Biodiversity Information Facility. 58 pp.  Olson (2010) Data as a service: Are we in the clouds? Journal of Map & Geography Libraries, 6(1): 76-78. =linking =linking  Hutchison, R.L. (2008) Table of lat/long equivalents in km & miles

30 Muchissimas Gracias a…  Arturo Ariño, GBIF DIGIT Work Area Chair, for permitting me to view a late draft of a GBIF position paper on fitness- for-use  Lee Belbin, ALA Geospatial Team Leader, for sharing insights into directions for the Atlas of Living Australia  John Pickering, of, for providing a renegade perspective for getting the job done

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