04249nas a2200253 4500008004100000245009000041210006900131260001200200490000600212520350100218653002003719653002003739653001303759100001903772700002003791700002203811700002403833700002503857700001903882700001203901700001703913700002103930856004403951 2020 eng d00aChange in Pictures: Creating best practices in archiving ecological imagery for reuse0 aChange in Pictures Creating best practices in archiving ecologic c09/20200 v43 a

The research data repository of the Environmental Data Initiative (EDI) is building on over 30 years of data curation research and experience in the National Science Foundation-funded US Long-Term Ecological Research (LTER) Network. It provides mature functionalities, well established workflows, and now publishes all ‘long-tail’ environmental data. High quality scientific metadata are enforced through automatic checks against community developed rules and the Ecological Metadata Language (EML) standard. Although the EDI repository is far along in making its data findable, accessible, interoperable, and reusable (FAIR), representatives from EDI and the LTER are developing best practices for the edge cases in environmental data publishing. One of these is the vast amount of imagery taken in the context of ecological research, ranging from wildlife camera traps to plankton imaging systems to aerial photography. Many images are used in biodiversity research for community analyses (e.g., individual counts, species cover, biovolume, productivity), while others are taken to study animal behavior and landscape-level change.

Some examples from the LTER Network include: using photos of a heron colony to measure provisioning rates for chicks (Clarkson and Erwin 2018) or identifying changes in plant cover and functional type through time (Peters et al. 2020). Multi-spectral images are employed to identify prairie species. Underwater photo quads are used to monitor changes in benthic biodiversity (Edmunds 2015). Sosik et al. (2020) used a continuous Imaging FlowCytobot to identify and measure phyto- and microzooplankton. Cameras at McMurdo Dry Valleys assess snow and ice cover on Antarctic lakes allowing estimation of primary production (Myers 2019).

It has been standard practice to publish numerical data extracted from images in EDI; however, the supporting imagery generally has not been made publicly available. Our goal in developing best practices for documenting and archiving these images is for them to be discovered and re-used. Our examples demonstrate several issues. The research questions, and hence, the image subjects are variable. Images frequently come in logical sets of time series. The size of such sets can be large and only some images may be contributed to a dedicated specialized repository. Finally, these images are taken in a larger monitoring context where many other environmental data are collected at the same time and location.

Currently, a typical approach to publishing image data in EDI are packages containing compressed (ZIP or tar) files with the images, a directory manifest with additional image-specific metadata, and a package-level EML metadata file. Images in the compressed archive may be organized within directories with filenames corresponding to treatments, locations, time periods, individuals, or other grouping attributes. Additionally, the directory manifest table has columns for each attribute. Package-level metadata include standard coverage elements (e.g., date, time, location) and sampling methods. This approach of archiving logical ‘sets’ of images reduces the effort of providing metadata for each image when most information would be repeated, but at the expense of not making every image individually searchable. The latter may be overcome if the provided manifest contains standard metadata that would allow searching and automatic integration with other images.

10adata repository10aecological data10ametadata1 aGries, Corinna1 aBeaulieu, Stace1 aBrown, Renée, F.1 aGastil-Buhl, Gastil1 aElmendorf, Sarah, C.1 aHsieh, Hsun-Yi1 aKui, Li1 aMaurer, Greg1 aPorter, John, H. uhttps://biss.pensoft.net/article/59082/02358nas a2200229 4500008004100000022001400041245011300055210006900168260001200237490000600249520163400255100002801889700001901917700001901936700002401955700001601979700001701995700001902012700002002031700002102051856005602072 2015 eng d a2150-892500aFostering ecological data sharing: collaborations in the International Long Term Ecological Research Network0 aFostering ecological data sharing collaborations in the Internat c10/20150 v63 a

The International Long Term Ecological Research (ILTER) Network was established in 1993 and is now composed of thirty-eight national networks representing a diversity of ecosystems around the globe. Data generated by the ILTER Network are valuable for scientists addressing broad spatial and temporal scale research questions, but only if these data can be easily discovered, accessed, and understood. Challenges to publishing ILTER data have included unequal distribution among networks of information management expertise, user-friendly tools, and resources. Language and translation have also been issues. Despite these significant obstacles, ILTER information managers have formed grassroots partnerships and collaborated to provide information management training, adopt a common metadata standard, develop information management tools useful throughout the network, and organize scientist/information manager workshops that encourage scientists to share and integrate data. Throughout this article, we share lessons learned from the successes of these grassroots international partnerships to inform others who wish to collaborate internationally on projects that depend on data sharing entailing similar management challenges.
 

1 aVanderbilt, Kristin, L.1 aLin, Chau-Chin1 aLu, Sheng-Shan1 aKassim, Abd, Rahman1 aHe, Honglin1 aGuo, Xuebing1 aSan Gil, Inigo1 aBlankman, David1 aPorter, John, H. uhttp://www.esajournals.org/doi/10.1890/ES14-00281.1