COLLABORATIVE DEVELOPMENT OF RECOMMENDATIONS FOR A COOPERATIVE NRDA

2008 ◽  
Vol 2008 (1) ◽  
pp. 1141-1145 ◽  
Author(s):  
Marty Cramer ◽  
Roger Helm ◽  
Mike Ammann ◽  
Charlie Hebert ◽  
Dan Doty ◽  
...  

ABSTRACT Collaboration is defined in some dictionaries as “working with the enemy” which can be the position both the responsible parties (RPs) and natural resource trustees (trustees) take when conducting “cooperative” natural resource damage assessments (NRDAs). In many incidents, collaboration on the collection of time-critical or ephemeral environmental data is delayed or the opportunity is lost while the RP and trustees negotiate the details of the scope and procedures of the data collection activities as well as future analyses/interpretation of the data collected. Consequently, in the absence of pre-spill planning as well as the commitment to basic tenets of cooperative work, the ephemeral data critical to determining the environmental effects of the oil and, subsequently, to conducting a successful damage assessment, can be lost. In order to support successful outcomes of cooperative NRDAs, the West Coast Joint Assessment Team (JAT) developed a document titled Recommendations for Conducting Cooperative Natural Resource Damage Assessments. The intent of the JAT document is to promote cooperative NRDAs and facilitate the development of an ephemeral data collection (EDC) plan to ensure the opportunity for collecting time-critical information is not lost. Specifically, the document outlines the cooperative assessment process including regulatory guidance and considerations for conducting a cooperative assessment. It also includes recommendations for organizing an EDC team, collection of source oil, water, sediment, and biota samples, analysis of those samples, and establishing data quality objectives. Additionally, an example of a trustee funding commitment letter is provided to expedite the initiation of the cooperative process and avoid prolonged legal negotiations. The JAT is an ad-hoc volunteer group of west coast-based oil company, federal and state trustee, and NGO representatives that was formed to share information and experiences related to NRDA and to discuss how best to improve the process for cooperative assessments. After several years of meetings, discussions, and presentations, the JAT put pen to paper and developed, in a collaborative and consensus based effort, recommendations for use by its members and others to facilitate cooperative NRDAs. This paper describes pertinent features of the JAT cooperative assessment recommendations document, the document development process as well as a brief background of the JAT.

2020 ◽  
Vol 5 ◽  
pp. 100
Author(s):  
Yasmin Iles-Caven ◽  
Kate Northstone ◽  
Jean Golding

Enrolling a cohort in pregnancy can be methodologically difficult in terms of structuring data collection. For example, some exposures of interest may be time-critical while other (often retrospective) data can be collected at any point during pregnancy.  The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prime example of a cohort where certain data were collected at specific time points and others at variable times depending on the gestation at contact.  ALSPAC aimed to enrol as many pregnant women as possible in a geographically defined area with an expected date of delivery between April 1991 and December 1992. The ideal was to enrol women as early in pregnancy as possible, and to collect information, when possible, at two fixed gestational periods (18 and 32 weeks). A variety of methods were used to enrol participants.   Approximately 80% of eligible women resident in the study area were enrolled. Gestation at enrolment ranged from 4-41 (median = 14) weeks of pregnancy. Given this variation in gestation we describe the various decisions that were made in regard to the timing of questionnaires to ensure that appropriate data were obtained from the pregnant women.  45% of women provided data during the first trimester, this is less than ideal but reflects the fact that many women do not acknowledge their pregnancy until the first trimester is safely completed. Data collection from women at specific gestations (18 and 32 weeks) was much more successful (80-85%). Unfortunately, it was difficult to obtain environmental data during the first trimester. Given the time critical nature of exposures during this trimester, researchers must take the gestational age at which environmental data was collected into account. This is particularly important for data collected using the questionnaire named ‘Your Environment’ (using data known as the A files).


1995 ◽  
Vol 1995 (1) ◽  
pp. 327-331
Author(s):  
Richard W. Dunford ◽  
Kristy E. Mathews ◽  
H. Spencer Banzhaf

ABSTRACT A cooperative approach was used to estimate natural resource damages from the Avila Beach, California, spill. The approach was cooperative because we, on behalf of Union Oil Company of California (UNOCAL), and the economist working for the State of California shared data collection and damage estimation responsibilities. Cooperative assessments have several advantages, including reduced costs and less duplication. Because this case was not settled when this paper was submitted, we provide no damage estimates.


2018 ◽  
Vol 2 ◽  
pp. e25439
Author(s):  
Peter Brenton

Many organisations running citizen science projects don’t have access to or the knowledge or means to develop databases and apps for their projects. Some are also concerned about long-term data management and also how to make the data that they collect accessible and impactful in terms of scientific research, policy and management outcomes. To solve these issues, the Atlas of Living Australia (ALA) has developed BioCollect. BioCollect is a sophisticated, yet simple to use tool which has been built in collaboration with hundreds of real users who are actively involved in field data capture. It has been developed to support the needs of scientists, ecologists, citizen scientists and natural resource managers in the field-collection and management of biodiversity, ecological and natural resource management (NRM) data. BioCollect is a cloud-based facility hosted by the ALA and also includes associated mobile apps for offline data collection in the field. BioCollect provides form-based structured data collection for: Ad-hoc survey-based records; Method-based systematic structured surveys; and Activity-based projects such as natural resource management intervention projects (eg. revegetation, site restoration, seed collection, weed and pest management, etc.). This session will cover how BioCollect is being used for citizen science in Australia and some of the features of the tool.


2020 ◽  
Vol 5 ◽  
pp. 100
Author(s):  
Yasmin Iles-Caven ◽  
Kate Northstone ◽  
Jean Golding

Enrolling a cohort in pregnancy can be methodologically difficult in terms of structuring data collection. For example, some exposures of interest may be time-critical while other (often retrospective) data can be collected at any point during pregnancy. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prime example of such a cohort. ALSPAC aimed to enrol as many pregnant women as possible in a geographically defined area with an expected date of delivery between April 1991 and December 1992. The ideal was to enrol women as early in pregnancy as possible, and to collect information, when possible, at two fixed gestational periods (18 and 32 weeks). A variety of methods were used to enrol participants. Approximately 80% of eligible women resident in the study area were enrolled. Gestation at enrolment ranged from 4-41 (median = 14) weeks of pregnancy. Given this variation in gestation, we describe the various decisions that were made in regard to the timing of questionnaires to ensure that appropriate data were obtained from the pregnant women. 45% of women provided data during the first trimester; this is less than ideal but reflects the fact that many women do not acknowledge their pregnancy until the first trimester is safely completed. Data collection from women at specific gestations (18 and 32 weeks) was much more successful (80-85%). Unfortunately, it was difficult to obtain environmental data during the first trimester. Given the time critical nature of exposures during this trimester, researchers must take the gestational age at which environmental data was collected into account. This is particularly important for data collected using the questionnaire named ‘Your Environment’ (using data known as the A files).


Author(s):  
Cristina G. Wilson ◽  
Feifei Qian ◽  
Douglas J. Jerolmack ◽  
Sonia Roberts ◽  
Jonathan Ham ◽  
...  

AbstractHow do scientists generate and weight candidate queries for hypothesis testing, and how does learning from observations or experimental data impact query selection? Field sciences offer a compelling context to ask these questions because query selection and adaptation involves consideration of the spatiotemporal arrangement of data, and therefore closely parallels classic search and foraging behavior. Here we conduct a novel simulated data foraging study—and a complementary real-world case study—to determine how spatiotemporal data collection decisions are made in field sciences, and how search is adapted in response to in-situ data. Expert geoscientists evaluated a hypothesis by collecting environmental data using a mobile robot. At any point, participants were able to stop the robot and change their search strategy or make a conclusion about the hypothesis. We identified spatiotemporal reasoning heuristics, to which scientists strongly anchored, displaying limited adaptation to new data. We analyzed two key decision factors: variable-space coverage, and fitting error to the hypothesis. We found that, despite varied search strategies, the majority of scientists made a conclusion as the fitting error converged. Scientists who made premature conclusions, due to insufficient variable-space coverage or before the fitting error stabilized, were more prone to incorrect conclusions. We found that novice undergraduates used the same heuristics as expert geoscientists in a simplified version of the scenario. We believe the findings from this study could be used to improve field science training in data foraging, and aid in the development of technologies to support data collection decisions.


2010 ◽  
Vol 13 (2) ◽  
pp. 369-380 ◽  
Author(s):  
J. Borges de Sousa ◽  
G. Andrade Gonçalves

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3588 ◽  
Author(s):  
Lien-Wu Chen ◽  
Yu-Hao Peng ◽  
Yu-Chee Tseng ◽  
Ming-Fong Tsai

Mobile ad hoc networks (MANETs) have gained a lot of interests in research communities for the infrastructure-less self-organizing nature. A MANET with fleet cyclists using smartphones forms a two-tier mobile long-thin network (MLTN) along a common cycling route, where the high-tier network is composed of 3G/LTE interfaces and the low-tier network is composed of IEEE 802.11 interfaces. The low-tier network may consist of several path-like networks. This work investigates cooperative sensing data collection and distribution with packet collision avoidance in a two-tier MLTN. As numbers of cyclists upload their sensing data and download global fleet information frequently, serious bandwidth and latency problems may result if all members rely on their high-tier interfaces. We designed and analyzed a cooperative framework consisting of a distributed grouping mechanism, a group merging and splitting method, and a sensing data aggregation scheme. Through cooperation between the two tiers, the proposed framework outperforms existing works by significantly reducing the 3G/LTE data transmission and the number of 3G/LTE connections.


2019 ◽  
Vol 5 (2) ◽  
pp. 94-103
Author(s):  
Yeni Ernawati

The purpose of this study was to describe the needs of students and teachers for learning to write scientific-based fable text, produce teaching materials on Student Worksheet (LKPD) on scientific-based Fable Text material, and describe the results of expert validation of the developed LKPD. This research is a development study using a modification of the development model of Dick, Carey, and Carey and Jolly & Bolitho. The subjects of this study were students of class VIII and Indonesian Language Teachers. Data collection techniques are done using a questionnaire and documentation. The feasibility of the developed teaching material is known from the results of validation by three experts on the 4 components of teaching material, namely the component of material eligibility, language component, presentation component and graphic. Based on the results of expert validation, LKPD on the fable text material developed is categorized as good or suitable to be used as a textbook companion teaching material. In the content / material component, LKPD outlines one Basic Competency (KD) in each activity. Each activity is in accordance with the steps of the scientific approach that is equipped with worksheets and assessment rubrics so as to facilitate students and teachers in the learning and assessment process. In the language component, LKPD uses simple and effective language, and is equipped with a glossary to make it easier for students to understand new vocabulary. In the presentation and graphic components, LKPD uses larger types and font sizes, and attractive designs with illustrations of colored images.


2021 ◽  
Vol 11 (22) ◽  
pp. 10771
Author(s):  
Giacomo Segala ◽  
Roberto Doriguzzi-Corin ◽  
Claudio Peroni ◽  
Tommaso Gazzini ◽  
Domenico Siracusa

COVID-19 has underlined the importance of monitoring indoor air quality (IAQ) to guarantee safe conditions in enclosed environments. Due to its strict correlation with human presence, carbon dioxide (CO2) represents one of the pollutants that most affects environmental health. Therefore, forecasting future indoor CO2 plays a central role in taking preventive measures to keep CO2 level as low as possible. Unlike other research that aims to maximize the prediction accuracy, typically using data collected over many days, in this work we propose a practical approach for predicting indoor CO2 using a limited window of recent environmental data (i.e., temperature; humidity; CO2 of, e.g., a room, office or shop) for training neural network models, without the need for any kind of model pre-training. After just a week of data collection, the error of predictions was around 15 parts per million (ppm), which should enable the system to regulate heating, ventilation and air conditioning (HVAC) systems accurately. After a month of data we reduced the error to about 10 ppm, thereby achieving a high prediction accuracy in a short time from the beginning of the data collection. Once the desired mobile window size is reached, the model can be continuously updated by sliding the window over time, in order to guarantee long-term performance.


1994 ◽  
Vol 37 (5) ◽  
Author(s):  
A. M. DzIewonski

The origins of the Federation of Digital Seismograph Networks (FDSN) can be traced to the summer of 1984. At that time, GEOSCOPE - the French global network of broadband instruments - was already well under way, and in the United States, the Incorporated Research Institutions for Seismology (IRIS) had just published its Science Plan for Global Seismographic Network (GSN). There was clearly an opportunity and the need to involve scientists from other countries in planning for the future of global seismology. An ad hoc meeting of some ten West European seismologists had been arranged in August during the annual meeting of the European Geophysical Society in Louvain. This may be considered to signify the beginning of widescale international cooperation, even though this particular group eventually became the nucleus of ORFEUS (Observatories and Research Facilities for EUropean Seismology). Rather than taking an active role in deployment of new stations, it chose to focus on the issue of providing the service for data collection and exchange, with an important mission of developing the requisite software.


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