Outer Space to Inner Earth: The Data

The Earth Science related topics in Day 4 include seven sessions. Among which two of them give us attentions to the role of geospatial data and geoinformatics; the other two concerns the topic of disaster data management; and one other session is related to the environmental policy and management in the specific issue of environmental indicator within the Asian context. The remaining two sessions present data in Astronomy and technology in renewable energy (a session relates to material sciences in previous days: A5 and E5).

Geospatial Data and Geoinformatics

The session Earth and Environment (Part I/ G3) concerns data application and management for the earth and environment and focus on geospatial dimension, while session Earth and Environment (Part II/ H3) focus more on technical perspective that we summarise theses talks in Computer and Information Science Report.  The discussion of G3 began with an introduction of the Multi-agents Knowledge Oriented Cyberinfrastructure (MAKOCI) developed in Taiwan with the aim of managing and discovering appropriate open GeoData from the web to assist in policy and decision making. In particular, semantic web technologies such as the Ontological Catalogue (ONTOCAT) are used for users to register metadata and acts as the semantic dictionaries. In addition, one of the more popular method of presenting GeoData is through Spatial Interaction Data Visualization, also known as Flow Mapping. In order to meet the computational power needed for Flow Mapping, a three-tier computational framework was built to process the data, perform the calculation, and presents the visualization. Field Observation Data is the primary channel for scientists to collect GeoData that forms the basis for further research, and the database hosting these data should consider the following factors during the design process: data preservation, quality control, pre-processing of the data, and speed of access. The session concluded with a presentation detailing the steps taken for the adaptation of Artificial Neural Network to model the fluctuation of ground water depth (GWD). The simulated results can be used to forecast ground water preservation and help regulate the subsequent groundwater usage.

As we have learned from previous days the importance of data curation, we might wonder what the role of data curation is playing in earth observations area? The Taiwan Integrated Earth Observation System session introduces Taiwan’s efforts in supporting the IPY project through the remote sensing satellite data of FORMOSAT-2 and OGC (Open Geospatial Consortium) standards and services, as well as 3D GIS cloud technologies for enhancing human-interaction and navigation. In addition, the Taiwan Geospatial One Stop Portal (TGOS) and the Collaboration Platform for Sustainable Development (COPSD) are projects that are currently under development serve to address the massive inflow of data, providing data management, sharing, and archiving services, as well as using public participation geographic information system methodology. The question in the discussion is not how much we don't know, but how to use the information that we do know and turn them into knowledge.

Disaster Data Management

Sessions of IRDR and the DATA Project (H1) and Global Perspectives on Disaster Databases (H2) are a series of presentations (with B2 and D5) coupled with panel discussion covering the topic of Disaster Loss Data, Session H1 focused on: the data landscape and the need of data. Disaster loss data landscape is made up of the data providers, collectors, data sharing platforms, and the user; the data can come from a variety of sources, including traditional media, social media, and scientific measuring station. Understanding the data landscape is essential to improve disaster management. Losses suffered during natural disaster are usually measured in financial terms, using economical model calibrated with loss data recorded from past events; analyzing the disaster loss pattern, the accuracy of which depends on the quality of data collected, could provide insights into management of future disasters. Some of the questions raised during the H1 panel session includes the issue of data loss, which is more prevalent nowadays due to the increase in data volume; the issue of improvements to data landscape so loss of data can be avoided; and the issue of ensuring quality of data and avoid data bias.

Session Global Perspectives on Disaster Databases continued the discussion on Disaster Loss Data with the following topics: disaster damage assessment, sources for specific disaster data, and dealing with disaster loss. The disaster loss and damage data is essential for risk assessment, which is used by decision makers in government to assess the damage dealt by the disaster, form recovery plan and take preventative measures to avoid further losses; due to the impact of data quality on those decisions, the speaker stressed the importance of collecting quality and precise data in the field. In addition to data quality, the standardization of data format and collection method for specific data source would also impact the time it takes for data processing and sharing; the standardization of data collection process also impact the international cooperation between small nations that share similar geological features, and could improve the preparedness and preventative measures employed by the governments. The final talk in this session was on damage and disaster loss, which covers the financial impact of natural disaster on people living in the area. The availability of disaster loss data could help mitigate the impact of natural disasters by ensuring adequate level of insurance coverage on property, goods, and crops are maintained. During panel discussion, questions were raised regarding the capability of disaster loss estimation, and on the possibility of current technology providing daily disaster loss prediction; the panel replied that while geological prediction is not a problem, disaster loss prediction and demographic shifts could not be accurately calculated based on available data. 

Environmental Indicator in Asia

The importance of various environmental indexes, such as the Environmental Sustainability Index (ESI) and Environmental Performance Index (EPI), is discussed in session H2. These indexes provide a measurable standard for government to gauge the effectiveness of their environmental policies, and could severely impact the country's image on international forum. In response to recent drop in ESI and EPI ratings, Taiwan and Korea invested aggressively on improvements such as smog control and creation of additional green spaces. Similar effort is being made in Malaysia, where the government is developing Environmental Performance Measurement System in order to attract investments and provides information for the government's policy making.

Astronomy and Material Science

Session Data Intensive Astronomy in East Asia (G4) discussed the current astronomical database and virtual observatory available to researchers in East Asia. As the data gathering technology improves in Astronomy, massive human and computer processing hours are required to analyze those data. Virtual observatories projects such as the Japanese Virtual Observatory (JVO), Chinese Astronomical Data Center (CAsDC), and the up and coming Taiwan Extragalactic Data Center (TWEG-DC) allow researchers to access and analyze the data collected over the years, making up for the lack in manpower or processing power at the data collecting facility. In particular, the discussion of database and data analysis in solar physics, has taken a specific focus on the Interactive Data Language and the spatial-temporal structure on analysing solar physic data. The virtual observatories also promotes the exchange of data with other major astronomical installations such as the Atacama Large Millimeter Array, providing researchers with a more complete picture than previously available. One question raised during the question and answer session was regarding digitization of data and pictures collected before the digital age, and it turned out that there is a division within the National Astronomical Observatory of Japan processing such data, while the the Chinese Astronomical Plate Digitization Project at CAsDC is performing similar effort in conjunction with the CODATA Data at Risk Group.

Panel Discussion during the session “Future Prospects for Renewable Energy: Solar Photovoltaic Technologies” (G5) concentrated on the prospect of developing solar energy industry in Taiwan. On the topic of solar cell efficiency, the panel noted that recent development in photovoltaic cell technology could significantly improve the energy conversion rate. The panel also noted that international cooperation with Germany and China for development of wind energy and energy storage technology is currently underway, and could compliment the energy gap of solar energy. One issue with the development of wind energy in Taiwan is the threat of natural disaster such as typhoon and earthquake, though cooperation between research institutes and the industry is looking into technologies that minimizing the environmental impact. The panel concluded that with the depletion of fossil fuel and risks associated with nuclear energy, solar power has the potential to become the next major source of energy.


  • Time & LocationOctober 31, 2012 @ Academia Sinica, Taipei, Taiwan 
  • Scientific Domain:  Earth Science (sessions: G3G4G5H1H2I2, and I4
  • Report prepared by:  John Wang and Andrea Huang


CODATA2012會議第4天與地球科學有關之講座包括了七個議題。其中二個議題主要焦點放在地理空間資料與地理資訊學在地球與環境議題中所扮演的角色; 另外二個議題探討災害資料管理; 另一議題則以環境政策與管理中特別的主題 - 「在亞洲地區的環境指標」為討論的重點; 其餘的議題則包括天文學領域的資料、以及再生能源的相關技術(與先前的材料科學議題A5與E5相關)。


「地球與環境 」第一部分 (G3)主要以地理空間的角度討論資料的應用與管理,「地球與環境 」第二部分 (H3)則強調技術方面的議題,因此我們將在電腦與資訊科學的報告中摘錄整理。G3議程由關於台灣『多代理人知識網路基礎設施』(MAKOCI)的介紹開場,而MAKOCI設立目的為探勘並管理網路上所可取得的地理資料,用以協助政府訂立政策。其中特別值得一提的是,MAKOCI運用語意網技術如「知識本體目錄/ ONTOCAT」提供使用者後設資料的註冊,並同時作為語意詞庫的用途。除此之外,地理資料最常使用的展現方式是為「空間互動資料視覺化」,或稱為「流程映射/Flow Mapping」。為了達到流程映射所需的電腦運算能力,電腦主機的運算架構被分解成數據,處裡,以及視覺化三個部份。至於地理資料的取得則是主要仰賴於現場觀測資料,而這些原始資料則會成為地理研究的基礎。建立儲存地理資料的資料庫時需要考慮的因素包括:資料保存,品質管理,數據的預處理,以及存取的速度。此議程最後一個議題為介紹如何使用人工神經網路模型於預測地下水位,由此模型模擬出的數據有助於預測地下水位的序存量並用於地下水使用之控管。

由於在會議的前面幾日我們已知資料策展議題的重要性,因此對於地球觀測資料的策展也是另一個我們可能關心的意提。在「台灣地球觀測資源整合論壇」議程中主要介紹台灣的相關實作案例,對於如參與國際極地年(IPY)計畫,台灣透過福衛二號的遙測衛星資料與開放式地理空間資訊標準(OGC)標準、以及增強使用者互動與流覽的 3D GIS雲端技術積極參與IPY活動。此外,「台灣空間資訊系統單一服務入口網,TGOS 」以及「永續發展協同合作平台,COPSD 」等發展中的計畫,將因應湧入的大量資料,所必須提供的資料管理,資料分享,及資料儲存等服務而持續進行中。在議程的討論中,與會者提出現在最主要的問題不是我們還有多少未知,而是我們如何整理以收集到的資料,並將他們轉換成知識。


「災害風險綜合研究計畫以及資料計畫 」(H1)以及「災害資料庫的全球觀點 」(I2)二大議程為一系列與災難損失資料相關的講座與專題討論所結合(其他相關議程分別為B2 and D5)。其中H1講座的主題包括了資料地景以及資料的需求。災損資料的資料地景由資料提供者,資料收集者,資料分享平台,以及資料使用者;而災損資料可來自多種管道,包括新聞媒體,社交網站,以及研究觀測站。了解資料地景將有助於改善災難控管。自然災難造成的損失大多是以金錢來衡量損失程度,而這些損失多是使用由過去災難資料修正過得經濟模型估算出的。而分析災損的分佈將有助於有助於管理未來有可能發生的災害;然而,分析災損分佈的準確性仰賴於所收集到資料的品質。在專題討論中討論的內容包括了:面對新一代儀器收集到的大量資料,如何避免資料的流失:如何改善資料地景,以避免其中的資料流失;以及如何確保所收集到的資料之品質以及避免偏頗的資料。

「災害資料庫的全球觀點 」議程繼續了關於災損資料的討論,其中的講座部份涵蓋了以下幾個主題:災難資料評估,特定資料之取得,以及對災害損失的應對。災難損失與破壞資料的取得使得風險評估得以進行,而災害的風險評估使政府得以估計災難帶來的破壞,訂立重建計畫,以及採取避難措施以降低災情。由於許多政府決策仰賴正確的風險評估,講者特別強調了取得精準,高品質資料的必要性。除了資料品質外,資料格式的標準化以及收集資料的方式都會影響分析與分享這些資料所需的時間。標準化資料的收集方式亦有助於共享地理特徵(如火山,斷層等)的國家之間對於天然災害的預防與準備。I2議程最後的講座討論了天災對人民所造成的金錢損失,而講者指出災損資料的存在將會幫助人民決定災後重建所需的保險選項及金額。在專題討論中,聽眾提問了關於災難損失預估的預測能力以及提供每日預測值得可能性,對此討論小組表示雖然自然災害本身的預測不是問題,災損預測以及人口流動並沒有準確的即時資料可供參考,也因此無從計算每日的災損預測。




「東亞地區密集的天文資料」議程 (G4) 討論的主題為東亞現有的天文資料庫、以及虛擬天文台。隨著天文學相關觀測技術的進步,日漸增加的天文觀測資料需要大量的人力與電腦運算時數以進行分析。日本虛擬天文台 (JVO),中國天文數據中心 (CAsDC),以及正在架構中的台灣星系天文學資料中心 (TWEG-DC) 等虛擬天文台相關計畫賦予研究人員取得並分析歷年來收集的天文資料之管道,而收集資料的天文台也可藉此補足因缺乏人力或電腦運算能力而無法分析的數據。特別值得一提的是,太陽物理學中的資料庫分析因動態資料量的特殊性,在討論中強調互動資料語言的描述、以及分析太陽物理資料時所需的時空架構。此外,虛擬天文台的設立也推廣世界主要天文設施 (例如與阿塔卡瑪大型毫米波天線陣) 之間的合作,並賦予研究人員取得更加廣泛的天文資料的能力。議程討論中聽眾向講者提問各虛擬天文台關於數位化之前所收集的天文資料之數位化的計畫,對此JVO代表表示目前有一個工作組正在進行天文照片數位化的工作,而CAsDC的代表也指出目前與CODATA瀕危資料小組合作的「天文底片數據化」計畫正在進行中。

「再生能源的未來: 太陽能光電技術」議程(G5)中舉行的的專題討論,聚焦於台灣的太陽能產業發展的前景。對於有關太陽能板的發電效率的疑問,討論小組指出最新的光電轉換技術相較於現行技術的發電率已有大幅度的進步;討論席並指出與德國及中國對於風力發電的相關合作可以有效輔助太陽能發電因日照時間影響而造成的的能量短缺。然而,風力發電在台灣的發展受到了颱風,地震等天災的限制,然而學術單位與產業之間正在共同尋求減輕環境對於風力發電的影響之方法。討論小組的討論結果為,有鑑於石化能源來源的枯竭以及核能發電的淺在危險性,太陽能有成為主要發電來源的潛力。