Case studies of ecological integrative information systems: The Luquillo and Sevilleta Information Management Systems

Transcription

1 Case studies of ecological integrative information systems: The Luquillo and Sevilleta Information Management Systems Inigo San Gil 1,1, Marshall White 1, Eda Melendez 2 and Kristin Vanderbilt 3 1 LTER Network Office, University of New Mexico, Albuquerque, NM USA 2 Luquillo Experimental Forest LTER, University of Puerto Rico, Rio Piedras, Puerto Rico 3 Sevilleta LTER, University of New Mexico, Albuquerque, NM USA, {isangil,mwhite,emeledez,vanderbi}@lternet.edu Abstract. The thirty-year-old United States Long Term Ecological Research Network has developed extensive metadata to document their scientific data. Standard and interoperable metadata is a core component of the data-driven analytical solutions developed by this research network Content management systems offer an affordable solution for rapid deployment of metadata centered information management systems. We developed a customized integrative metadata management system based on the Drupal content management system technology. Building on knowledge and experience with the Sevilleta and Luquillo Long Term Ecological Research sites, we successfully deployed the first two medium-scale customized prototypes. In this paper, we describe the vision behind our Drupal based information management instances, and list the features offered through these Drupal based systems. We also outline the plans to expand the information services offered through these metadata centered management systems. We will conclude with the growing list of participants deploying similar instances. Keywords: Metadata Management Sytem, Metadata Editor, Drupal Content Management System 1 Corresponding author

2 1 Introduction Ecologists aware of scientific data preservation practices have been seeking optimal tools to generate quality metadata. Good data documentation is critical for data preservation and data discovery [1]. Structured, standardized metadata facilitates the advancement of science by enabling rapid data integration and synthesis. In this paper we present a set of tools to create, edit and manage metadata. The National Biological Information Infrastructure (NBII) [2],[3], is a US Geological Survey program whose mission is to facilitate the access and use of the biological information. The NBII supports metadata initiatives by providing metadata training services [4] as well as sponsoring initiatives to create new metadata editing tools [5]. There are a number of standalone tools to generate metadata for individual users and organizations, but these tools often fall short of community expectations. Users attending NBII-sponsored usability sessions and other feedback mechanisms reported problems including confusing interfaces, unstable applications and a perceived lack of benefit. Overall, a representative perception is that the process of creating metadata consumes too much time. Representatives for the Long Term Ecological Research Network program, the Arizona Hydrological Information System [6], the Oak Ridge National Laboratory Mercury Consortium [7] and the NBII program teamed up in 2006 to produce a set of design guidelines for a better metadata entry tool and editor. The resulting editor tool [5] addressed most of the design requirements, but the early adopters found it difficult to use. These new considerations led the authors to develop a more integrative and simpler editing tool integrated in the Drupal content management system [8]. The task of generating standardized metadata should be integrated in the task of generating metadata. The Drupal based system presented in this paper saves the information manager or investigator the extra step of using a stand alone editor to make the metadata comply with the rules of common metadata specification. In addition, this editor is also oriented to those users looking for a feature rich web-based editor. This paper presents the metadata tools and systems developed using the Drupal CMS technology. We use two case studies to describe the details and early reports of the functionality of the system. Highlights of this free open-source Drupal content management system include: fast and easy implementation, customization, maintenance and use. Other important system design requirements include a built-in relational model and semantic mediation for the information content. We implemented this information management system at two Long term Ecological Network (LTER) sites and made it freely available to the ecological research community. About LTER. The LTER Network is comprised of 26 research sites located in the United States, Puerto Rico, Antarctica, and Oceania. The LTER developed a metadata program to document and preserve their long-term scientific data. [9],[10]. The LTER network has an international counterpart organization (the ILTER) with forty member networks representing as many countries. To facilitate exchange of information within and outside the network, the ILTER has adopted metadata policies and standards. However, financial resources devoted to metadata management at

3 ILTER research sites are frequently insufficient. Each US-LTER site should have a full-time information manager. The information manager ensures that all scientific information related to the station is preserved, well organized and accessible to all personnel. Usually, this person or team also manages the information that is made available to the public in general. Often these human resources are stretched thin, resulting in delays and gaps in the metadata program [11]. LTER heeds their own metadata mandate [12], offering to the public over 7,000 studies in a metadata specification commonly used in ecology. Outside the LTER, however, we do not always see structured metadata in the biology and ecology disciplines: metadata is often either absent or minimal and non-conforming to any known common specification. More on NBII. The NBII program started in 1993 [2] as a collaborative program to facilitate information on biological resources, including scientific data. The NBII links databases, information and tools originated from NBII partners. NBII collaborators work on data and metadata standards, tools, and technologies that make it easier to use and integrate biological resources. Paper outline. The paper is outlined in three more sections. In section 2, we explain our vision for a successful ecological information management system, including our motivation and experiences with several information managers in the field. In Section 3, we explain the system architecture, starting from broad considerations about the Drupal content management system to the specific customizations to the information management needs of the ecological research stations at LTER. We discuss the first two implementations and case studies of this system in section 4. We conclude the paper with a discussion about the current work, our next clients, our partners and future outlook. 2 A Vision for an integrated metadata management system. The envisioned Information Management System provides a service for ecological researchers as well as the public in general. The information packaging duality is attained by creating different levels of detail for the information served. For example, high level descriptions of research projects and research locations may be appropriate for the public while extensive technical descriptions of data methodologies may be more appropriate for those who use the ecological data collected at field stations and LTER sites. We surveyed the categories used to classify and serve information through the 26 LTER websites. We found that the most recurring categories of information include: Scientific Data, Publications, Research Project, Personnel Directory, Sites, Facilities, News, Maps, History, Educational Activities, Outreach Activities and Informatics. There are other information categories, but the aforementioned categories are the most observed at the LTER sites. These information categories are interrelated: A photo gallery contains visual information about research sites and personnel; a research project is related to its scientific data, publications, people and research

4 maps. The news category contains articles related to people, outreach efforts and educational activities. Metadata includes information about data, people involved in the data lifecycle, research projects, maps, publications and research sites. Figure 1 illustrates some of the information categories used to classify information at most US LTER sites, as well as the subset that comprises metadata. Fig 1. The figure shows the most common categories of information found while surveying twenty six LTER websites. The most common categories are represented by a larger font, while other less popular groupings have smaller fonts. The shaded ellipse encircles the categories that constitute metadata. Our goal is to integrate the metadata management process in the broader information lifecycle, avoiding duplicating the metadata work. We wanted to simplify the data documentation process. Instead of using a standard-compliant standalone editor, we save effort and avoid further errors by having the local information management system output standard compliant metadata. However, the task of creating a universal adapter for each custom information management system would be very expensive. Instead, we focus on offering an easy to use information management system that also generates standard-compliant metadata. This Drupal based system allows the manager to create custom views of the information without specific programming or web-skills. Drupal relates all the information categories outlined above. Drupal also excels at serving information on the web. We are able to easily contextualize unsolicited information to the main content displayed, enhancing the experience of the visitor. For example, if a web visitor is visualizing a research project, the system volunteers the top five data sets produced under the research project, the relevant personnel and publications. The system allows simple content tagging, thus enabling additional content relationships. We offer the web visitor content that is directly related to the main display (research

5 project has data, has publications, has people) and also other content related through the tagging process. Related Work. There are many current developments that are either directly related to this effort or are similar conceptual models. We already pointed out Aguilar s editor [5] as a precursor of this work. Aguilar s choice of technology, a mashup of Orbeon [13] and Java that runs in a servlet container such as Tomcat [14] proved too much for wide adoption and further refinement. The standalone editors such as Metavist [15] and Morpho [16] were used as guiding principles. Perhaps the OBFS dataset registry tool [17], a web form that enables basic documentation of a data set, is the closest precursor in the sense that it is a web based integrative metadata tool. There are a number of synergistic efforts. The U.S. Geoscience Information Network group has developed a Drupal based metadata editor for basic metadata (ref), offering the content in ISO [18],[19] compliant reports. Also, the US National Phenology Network [20] has developed a set of forms to capture the phenophases of plants and other living animals. The front end of the application uses Drupal, while the forms use a java framework. The rest of the metadata and information is shared by the primary US-NPN website. Spain-based Grupo de Ecología Terrestre developed an integrated information management system called Linaria [21] that serves structured metadata from the system. The biological station at the University of Michigan also uses a Drupal based modified version of our model [22], highlighting the adaptability of the system to customizations and user needs. The wind energy group at the Oak Ridge National Laboratory (ORNL) has developed a set of metadata capture forms based on our work[23]. The outreach efforts sponsored by the NBII gave way to collaborations with the National Phenology Network, The United States Virtual Herbarium, the Spain Long Term Socio-Ecological Research Network, the Finnish Socio-Ecological Research Network and the Long Term Ecological Research Network in Taiwan. These groups have also benefited from our vision or technology, while we have been able to improve the Drupal implementation. Another remarkable Drupal based effort in ecology, and specifically, in biodiversity are the Encyclopedia of Life s modules for biodiversity information management [24] are a reference for information managers in ecology. Particularly interesting are EOL s tools for metadata management in ISO. Another Encyclopedia of Life product that uses Drupal as its platform is LifeDesks [25]. We plan to use some of the species pages and taxonomies used, as well as some optimization modules that will provide a low-cost, value added features to the work we are presenting in this paper. 3 System architecture In this section we cover the customizations made to manage ecological metadata and other common ecological information. Since our system is based on the Drupal framework, we describe first the basics of the Drupal model, then we describe the customizations made in order to make a information management system for use in biological stations.

6 Why Drupal? At the time when we started implementing the vision outlined in section 2, Drupal was the only content management system that had all the following characteristics: Open source, substantial community adoption and support. Drupal also has a growing community of developers and adopters [26]. Drupal was the only content management system that easily allows the user to work with the architecture. We found Drupal to be flexible to adapt the architecture to the data model and customer needs. This means that we did not lose any of the Drupal functionality while we adapted the relational database to our needs. We were able to customize from the database to webform and views with adequate granularity for the information categories. Other CMSs have many virtues, and in some aspects may surpass Drupal, but we valued the system s flexibility. 3.1 The Drupal framework The Drupal content management system is a product that can run on top of Apache [27], Microsoft s IIS web server [28] or other web servers. The code base is PHP [29], with some Javascript [30] additions. Most Drupal instances use MySQL [31] as the backend relational database, however PostgreSQL[32] can be used too. Drupal is a well adopted open source content management system, with well over half a million websites powered by Drupal [33], or 1% of the internet share. The initial install comprises four simple steps that are clearly documented. With all prerequisites running, an initial complete install can be completed in about five minutes. To the Drupal community, a node refers to a record in a content-bearing table of the database. Tables that contain information may represent a webpage, a story, an article, a blog post, a photo. Drupal provides all information types the same underlying structure. Any application developed for a specific information type may be leveraged by all the information types in Drupal. This fosters information integration. Drupal node-centric structure makes the developer s work relevant system wide. In Drupal, the different types of tables are referred to as Content Types, I.e: Content Types are categories of information groups or containers for a specific category of information. For example, the Content Type Research Site may encompass a site description, latitude and longitude and site elevation. Nodes stored in content types can be linked to each other. For example, a node in the content type research project may contain several nodes in the content type data set. This is relational database design which can be directly inspected in the underlying MySQL database. The look and feel of the front end application (the website face) is easily customizable through custom Themes. Drupal themes are the layouts that structure the content on the web application. A user can change the look and feel by clicking twice. There are hundreds of themes available for use [34]. Maintaining this information system up-to-date will be easier: The only tool required is an internet browser. Also, separation of content, organization and layout allows planning for independent modifications of the look and feel and the content quantity and quality. Almost all the Drupal operations are conducted using a web browser (I.e; Firefox, Internet Explorer, Chrome, etc.). Drupal s core is maintained by the Drupal team [33].

7 There are many extra features that extend the basic functionality through the addition of modules. A distributed community of developers release these modules and themes using programming guidelines, principles and open source philosophy. The Drupal web site structures all these custom modules and themes at Customizing Drupal Currently, our LTER Drupal group uses many extensions to the core and has developed custom content types for personnel, research site, research project, metadata for dataset with data table and attribute types. We also benefit from optimized modules that manage bibliographies, image galleries and videos developed by the Drupal community. Using extended functionality it is possible to serve content in the extensible markup language (XML)[35]. Using Perl [36] and XSLT [37] transformations, we provide Ecological Metadata Language [38] and Biological Data Profile [39] compliant metadata. We can serve the content as PDF, Excel spreadsheets, Word documents, and other commonly used formats. Our group uses the Views module extensively. The Views module allows us to offer the content in many user friendly and intuitive layouts. The views module is nothing but a GUI into the creation of structure query language (SQL) queries, coupled with the actual final web layout. In the same GUI interface we configure the queries (fields, filters, arguments, relations), the layout (the style, pagination) and the display (access, sorting). Other interesting features are security (SSL encryption, captchas and enhanced logs), user management, LDAP connectivity and RSS feeds. The latest stable version of Drupal (Drupal 6.*) provides its adopters with taxonomies for semantic mediation. Drupal taxonomies are families of keywords. These keywords may be free form or may come from a controlled vocabulary. The keywords may be structured hierarchically, conferring some further structure to a vocabulary list. These keywords can be used to tag content, forging relationships between otherwise disconnected information. In summary, the content types are repositories of information customized to the categories managed by the group. Creating a custom content type in Drupal is fairly simple. Each content type includes a configurable input form to capture and edit the information that it holds. Figure 2 shows a subset of Drupal ER diagrams for the metadata tables.

8 Fig 2. A simplified data diagram that includes most of the metadata related tables. Most of the Drupal core tables have been excluded from this diagram, except for the master table "node", in the upper right area. The tables shown in Figure 2 are related to ecological metadata management. The areas in the figure represent the information categories discussed: A personnel directory, whose main table is titled content_type_person. The basic metadata area, whose main table is titled content_type_data_set. The structure of the tabular data entities area (content_type_data_file). The georeference area, whose main table is the content_type_research_site. The variable area, whose main table is titled content_type_variable. The tables that have the prefix content_field are dependent on the content types. These tables hold information for the one-to-many relationships to their parent tables. There are keys inside those tables to index the multiplicity on the relations.

9 In Figure 3, we show a diagram that expresses the metadata content types or information categories as implemented in Drupal custom content types and their relationships. Note the many to many relationships as well as the one to many relations. Fig. 3. The seven Drupal custom content types used to document ecological data and their relationships. Each content type may represent one or more tables in the Drupal relational database. All content is related at the record or node level. In order to represent the most common categories of information, we have created seven content types: 1. The basic unit refers to an observable. We classify observables in three types: a physical, quantifiable measurement, a date or a set of codes. This classification avoids complexities noted by many [40]. Variables can be described using the associated web form. The web form (see figure 4) has three tabs corresponding to the types mentioned (physical measurement, dates and codes). 2. The data file structure describes the physical details of the data container, usually a spreadsheet or a database view output. Details such as the column separator, number of header or footer lines, file name and link to the actual data are among the information that the user can input in the associated, multi-tab web form. 3. The research site describes the location where data is gathered. Latitude, longitude, description of the site characteristics, and elevation are some of the descriptors that can be entered in the web form. 4. There is also a form to enter the contact information and other details about a person. These forms have fields to relate to other content types, called as node references. These inputs use autofills to make the correct selection easier. 5. A bibliographic section captures all information related to publications.

10 6. The basic details for a data set, such as title, abstract, publication date, keywords, etc are captured in another form that has connectors to the personnel, research sites and publications. See an instance of this form in Figure 5 7. A research project form captures information about the umbrella project that may encompass several data sets. Fig 4. A web form to capture information about a variable. Ideally, the information about a variable is populated automatically off the original data. However, a user friendly interface is provided to correct and add information about a variable. Three types of variables typically used in biological studies can be documented. Codes, dates and physical measurements can be added to a description of the variable using the tabs in the form.

11 Fig 5. This web form captures the basic details about a dataset. The information captured (abstract, title, identifiers, locations, etc) allows the data to be found in specialized searches. The four tabs break down the form in simple one-pagers, and divide the metadata ingestion process by information categories. 4 Case Studies We describe here the steps taken to migrate content from the Luquillo Experimental Forest LTER [41] and Sevilleta LTER [42] information management systems in to the new Drupal model. These two LTER sites have a long history of research, with continuous data records that span about twenty years.

12 4.1 The Luquillo Experimental Forest LTER case The Luquillo LTER content migration is nearly complete. All the content is tied together minimizing the risk of running into a page without further suggestions or links to related content. The information is also mediated by a custom controlled vocabulary whose adequacy is being tested against the goal of unearthing related information (discovery functionality). The migration process started with the effort of three persons, one dedicated information manager for the Luquillo site, and two operators from the LTER Network Office. There were two main tracks for the migration, coordinated by the Luquillo information manager. One track dealt with the overall content, structure, layout and vision, while the other track focused on metadata. The metadata migration process: Most of the Luquillo metadata was standardized [11] using the Ecological Metadata Language specification as the common vehicle to share information. Following the first migration step, there was a semi-manual quality control procedure of the resulting EML documents. Once the metadata was rich in content, and controlled for quality, then taking advantage of the standardized format for metadata, we wrote a parser using Perl to migrate the metadata inside the Drupal content types created to host metadata. The re-usable parser (EML is used by several networks in the USA and abroad) accommodated most of the content and relationships in the content within the Drupal MySQL database. Over one hundred and twenty datasets were automatically migrated to the Drupal system. The 120 plus metadata sets describe over 900 tabular data files. Each data file, usually a spreadsheet, may contain data organized in hundreds or thousands of rows and several columns. Data files may have from three columns to several dozen columns. Each column represents a variable. The migration script re-used identical variables for different data files. In total, we processed over three thousand variables, some of which were found to be redundant upon closer inspection. We planned a revision procedure to check for content integrity, consisting of completing the relations with other relevant information not captured in the EML documents and correcting migration errors. We created a specialized variable query and results page that enabled us to detect and merge similar variables. By merging variables we facilitate data integration across different datasets. The Luquillo crew conducts research at several research areas. Most of the research areas are located within the Yunque National forest boundaries, except for a few areas that are located in a more urban setting, west of the forest. Each research area contains several research sites. Each research site contains a number of plots that are used to observe effects of treatments or simply experiment replicates. All this site information is managed in Drupal by the custom content type Research Site. In all, there are over fifty entries in this category which is closely related to research projects, data sets, data files and variables. Figure 6 shows Luquillo s hierarchy of content types under the umbrella of the Research Projects and gives the quantity of nodes for each content type. All seven content types are presented with the quantity of nodes that have been entered or in the process of entering into the system. The figure presents the relationship among the several content types.

13 Fig. 6 Luquillo s Information Management and Content system. Hierarchy of content types, their relations and the number of records these content type contain. Legend: CTE = Canopy Trimming Experiment; LEF = Luquillo Experimental Forest; PPT = Precipitation; NADP = National Atmospheric Deposition Program; LFDP = Luquillo Forest Dynamics Plot; SOM = Coil Organic Matter; LIDET = Long-Term Intersite Decomposition Experiment Team RP # =

14 Abbreviated Research Project; CT1:CT2 = Mapping a node from CT1 to CT2; {A} =A finite set of nodes; The overall information content migration to Drupal at the Luquillo LTER site was based on providing functionality while addressing shortcomings of their previous system. The legacy functionality included a searchable personnel directory, a data catalog with comprehensive structured metadata, a high level description of the Luquillo LTER projects, a publications catalog with over one hundred entries, several maps, a list of outreach activities including an elementary school program and a calendar of events. Parts of the information managed were automatically updated in the dynamic site portal using mysql and Paradox databases and PHP for the web interface. Other information offered through the web was static content subject to manual revisions both in the back end and the front site page, relying mostly on the server file system. Some Luquillo LTER goals in regard to the design of an information system included: easier maintenance than the current information system, shortened time lags between data capture and data offer online, semantic mediation for data classification, better information integration, and a framework that facilitates broader participation where investigators could take ownership of how the data and results from the data are portrayed to the public. Finally, Luquillo wanted to implement a vocabulary coordinated by a Luquillo committee. In addition, Luquillo wanted to connect all the legacy contents offered through the legacy sites. Personnel profiles with not just contact information, but related publications and data sets. Research projects were connected to people and publications, and so on. All this interconnected content made it easy to offer a more contextualized experience to anyone visiting their information portal or website. A committee formed by principal investigators from Luquillo LTER and the information management team refined a hierarchical controlled vocabulary that was used to tag the content. This task took considerable time resources, as there are five families of legacy vocabularies to tag the Luquillo information and data. The vocabularies were grouped in these five categories: Terms for describing the Core Area LTER Data Projects Terms for describing research locations Terms assigned by principal investigators Terms procured by a Luquillo LTER committee. Terms used for a special research project The most populous family was the free form Assigned by principal investigators, which included over eight hundred terms, including some misspellings and very similar terms. In contrast, the Core Area vocabulary had only a dozen terms, while the other vocabularies had terms in the one to two hundredths, including some redundancies. The new vocabulary, organized hierarchically, will be used for several purposes. In our content management context, we will test the subset that optimizes information discovery by analyzing both web logs and the number of nodes related and exposed in queries per term. The migration process started about a year ago, and it is nearly complete [43]. The cost of the migration process can be broken down in developer time (about 30 hours),

15 planning time (about a week), and development meetings (about three weeks). The Luquillo information manager traveled for some of the development meetings, adding the cost of the trip to the total time of this project. However, we still have to factor further training (one week) and learning as well as usability labs oriented to improve the service. 4.2 The Sevilleta LTER case The Sevilleta LTER site underwent a migration process that was similar to Luquillo LTER s migration. However, there were a number of differences that are noteworthy: All the migration team was co-located, which helped with the planning and development meetings. The legacy information was structured in a content management system (PostNuke, [44]), which translated the migration process to an exercise of mapping the content management systems databases. Much of the quality control process is still in order, since years of existence have resulted in several inconsistencies in the information structure. A new research plot content application has been deployed, with a higher degree of granularity. More sites, plots and subplots are documented in the database for use of the researchers and public exploration. The personnel, bibliography, data sets and research projects are now interconnected at the record (or node) level, rather than in separate compartments. The presentation to the user through the web portal is richer, with a higher degree of contextualized information per page visited. We minimize dead ends; that is, those information pages that have no further contextual links. The metadata migration followed the same path as in Luquillo. EML documents were used to move the content into the custom Drupal content types. In the Sevilleta LTER case, the EML content was non-uniform [45]. While some datasets were rich and quality controlled, others had limited content or inconsistencies, making the postmigration corrections more time-consuming. In all, the migration phase is completed; however, the content is not yet as envisioned in the planning process due to the quality control process that needs to happen. The correction and verification process of over two hundred data sets is easy but time consuming. We estimate about 100 hours extra to finish the Sevilleta Drupal project. The current Drupal Sevilleta portal mimics the previous website portal front page. Some of the menus and categories of information are the same, but the interconnectivity and functionality have been greatly expanded. For example, a personnel directory entry has been enhanced significantly. In addition to the customary person titles and contact information, we added the related list of research projects, data sets and publications. We tag the user with relevant keywords and show blocks of tag-related information on the margin of the main content. We have created similar rich pages for the data sets, research projects and bibliography. A publication list is no longer a list of more or less standard references. In addition to the list, all the elements that make up the list (title, authors, tags) are linked to the corresponding content.

16 4.3 Other upcoming and synergistic cases: The Plum Island LTER [46] and Arctic LTER sites [47] hosted at the Marine Biology Laboratory [48] are next to start the migration process. The LTER Information Management Committee allocated some modest funds to train the information managers through the development of their new information management systems. This process is expected to start sometime during the summer of The University of Michigan Biological Station has also tweaked the original Drupal based model, simplifying it for the needs of their principal investigators and users [49]. Specifically, the information manager has merged the data set and data file structure content types. This merging process narrows the definition of a dataset, but simplifies the metadata entry process, an advantage from usability point of view. The North temperate Lakes LTER is on the early stages of their content migration into the Drupal model described above [50]. One of the first steps consisted of integrating content in the database but shown through two different web portals: A website that uses the common projects for the North Temperate Lakes and one for the associated Microbial Observatory. The content types were modified slightly to adapt them to a different data model. The North Temperate Lakes LTER is currently developing queries to migrate the data into the new structure according to their migration plan. 5 Concluding remarks and future work We have developed a low cost integrative information management system for biological and ecological stations [51]. The customized information categories have been represented in a relational database using the Drupal content management system. Our decision was driven by several factors, including an analysis of the general resources of our potential consumers. This Drupal based information management system consumes and produces metadata that is compliant with some of the most common specifications. The system can be adopted by any organization. A number of instances have been deployed to serve as cloud-based metadata editors and metadata catalogs [52]. A factor that influenced us to offer these web based editors to produce and edit existing EML and BDP compliant metadata is the value of the NBII and LTER metadata program [4],[53]. The solutions proposed and described in this paper have been adopted by four biological stations that have been producing hundreds of scientific data since the 1980 s or earlier. Currently a joint NSF proposal of six LTER stations has been funded to advance several aspects of this system, including the automatic generation of metadata from data stored in relational databases, the consumption of web services, including the National Biological Information Infrastructure Thesaurus web services [54] and the US Department of Agriculture Integrated Taxonomic Information System web services [55]. Also, with this grant, we have started collaborating with Drupal developers that have worked with the Encyclopedia of Life (EoL) consortium with the intent of better integrating the metadata compliance in the Drupal system as well as the consumption of EoL s species pages.

17 A usability test for the systems is in order; an information system is successful when its users find it helpful. We plan to use the usability testing laboratory at the University of Tennessee [56] to find out and correct the weakest points of the system. In summary, we have sought a low cost solution to enhance the management of information and scientific metadata as a means to promote data integration and synthesis. The success of integrative network architectures such as PASTA [57] relies on the quality of the data ingested from the data providers. The Drupal based system that we provide here helps with the data and metadata curation and manipulation processes that are meant to harmonize otherwise irreconcilable data. Acknowledgments. Inigo San Gil would like to acknowledge the support of the USGS NBII program through the cooperative agreement with the NBII. References 1. Michener, W. K. (2005) Meta-information concepts for ecological data management. Ecological Informatics 1(1), 3-7 (2005) 2. Sepic, R. and Kase, K.: The national biological information infrastructure as an E- government tool Government Information Quarterly 19(4), (2002) 3. The National Biological Information Infrastructure site at 4. San Gil, I, Hutchison, V., Frame, M. and Palanisamy, G. Metadata Activities in Biology. J. of Library Metadata. Accepted (2010) 5. Aguilar, R., Pan, J., Gries, C., San Gil, I. and Palanisamy, G.: A flexible online metadata editing and management system. Ecological Informatics, 5(1), (2009) 6. The Arizona Hydrological Information System at 7. The Oak Ridge National Laboratory Mercury Consortium 8. The Drupal Content Management System, 9. The Long Term Ecological Research Network, 10.Hobbie, J.E.: Scientific Accomplishments of the Long Term Ecological Research Program: An Introduction. BioScience, 53(1), (2003) 11.San Gil, I., Baker, K., Campbell, J., Denny, E. G., Vanderbilt, K., Riordan, B., Koskela, R., Downing, J., Grabner, S., Melendez, E., Walsh, J. M., Kortz, M, Conner, J., Yarmey, L., Kaplan, N., Boose, E. R, Powell, L., Gries, C., Schroeder, R., Ackerman, T., Ramsey, K., Benson, B., Chipman, J., Laundre, J., Garritt, H., Henshaw, D., Collins, B., Gardner, C., Bohm, S.,. O'Brien, M., J. Gao, W. Sheldon, S. Lyon, D. Bahauddin, M. Servilla, D. Costa and J. Brunt. The Long Term Ecological Network metadata standardisation implementation process: A progress report. International Journal of Metadata, Semantics and Ontologies. v4, n3, pp (2009) 12.Harmon, M. Motion to adopt EML at the Coordinating Committee. (2003) pring_03_cc.htm 13.Orbeon, a framework for XForms Tomcat, An apache servlet container Rugge, D. J. :Creating FGDC and NBII metadata using metavist Technical Report (2005) 16.Morpho, a standalone editor that outputs Ecological Metadata Language compliant XML The Organization for Biological Field Stations portal is at

18 18.ISO A international geographic information metadata standard. commid= ISO Another ISO standard to cover geographic metadata, this is the XML implementation 20.The US National Phenology Network The ecology group at Sierra Nevada, creators of Linaria The University of Michigan Biological Field Station using Drupal. (2010). Resource at 23.The wind energy data and information gateway (WENDY) at 24.Encyclopedia of Life LifeDesks Drupal Modules, by the encyclopedia of life 26.Wiersma, G.S.: Building Online Content and Community with Drupal. Collaborative Librarianship.1(4) pp169 (2009) 27.Apache web server at 28.Microsoft s Internet Information Server 29.The Pre HTML Processor language at 30.The JavaScript at 31.Mysql now at 32.PostGreSQL at 33.Buytaert, D.: State of Drupal. Keynote presentation at DrupalCon 2010, San Francisco, CA (2010) 34.The Drupal themes at 35.The extensible markup language at 36.The Perl language at 37.The XML stylesheet transformation language at 38.The guidelines for EML use are at /index.html 39.The Biological Data Profile at 40.Velleman, P.F. and Wilkinson, L.:Nominal, ordinal, interval, and ratio typologies are misleading, American Statistician (1993) 41.The Luquillo Experimental Forest LTER at 42.The Sevilleta LTER portal at 43.Melendez, E.: Developing a Drupal website-ims for Luquillo LTER while learning Drupal. Databits. Spring Issue. (2010) 44.PostNuke Content management system 45.San Gil, I. and Baker, K.:The Ecological Metadata Language Milestones, Community Work Force, and Change. Databits. Fall (2007) 46.The Plum Island Ecosystem at 47.The Arctic LTER at 48.The Marine Biology Laboratory at Woods Hole, Massachusetts The University of Michigan Biological Station 50.The North Temperate Lakes Drupal developments 51.The DIMS at 52.One of the instances of a cloud based editor at 53.Lytras, M. D. and Sicilia M.A: Where is the value in metadata?. International Journal of Metadata, Semantics and Ontologies. 2(4), (2007) 54.NBII Thesaurus tool and web client accessible at 55.The Taxonomic web services

19 57.The University of Tennessee College of Communication and Information user experience laboratory 56.Servilla, M.S., Brunt, J.W., San Gil, I., and Costa, D.: Pasta: A Network-level Architecture Design for Generating Synthetic Data Products in the LTER Network. Databits Fall (2006)