ESA LearnEO! A Radmap fr Earth Observatin Educatin in Eurpe DRAFT v3
ESA AO/1-7008/11/I-BG Earthnet - ESA Learn Earth Observatin Prject LearnEO! Deliverable D-170, December 2015 Authrs Valbrg Byfield, Natinal Oceangraphy Centre, U.K. val.byfield@nc.ac.uk Fabi DelFrate, Tr Vergata University, Italy. Ravi Kapur, Imperative Space, U.K. Pierre-Philippe Mathieu, ESA-ESRIN, Mark Higgins, EUMETSAT Participants in the ESA LearnEO! Educatin Wrkshp Frascati, 3-5 Nvember 2014 Dwnlad radmap http://www.learn-e.rg/dcs/learneo_eo_educatin_radmap_v3.pdf Revisin Histry Issue Date Change recrds Authr(s) v1.0 2015-02-14 Draft radmap based n presentatins, discussin and summaries at the ESA LearnEO Educatin Wrkshp, Frascati 5-7 Nv 2014, with pst wrkshp input frm participants. v1.1 2015-05-05 Revised Radmap based n wrkshp discussins, pst wrkshp feedback frm participants n pririties fr future EO educatin activities. V. Byfield, F.Del Frate, M.Higgins, R.Kapur, with LearnEO Educatin Wrkshp participants V. Byfield, F.Del Frate, M.Higgins, R.Kapur, with LearnEO Educatin Wrkshp participants v1.2 2015-05-31 Minr revisins t text. V. Byfield, F.Del Frate, R.Kapur, M.Higgins, with LearnEO Educatin Wrkshp participants v2.0 2015-12-15 Versin 2 f the Radmap, extensively revised t include infrmatin and pririties frm EO Open Science 2.0. V3.0 2015-12-31 Versin 3 f the draft Radmap with minr changes t finalize layut and text V. Byfield, F.Del Frate, R.Kapur, P.-P. Mathieu M.Higgins V. Byfield, F.Del Frate, R.Kapur, P.-P. Mathieu, M.Higgins
Cntent Executive Summary... iv 1 Intrductin... 1 2 A visin fr the future: where d we want t be in 2030?... 1 2.1 The visin: Earth bservatin in Envirnmental Data Science (EDS)... 1 2.2 User Prtraits... 2 2.2.1 A new EDS graduate... 2 2.2.2 A career changer... 2 2.2.3 A research scientist wh needs t wrk with a new type f data... 2 2.2.4 An envirnmental cnsultant... 3 2.2.5 A university lecturer... 3 2.2.6 A schl teacher... 3 2.3 Easy access t EO educatin fr all... 3 3 Meeting the educatin needs f different audiences... 4 3.1 Attracting, inspiring and infrming new audiences... 4 3.1.1 EO educatin in schls... 5 3.1.2 Nn-technical users in the wider cmmunity... 6 3.2 Prfessinal educatin fr envirnmental data scientists... 6 3.2.1 University-level educatin f envirnmental scientists... 7 3.2.2 Cntinued prfessinal develpment... 7 4 Existing EO educatin resurces and initiatives... 8 4.1 Web-Resurces and E-Learning... 8 4.1.1 ESA... 8 4.1.2 NASA... 9 4.1.3 NOAA... 10 4.1.4 Eurpean Spatial Data Research (EurSDR)... 10 4.1.5 Other resurces... 10 4.2 Capacity building initiatives... 10 4.2.1 On-ging internatinal prgrammes (in alphabetical rder)... 10 4.2.2 EU funded prjects (in alphabetical rder)... 13 4.2.3 Other internatinal cperatin... 15 4.3 Sftware and tls fr data analysis... 15 4.4 Outreach activities... 16 4.4.1 DLR... 16 4.4.2 ESA... 16 4.4.3 University f Heidelberg... 17 4.5 Apps and interactive bks... 17 4.6 Citizen Science... 17 5 Overcming existing barriers t effective EO educatin... 18 5.1 Lack f access t data and infrmatin suitable fr nn-experts... 18 5.1.1 Scientific users with limited EO expertise... 19 5.1.2 Schls and nn-technical users in the wider cmmunity... 19 5.2 Lack f relevant examples and case studies... 19 ii
5.3 Fragmentatin f Eurpean EO educatin resurces and initiatives... 19 5.3.1 Causes f the fragmentatin... 20 5.3.2 Overcming the fragmentatin t prvide easy access... 20 5.4 Pr Internet cnnectivity... 21 6 Recmmendatins... 21 6.1 Maintaining and extending the cre EO educatin cmmunity... 21 6.2 Wrking twards a ne-stp market place fr Eurpean EO educatin... 22 6.2.1 Review f existing resurces and their relevance t brad user grups... 22 6.2.2 Develpment f a gateway tl fr easy user access t relevant resurces... 23 6.2.3 Supplementing the gateway with a recmmendatin engine... 24 6.2.4 Prviding lcal and n-line peer supprt... 24 6.2.5 Identifying gaps and setting pririties fr future develpment... 25 6.3 Harnessing new cmputing and cmmunicatins technlgies... 26 6.3.1 App develpment... 26 6.3.2 Citizen science and direct engagement with real data... 26 6.3.3 Including ther technlgies... 27 6.3.4 The rle f MOOCs... 28 6.4 Keeping EO educatin relevant and up-t-date... 28 6.4.1 Crwd-surcing f new educatin resurces... 29 6.4.2 Setting standards and guidelines... 29 6.4.3 Building n existing material t reduce effrt... 30 6.4.4 Review, testing and quality cntrl... 30 6.4.5 Crediting cntributrs and prviding feed-back... 31 6.4.6 Mechanisms fr engaging ptential cntributrs... 31 6.5 Shwing cnsideratin fr users with pr Internet cnnectivity... 31 6.6 Summary f Recmmendatins... 32 6.6.1 Shrt term recmmendatins (1-3 years)... 32 6.6.2 Medium term recmmendatins (3-5 years)... 33 6.6.3 Lng term recmmendatins (6-10 years)... 33 References... 33 Appendix 1: LearnEO! Educatin Wrkshp Participants... 35 iii
Executive Summary Fr sciety t benefit fully frm its investment in Earth Observatin the data must be accessible and familiar t a glbal cmmunity f users wh have the skills, knwledge and understanding t use the bservatins apprpriately in their wrk. Future Envirnmental Data Scientists will need t draw n multiple data and infrmatin surces, using data analysis, statistics and mdels t create knwledge that is cmmunicated effectively t decisin-makers in gvernment, industry, and civil sciety. Netwrks, clud cmputing and visualizatin will becme increasingly imprtant as citizen scientists, data jurnalists and pliticians increasingly use Earth bservatin prducts t give their arguments and decisins scientific credibility. The verarching aim f Earth bservatin educatin must therefre supprt life-lng learning, allwing users at all levels t remain up-t-date with EO technlgies and cmmunicatin mechanisms that are relevant t their individual needs. Emerging interactive educatin methdlgies (such as MOOCs and mbile learning), and hands-n engagement with real data (such as thrugh citizen science prjects) will becme increasingly central t utreach, training and frmal educatin. T achieve this, it is necessary t engage a cmmunity f experts frm a range f disciplines, in rder t establish a cmprehensive netwrk f educatrs, technical experts, and cntent prducers. It will als be imprtant t encurage crwd-surcing f new cntributins, t help maintain scientific and educatinal quality. This is a frmidable task, beynd the resurces f any individual rganisatin. This Radmap fr future EO educatin is the result f tw wrkshps held at ESA-ESRIN, the ESA LearnEO! Educatin Wrkshp 5-7 Nvember 2014, and EO Open Science 2.0, 12-14 Octber 2016. Based n material presented at these wrkshps this radmap includes: a brief review f existing resurces and initiatives t deliver EO educatin in Eurpe, a preliminary identificatin f current gaps, an assessment f the ptential fr mdern infrmatin and cmmunicatin technlgies t help deliver EO educatin and training, and a set f justified recmmendatins fr future activities t ensure delivery f the educatin and training needed t take full advantage f EO data t prvide infrmatin fr envirnmental mnitring and decisin supprt. Bth wrkshps revealed blurring f bundaries between EO data science and EO educatin. Fr example, tls presented at EO Open Science 2.0 cme with supprting tutrials and use-cases, and these have a rle t play in frmal and infrmal educatin. Case studies frm scientific research ften use image data that can inspire and infrm audiences frm utside the scientific cmmunity. Research initiatives that cntain citizen science elements need t inspire and educate vlunteers in rder t be effective. T harness the educatin ptential f such activities requires an inclusive apprach, pen t anyne interested in cntributing t the n-ging develpment f EO educatin regardless f their backgrund. Fragmentatin f effrt and the lng-term sustainability f tls, utreach initiatives and educatin prjects are n-ging cncerns. The difficulty in maintaining user supprt when a prject ends crpped up in many cntexts at bth wrkshps. Open data, pen surce, pen science and pen educatin can mitigate sme f the prblems that may ccur when successful initiatives becme static as funding stps. Hwever, t meet user needs fr ease f access t available resurces and technical supprt there will always be a need fr a stable cre effrt that can maintain a basic level f activity and use this t leverage cntributins frm the wider cmmunity. Tw cnsideratins are central t the recmmendatins frm the wrkshps: 1. Future educatin initiatives shuld build n and include quality educatin material and established training netwrks frm a wide variety f past and current prjects. 2. New users shuld have easy and time-efficient access t available suitable educatin resurces, which can inspire interest and meet individual needs. T recncile these tw cnflicting requirements will require effective use f mdern technlgies iv
fr prviding access t nline resurces and present available chices in ways that meet a users preferences and individual learning needs. The recmmendatins belw have been divided int shrt-term (1-3 years), medium term (3-5 years) and lng term (6-10 years). Shrt term (ST) measures seek t establish a netwrk f interested experts, review existing resurces, identify gaps, set pririties fr future wrk, develp utline specificatins fr a gateway tl t prvide ne-stp targeted user access t distributed resurces, and investigating ptential mechanisms fr prviding user feedback and n-line peer supprt. In the medium term (MT) plans fr a gateway tl will be develped in detail and implemented as a prttype. This shuld prvide user access t widely distributed resurces, facilitate user feedback, peer review and user supprt. In the lnger term (LT) user access t the gateway will be further imprved t supprt crwdsurcing t fill gaps in and keep abreast f new develpments, and t facilitate peer review in rder t maintain technical, scientific and educatinal quality. Summary f the main recmmendatins Recruit and supprt a netwrk f experts t facilitate interactin between scientific, technical, educatin and cmmunicatin experts t plan and deliver a mre integrated apprach t EO educatin. (ST) Review existing educatin resurces, including thse that are nt part f frmal educatin initiatives, mapping these t brad user grups and applicatin areas, in rder t identify gaps, and set pririties fr future develpment. (ST) Encurage the develpment f new hands-n tutrials and ther activities assciated with EO-related apps and tlbxes, t shw hw these may be used in educatin cntexts. (ST) Develp additinal n-line curses (e.g. MOOCs), which shw hw EO data can prvide infrmatin fr scientific research and decisin supprt in a variety f cntexts (ST-MT). Detailed planning and implement an adaptive EO educatin gateway tl t facilitate user access t distributed resurces, tailred t individual interests and educatin needs. (MT) Develp a recmmendatin engine assciated with the gateway tl t facilitate user feedback, user recmmendatins and n-line supprt. (MT) Set up a frum fr prviding lcal and n-line peer supprt, linked t the gateway tl and recmmendatin engine. Encurage the inclusin f citizen educatin in citizen science, using the gateway tl and recmmendatin engine t facilitate links between citizen science prjects and suitable external educatin initiatives. (LT) Develp mechanisms t encurage, supprt and facilitate crwd-surcing f new educatin cntributins frm the wider EO data science cmmunity, reviewing these and making them available thrugh the EO educatin gateway (LT). Maintain and extend the gateway tl, recmmendatin engine and assciated fra, t include supprt fr specialist EO educatin netwrks where users and resurce prviders can cllabrate t develp, test, review and translate material. (LT) v
1 Intrductin Fr sciety t benefit fully frm its investment in Earth Observatin (EO) the data must be accessible and familiar t a glbal cmmunity f users wh have the skills, knwledge and understanding t use the bservatins apprpriately in their wrk. T achieve this, EO educatin must supprt life-lng learning, allwing users t remain up-t-date with new data surces, prcessing techniques and cmmunicatin mechanisms that are relevant t their individual needs. Prviding educatin resurces fr life-lng learning by users at all levels acrss the full range f EO applicatins is a frmidable task, beynd the resurces f an individual rganisatin. Recgnising this, the Eurpean Space Agency (ESA) has taken the initiative t develp a Radmap fr Earth Observatin Educatin. This Radmap starts with a visin f the future (Sectin 2), fllwed by an verview f key educatin needs f different audiences (Sectin 3), a brief review f existing EO educatin and training initiatives (Sectin 4), and an analysis f barriers t effective EO educatin fr all (Sectin 5). The Radmap itself, in the frm f justified recmmendatins fr future educatin activities is presented in Sectin 6. The review and recmmendatins are based n talks and discussins that tk place during a 3- day Earth bservatin educatin wrkshp, rganised as part f the ESA LearnEO! Prject 1 at ESA-ESRIN in Frascati, Italy, 5-7 Nvember 2014. Additinal suggestins ideas were prvided by wrkshp participants ver the fllwing weeks. Details f wrkshp bjectives, prgramme and participants may be fund in Annex 1. The analysis and recmmendatins resulting frm the LearnEO! Educatin Wrkshp have been updated and revised in the light f discussins that tk place during Earth Observatin Open Science 2.0 in Frascati, 12-14 Octber 2015. This dcument is nt a cmprehensive review f all existing resurces fr EO educatin. Nr is it a detailed specificatin fr a future Eurpean EO educatin system. Instead it sets ut a visin f hw EO data culd cntribute t Eurpean sciety in the future and gives sme ideas fr hw t make the visin cme true. We hpe that ur recmmendatins will help Eurpean institutins engaged in EO educatin and training t deliver educatinal tls and training activities that remain relevant an and up-t-date. The ideal system is ne where users at all levels have easy access t data, infrmatin and training resurces delivered in a way that suits their individual needs. It is nt a system that sees educatrs and students as distinct and separate grups, but ne where all wh wish t learn r cntribute t the educatin f thers will have the pprtunity t d s. This will a richer learning envirnment fr everyne, and will ultimately help t make Earth bservatin a familiar and natural cmpnent f envirnmental science, plicy-develpment, resurce management and daily life - an enjyable and useful surce f infrmatin fr Eurpe s citizens. 2 A visin fr the future: where d we want t be in 2030? 2.1 The visin: Earth bservatin in Envirnmental Data Science (EDS) In 2030 Envirnmental Data Science (EDS) will be a discipline whse practitiners can draw n multiple data surces frm a range f scientific disciplines, in rder t create envirnmental knwledge t supprt their decisins. Data will be bi-ge-chemical, physical and scial. The data sets will be large, cver space and time and vary in range and reslutin. Knwledge will be created using data analysis, statistics and mdels. Debates abut the rle f thery in big data will be n ging. The rle f clud cmputing will be significant. As tday, netwrks and cllabratin acrss different disciplines will be imprtant. Outputs will allw meaning t be easily recgnised, s visualisatin will be crucial. 1 http://www.learn-e.rg 1
There will be mre citizen scientists and mre data jurnalists. Envirnmental data science prducts will be a natural part f civil sciety and gvernmental advcacy. Pliticians will use prducts that are accessible t them in rder t give their arguments and decisins scientific credibility. As tday, hwever, n argument will be wn slely n the grunds f envirnmental data science. Future EDS prfessinals will have a wide range f skills that allw them t prvide decisin supprt fr gvernment, industry and civil sciety in a timely and apprpriate manner. They are meta-experts wh can identify, access, prcess and analyse data frm multiple surces t retrieve relevant infrmatin and knw hw reliable it is. Gd cmmunicatin skills allw them t interact with different users t establish their infrmatin needs and deliver the required infrmatin in suitable frmats. As meta-learners they keep abreast f new develpments in their field f expertise and in cmputing and cmmunicatin technlgies, making effective use f available training pprtunities. Frm their wn experience, they knw the value f penly available educatin resurces, and are therefre prepared t share their expertise by develping new case studies and lessns, reviewing resurces prvided by thers, ffering feedback t authrs and advice t ther users. 2.2 User Prtraits 2.2.1 A new EDS graduate Ada just graduated in Envirnmental Data Science frm a Cnsrtium f Eurpean Universities. Her hnurs prject lked at changing agricultural patterns in Eurpe since 2010. She received particularly high marks fr the clarity f her presentatin f uncertainty. She used ecnmic, scial and envirnmental data frm ver 30 different surces, and hpes she gt all the attributins right (the nes with DOIs will be k). She nly used data that can be presented as text r gridded NetCDF. She used a GIS fr the visualisatin and the R-Py plug-ins 2 fr the data prcessing. Prcessing was dne using the university cnsrtium clud server, with access t the data via pen-dap and web-map servers. Her studies were really practical. Many f the early classes invlved taking an n-line curse n EurEONet 3, which wuld then be discussed in class. The best lessns had great interactins s yu culd play with data and really understand its applicatins. Sme f her classes were taught with the pen data science stream 4. Her entire degree was taught nline. She is nw ready fr the first step in her career in industry, civil service r research. 2.2.2 A career changer Bill is starting a new career in Earth Observatin after several years as an ceangrapher, where he used EO data t supprt the develpment and validatin f cean mdels. As a data user, he was acting n panels t supprt the develpment n new data prducts, and fund himself increasingly interested in the effrt t deliver data prducts f knwn quality (including uncertainty estimates), traceable t reference standards. He felt he culd make a cntributin, but switching disciplines wuld be a big change, nt t be taken lightly. Luckily he had the pprtunity t use self-paced nline mdules available via EurEONet t btain mre in-depth infrmatin and test the water befre deciding finally t make the switch. 2.2.3 A research scientist wh needs t wrk with a new type f data Claire is an eclgist wh wants t include new EO data in her wrk. Thrugh EurEONet, she had easy access t the prduct guide, example data, and citatins fr research that included the use f this data type. She fund that the prduct guide was clearly laid ut and easy t navigate, t find 2 R-Py prvides a lw-level interface t R (an pen-surce language and envirnment fr statistical cmputing and graphics) frm Pythn (a widely used general-purpse, high-level, pen-surce prgramming language). R-Py plug-ins includes wrappers t graphical libraries, as well as R-like structures and functins. 3 Our prpsed n-line market place fr Eurpean EO educatin resurces (see Sectin 6.X). 4 Data stream prcessing allw envirnmental data scientists t access streams f real-time data and carry ut their wn prcessing and analysis, string the results in the clud and sharing infrmatin and data nline. 2
the infrmatin she needed with minimal effrt. The data were easy t access and manipulate, and it was clear where t begin. Sme f the review papers that analyse the applicatin f several datasets t specific prblems were really useful, and allwed her t adapt available analysis methds t her wn wrk. The DOI made the data easy t reference in papers, and the data prviders track wh is publishing based n their data infrmatin that is f value bth t users and data prviders, wh can tell their funders just hw much value is being generated fr Eurpe by having accessible data. 2.2.4 An envirnmental cnsultant Dan is a cnsultant wanting t develp his prfessinal skills t include the analysis f EO data fr envirnmental mnitring and resurce management. A busy prfessinal, he needs t d this whenever time allws, thrugh self-paced mdules that assist his learning and makes it mre effective. These mdules cver the data, visualisatin, statistics, and cmmunicatin. He als appreciates the pprtunity affrded by EurEONet t cntribute case studies based n his wn experience and link these int existing training mdules. A great way t learn is t teach, and the increased expsure he gets by cntributing training materials als brings him new clients and cllabratrs. 2.2.5 A university lecturer Eva has just started her jb as a university lecturer in envirnmental science. One f her tasks is t help develp a new remte sensing mdule, and she is desperately lking fr material she can use t make her lectures infrmative, scientifically valid, visually appealing, and relevant t the subject area. Thrugh EurEONet she has easy access t diagrams, figures, images and phts prvided by EO prfessinals and data users frm arund the wrld, and made available n-line thrugh a Creative Cmmns licence. Access t suitable data sets and analysis tls supprted by easy-t-use, peer-reviewed instructins, allws her t build a tailred series f hands-n practical exercises fr her students. Her students can als use the n-line resurces fr individual and grup prjects. In return they cntribute by testing new material, prviding feedback t authrs and data prviders, and reviews that make it easier fr ther users t evaluate and select material fr their particular use in the future. 2.2.6 A schl teacher Finn is a schlteacher lking fr educatin material he can include t make his teaching mre relevant and exciting. Thrugh EurEONet he has access t interesting case studies which are supprted by educatin resurces fr the subjects he teaches. The materials are easy t link t natinal curriculum bjectives, with activities that are easy t implement in the classrm, and really engaging and suitable fr students at different levels, s he can make his teaching suit the differing needs f his students. As a result all his students have at least ne experience f using EO data t slve a simple, interesting prblem by the time they leave schl. Knwing the imprtance f gd feedback, Finn prvides infrmatin n hw the material is used by his students and ffers suggestins fr imprvements. He als makes recmmendatins t ther users and shares his experiences with clleagues thrugh the n-line teacher frum. 2.3 Easy access t EO educatin fr all The prtraits abve are examples f hw different types f EO data users might take advantage f penly available educatin resurces, and als cntribute t making these resurces cmprehensive, relevant, user-friendly and up-t-date. The EurEONet f ur visin brings tgether existing Eurpean resurces and initiatives and adds value t these by harnessing the expertise f EO data users frm many walks f life. An ver-arching system makes it easy fr different users t identify and access resurces that suit their wn needs. Thse wh wish t cntribute can easily d s by prviding their wn material, testing and reviewing material prvided by thers, r by ffering advice t their peers thrugh apprpriate n-line fra. 3
The develpment f such a system fr easy access t learning fr all requires us t address several interrelated prblems: The need t demystify EO and increase visibility f the data and its applicatins in all senses, (including literally shwing peple hw EO wrks and what the data lks like). Navigatin and search issues, (including enabling mre direct and intuitive access t relevant data and imagery using cmmn search terms relevant t the target user grups). The need fr standards in terms f platfrms, technlgies and cmmn tls used t develp apps and t facilitate access t data fr new audiences. The rle f data visualizatin, inf-graphics, CGI and film prductin in highlighting, interpreting, and enabling better understanding f the data. Ensuring curriculum links fr schl-based educatin. The need fr brad segmenting f 'nn-technical' user grups, and tailring apps and services accrdingly. The idea f making use f lcal expertise t supprt new users (e.g. in university settings). Encuraging and facilitating the crwd-surcing and peer-review f new educatin resurces by making it easy t cntribute, and ensuring that cntributrs are credited and receive feedback n their wrk. The need fr gd user supprt withut ver-burdening resurce prviders. 3 Meeting the educatin needs f different audiences Grup discussins at the LearnEO! Wrkshp dealt with tw brad audiences: thse in frmal educatin at schls and universities, and thse participating in mre infrmal educatin activities as part f cntinued prfessinal develpment. One might equally distinguish audiences based n their level f educatin, technical expertise, r mtivatin fr wanting t learn mre abut applicatins f Earth bservatin. T achieve the visin fr 2030 where EO data is an integral part f decisin supprt at all levels, EO educatin must (i) attract, inspire and infrm new audiences, and shw them the value f EO data fr envirnmental mnitring and management, and (ii) prvide high-quality, n-ging educatin and training fr envirnmental data science prfessinals, enabling them t use EO-data apprpriately in their wrk. 3.1 Attracting, inspiring and infrming new audiences Althugh Earth bservatin is an inherently pwerful and cmpelling tl nce understd, fr many ptential new audiences the data sets seem inaccessible and t technical t warrant mre detailed attentin. There are perceived barriers t entry, which stem frm the technical jargn f the sectr, the bewildering diversity f data types, and a lack f cherent rutes t accessing the data. Sme user grups will need t be equipped with an understanding f fundamental cncepts and underlying technical principles, but at the utset the main aim must be t grab the attentin f ptential users and shw in clear unequivcal terms what EO can d fr them. This means trying t persnalise the cncepts f EO and t make the cntent feel less remte'. Effrts shuld be made t make EO feel less remte by demnstrating that the underlying principles are actually quite straightfrward. It is crucially imprtant t nt make wrng assumptins abut what these new audiences already knw, including in terms f the basic physics, but rather t demnstrate, as simply as pssible, hw the technlgy wrks, and hw it can play a key rle by infrming the decisin-making prcess in a wide variety f cntexts. 4
3.1.1 EO educatin in schls 3.1.1.1 Inspiring students, building engagement and develping innvatin and skills Earth bservatin is nt a curriculum subject, but it has the ptential fr bringing ther subjects t life and t make them feel mre persnally relevant and emtinally engaging. We want the next generatin f decisin-makers and plicy develpers t have grwn up with a rutine, embedded, and day-t-day expsure t Earth bservatin data prducts, s that they grw int adults with a deep-seated understanding f the majesty, vulnerability and fragility f ur envirnment. Emtinal engagement can be derived frm clear cmmunicatin abut the cntext f the data, but als thrugh high prductin values in terms f the quality f apps, the way in which stries are tld thrugh animatin and vide, and the way in which imagery and ther data is interpreted thrugh high-quality inf-graphics and data visualisatin. In many ways, EO educatin at schl level and fr yunger peple can be seen as a frm f 'capacity building' tw generatins hence. It can cmbine skills develpment with the grwth f an inherent, intuitive understanding f the pwer and rle f Earth bservatin and the perspective it prvides fr plicy develpment, frward planning, and gd decisin-making. T achieve ur visin f the future, we need t cater fr a new generatin f multi-skilled wrkers, and EO educatin shuld bear this in mind by prviding pathways t understanding hw t use specific data fr specific purpses, whilst als encuraging the next generatin t be innvative and resurceful in extending and expanding upn existing resurces and sftware tls. 3.1.1.2 Ensuring curriculum links fr schls and meeting teacher needs T give students the pprtunity t develp an intuitive understanding f EO it is essential t give students and teachers easy access t relevant EO data, instantly and n their wn terms, bth in schl-based educatin and infrmal learning thrugh, fr example, science centres. Teachers are mre easily engaged if EO educatin resurces include in-depth curriculum links, and the ability t search fr data using curriculum terms. Making this pssible in multiple internatinal curricula is nt a trivial task, and requires cllabratin between EO scientists and educatrs at natinal and internatinal level. 3.1.1.3 Cmputer-assisted learning Mdern technlgies such as apps and scial media prvide cnsiderable scpe fr develping EO educatin resurces that can engage students while relieving the burden n ver-wrked teachers. This ptential is already recgnised in sme f the mre recent educatin resurces develped, fr example by ESA (Sectin 4). There are three imprtant cnsideratins in develping an EO app fr frmal r semi-frmal educatin use, where the principal users will be teachers and t sme extent students: 1. Extreme 'time pverty'. An app fr teachers has t meet the very highest standards f intuitiveness, ease f use, and ease f navigatin. Teachers wrk under high levels f time pressure fr lessn preparatin and delivery. Fr an app t have a chance f being used, in-depth and regularly, it must be seen as mre than just an ccasinal gimmick. It must stand up t the very lw tlerances f the target audience, in terms f patience and expectatins fr ease f use. 2. Delivery f the curriculum. Teachers in general will nly be able t make substantive and regular use f sftware tls and visual resurces if they help t deliver the curriculum. The curriculum is the fcal pint f all teaching and learning, and n matter hw innvative the teacher, they will generally avid tls that d nt meet this need. Therefre, curriculum linked terminlgy in the interface f any app r ther educatin resurce is key. 3. Self directed learning. T enable teachers t allw their students t use an app as part f their wn guided r self-directed learning, the cre and any assciated apps, tls and r multimedia resurces must have features that allw students t 'slve challenges' r 'investigate' the data. It has t d mre than just prvide infrmatin. There must als be a 'narrative' dimensin that prvides cntext fr the data. 5
3.1.1.4 Cmbining educatin and citizen science Prvided these cnsideratins are addressed, teachers and students generally relish the pprtunity t engage directly with real-wrld data. This creates depths f learning and insights that are hard t develp in ther ways and allws students t feel they can make a cntributin t science. If an app has the additinal aim f being useful t scientific audiences and t assist with matters such as data validatin, it may ffer cnsiderable pprtunities fr added value t bth the educatin and scientific cmmunities. When students feel they are taking part in real scientific investigatin their mtivatin is likely t increase, with psitive effects n bth learning and persnal engagement. Simultaneusly, the scientific cmmunity may benefit frm a large and willing chrt f 'citizen scientists'. 3.1.2 Nn-technical users in the wider cmmunity Many f the issues that apply t teachers and students als apply t ther 'nn-technical' user grups, such as NGOs, lcal authrities, plicymakers, science cmmunicatrs, and small and medium size enterprises. Time pverty is a fact f life fr almst everyne, with crrespnding need fr easy access t material that is relevant t an individual r rganisatin s remit and respnsibilities. Unless EO data sets, case studies and technical infrmatin are easy t access and demnstrably relevant, decisin-makers are unlikely t invest much effrt in acquiring the knwledge and skill they need in rder t use EO data apprpriately in their wrk. Given the myriad f EO data prducts and applicatin areas develped ver the last decades, and the fact that much mre will be available in the future, the task f develping suitable educatin resurces and training pprtunities is frmidable. It is therefre imprtant t identify the main audiences, and segment them accrding t infrmatin needs at least alng brad lines. T segment them at t granular a level wuld, hwever, ver-cmplicate the prcess f tailring apps and ther tls, cause further fragmentatin f available data surces, tls and ther training resurces, and ultimately make it mre difficult fr an individual r rganisatin t identify and access what they need. The best way t ensure that user requirements are met is likely t be thrugh partnerships between EO scientists, data-prviders, and prfessinal educatrs n the ne hands, and representatives f key user grups such as NGO s n the ther. This culd help t amplify the real wrld educatinal and citizen science cntexts with which educatrs can engage new users and ptential students (including thse in frmal educatin). It will als help in identifying and addressing majr challenges assciated with develping and maintaining the skills need t use EO data apprpriately as ne f several decisin-making tls. 3.2 Prfessinal educatin fr envirnmental data scientists When planning the educatin f Envirnmental Data Scientists it is imprtant t cnsider the different categries that are included in this umbrella term. The wrkshp discussin made a distinctin between frmal, university-level educatin and mre infrmal prfessinal develpment thrugh shrt curses and self-study a divisin we als fllw here. Hwever, there is als a need t lk at the rle and functins f different grups wh are invlved in either frmal r infrmal educatin - students, lecturers, scientific researchers, technicians, senir engineers, cnsultants, plicy makers etc. Other divisins are created by the many envirnmental science disciplines (e.g. meterlgy, ceangraphy, gelgy, bilgy, agriculture), each with separate requirements in terms f backgrund infrmatin, data access, and (t a lesser extent) data prcessing and analysis methdlgies. Curses that bridge the gap between scial and envirnmental sciences als blur the bundaries between educatin designed t deliver a high level f technical expertise and educatin fr a mre general audience wh will take n the rle f bridging the gap between EO-based data science and plicy- and decisin-makers in the wider sciety. 6
Sme general cnsideratins apply t mst f these grups, including, fr example: the need fr learners t acquire technical, cmputing and cmmunicatin skills at a level that enable them t perfrm well in their chsen prfessin, the need t understand the strengths and limitatin f Earth bservatin and ther data types in different cntexts, and the need t address ge-ethics issues that may arise frm the use f EO data fr different purpses. Educatin resurces and training curses shuld aim t prvide students with examples and activities that will facilitate the develpment f technical skills and understanding f the data, as well as a sense f wider respnsibility fr hw the data may be used. 3.2.1 University-level educatin f envirnmental scientists Frmal educatin in universities r equivalent technical training is the main rute t educating new envirnmental data scientists, and t equip them with the skills they will need t perfrm effectively in their future prfessins. Whilst the skill set required by different scientific disciplines, technicians, engineers, EO-experts and students r researchers in different science disciplines may vary slightly, gd cmputing skills are needed fr all these grups. Students n envirnmental science curses are nt necessarily interested in hw t use EO data. Hwever, given the increasing imprtance f EO fr envirnmental mnitring, it is imprtant t demnstrate, at least n an intrductry level, hw EO can cntribute. This will require gd, relevant examples relevant t the different disciplines. Fr thse wh decide that EO data is f interest, the ability t access, read, manipulate, analyse and display data using cmmnly available tls is essential. This can, hwever, be difficult t master fr many students as it cmmnly includes sftware develpment envirnments such as Mat Lab and IDL, and nw increasingly pen surce tls such as Pythn and R, r tlbxes such as thse prvided by ESA fr use with Envisat and Sentinel data. Being able t take advantage f new, clud-based data initiatives t bring tgether different data surces is als becming increasingly imprtant. Interacting with nn-expert users f infrmatin derived frm EO-data and ther surces is nw almst a pre-requisite fr science prfessinals. Training in hw t d this effectively is imprtant, nt nly fr individual scientists, but als fr the n-ging effrt t make EO mre accessible t users in the wider cmmunity, and students learning science cmmunicatin can make a valuable cntributin. Being able t demnstrate the scietal benefits f EO (and envirnmental science generally) is imprtant fr data prviders, rganisatins funding scientific research, and many ther rganisatins active in this field. Hence training that enables students t cmbine sci-ecnmic and envirnmental infrmatin, fr example thrugh the use f GIS, will be imprtant fr many. Clsely allied t scietal benefits f EO is the cncept f Ge-ethics. Earth bservatin is a tl, and like all tls, it has the ptential fr being used t the detriment f the greater gd. Educatin f envirnmental data scientists is nt cmplete withut at lest sme cnsideratin f the different ways in which EO can cntribute t sustainable envirnmental management r t the depletin f resurces, depending n hw it is used. Lecturers and ther trainers in universities and equivalent rganisatins require access t highquality infrmatin, case studies and hands-n training material. Whilst internal quality cntrl may g sme way t ensuring that trainers have the necessary cmpetencies t equip students with the necessary knwledge and skills, this task can be made easier thrugh access t peer reviewed quality-cntrlled educatin resurces. Such material may be used, nt just in frmal educatin, but als in cntinued prfessinal develpment. 3.2.2 Cntinued prfessinal develpment Wrkshp discussins identified three brad grups that require n-ging prfessinal 7
develpment training: Prfessinals with a teaching rle need training curses r self-study training materials that will allw them t incrprate EO int their existing rle. Researchers in a decisin supprt rle fr risk management; upstream they interact with scientists and data prviders; dwnstream they supprt risk management f sme srt, fr example thrugh insurance, cntingency planning, emergency respnse, etc. Prfessinals prviding decisin supprt fr lnger term planning and management in rder t advise plicy-makers in gvernment, civil sciety and industry, r ffer guidance t nn- EO science that benefits frm EO as ne f many bservatinal tls. An effective EO educatin prgram needs t lk at the needs f these users and decide hw best t make necessary resurces easily available. This means wrking backwards frm the decisin makers in different applicatin areas. What are their needs? What infrmatin d they require, in what frmat? Hw d they use this infrmatin? Frm such an analysis it becmes pssible t determine what training is necessary t equip decisin supprt scientists with the knwledge and skills they need in rder t prvide timely and reliable infrmatin t end users. Fr example, what level f understanding f different data prducts, sensrs, prcessing systems, algrithms and analysis methds will data scientists need in rder t have cnfidence in the infrmatin they prvide? Knwing the strength and limitatins f different sensrs and data prducts under different cnditins r in different gegraphical regins can be imprtant here. There may be a need t cnsider the rle f supprting data, fr example frm in situ mnitring systems r numerical mdelling. Training may als be needed in hw t deliver envirnmental infrmatin t different target audience in ways that are understandable, inspire cnfidence and include apprpriate estimates f uncertainty. In the met cmmunity the US based COMET prgramme prvides effective prfessinal training, and has been arund fr a lng time, s that it is trusted. Smething similar is needed fr lngterm prfessinal training in ther areas f envirnmental science. 4 Existing EO educatin resurces and initiatives The wide variety f Earth bservatin satellites, data sets and applicatin areas is reflected in the diversity f existing EO educatin resurces and training initiatives. We have rganised these int fur different categries: web-resurces and e-learning, capacity building, sftware and tls, and EO utreach. The review integrates material presented at the Frascati EO Educatin Wrkshp with ther infrmatin frm ESA LearnEO! and frm sme f the presentatins given at EO Open Science 2.0. It shuld nt be seen as a cmprehensive review f available resurces. 4.1 Web-Resurces and E-Learning 4.1.1 ESA A dedicated website fr EO Educatin and Training activities is published n ESA s EO prtal. 5 This prvides a cmprehensive verview and easy access t all ESA prgrammes in EO educatin, training and capacity building. A sectin n primary and secndary level EO educatin includes descriptins and links t nline tls, teacher training curses and material that can be rdered frm the ESA educatin ffice. Anther sectin includes summaries f EO training curses at university level with links t their respective webpages with access t presentatins and ESA / Third Party Missin (TPM) data used fr exercises. Similar material is available fr advanced training at pst-graduate level. The ESA Eduspace multi-lingual website 6 is dedicated t secndary educatin. The aim f 5 https://earth.esa.int/web/guest/e-educatin-and-training 6 http://www.esa.int/specials/eduspace_en 8
Eduspace is t prvide attractive image data, infrmatin and tls suitable fr teaching and learning a variety f tpics in Gegraphy, Physics, Envirnmental Science and related subjects, accrding t the curriculum f each cuntry. The main value f Eduspace lies in the practical nature f its e-learning cntent. The website nt nly explains the thery and applicatins f EO in terms suitable fr a secndary schl audience, but als prvides case studies that give practical examples f hw EO data is used. Each case study presents student with a real wrld prblem, which they need t address thrugh hands-n prcessing f EO data using sftware designed fr use in schls. The Eduspace Image Catalgue 7 prvides Eduspace users with a multi-missin catalgue f EO data ver Eurpe. This prvides teachers and students with carefully selected example data fr use in Eduspace case studies and allws them t adapt (persnalise) the case studies with EO data frm their specific regin f interest. The Interactive Metesat n-line applicatin - a new nline tl that shws satellite data cmbined with student measurements - has been develped as an Eduspace mdule alng with a case study n the interpretatin f Metesat images. In the field f e-learning ESA has als develped Earth frm Space: The living beauty 8 - the first electrnic bk shwcasing EO applicatins, develped fr Apple s ipad and available thrugh itunes. The 105 page bk takes the reader n a scientific vyage that shws hw sme f the latest technlgy has changed the way we view the Earth. There are five chapters: Slid Earth, Oceans, Crysphere, Atmsphere and Land, shwing the latest and mst impressive results f ESA s EO missins. Electrnic bks n individual missins are als being develped. ESA LearnEO 9 prvides hands-n lessns n different EO applicatin areas, using data frm ESA satellites. The lessns are designed fr the Bilk sftware, and cme cmplete with backgrund infrmatin, step-by-step instructins, example data and mdel answers t questins psed in the lessns in rder t stimulate student learning. Material frm the lessns are available under a Creative Cmmns licence t anyne wh wishes t build n LearnEO resurces t create their training materials. An ESA MOOC, Mnitring Climate Change frm Space 10 prvides basic infrmatin abut the use EO data t mnitr and study climate variability and change. The MOOC has been specifically designed t vercme perceived barriers t the use f EO by nn-technical users. It encurages wider use f EO data by prviding practical, real-wrld examples f hw f EO data are used t mnitr and adapt t climate change, increase resilience t climate-related hazards, and prvide decisin supprt fr sustainable develpment and resurce management planning. The curse explres and addresses sme f the prblems related t the take-up and usage f EO data, and demnstrates the benefits f using EO data in scenari planning. 4.1.2 NASA The gal f the NASA Applied Remte SEnsing Training (ARSET) 11 is t increase the utility f NASA earth science and mdel data fr plicy makers, regulatry agencies, and ther applied science prfessinals in the areas f Health and Air Quality, Water Resurces, Ec Frecasting, and Disaster Management. The primary activities f this prject are webinars and in-persn curses. NASA WrldWind 12, pens up pssibilities fr virtual glbe applicatins. The use-cases include scial media type activity as well as mre sphisticated urban infrastructure management, climate research, disaster respnse and all types f navigatin, frm persnal directins t industrial supply chain, t aernautics and satellite tracking. 7 http://maps.e.esa.int/eduspace/index.jsp?ncmb=true 8 www.esa.int/highlights/esa_s_first_ibk, 9 www.learn-e.rg 10 https://www.futurelearn.cm/curses/climate-frm-space 11 http://arset.gsfc.nasa.gv/ 12 http://webwrldwind.rg and http://wrldwind.arc.nasa.gv/java/ 9
4.1.3 NOAA NOAA's Natinal Weather Service (NWS) and ther rganizatins are spnsring MetEd 13 - a free cllectin f learning resurces fr the gescience cmmunity. The training cnsists f lessns and curses. A lessn is targeted tward ne fcused subject, whereas a curse is a cllectin f lessns that pertain t a brader subject area. It is pssible t receive certificates f cmpletin fr bth lessns and curses. Curses are entirely self-paced and available fr pen enrlment. Links are als prvided t selected resurces nt hsted n MetEd. 4.1.4 Eurpean Spatial Data Research (EurSDR) Eurpean Spatial Data Research (EurSDR) hlds distance e-learning curses n EO and geinfrmatin tpics. 14 These curses can be fllwed ver the Internet frm any lcatin, allwing participants t update their knwledge with minimum disruptin. Each curses requires abut thirty hurs f nline study and is cmpleted in tw weeks. 4.1.5 Other resurces SAR-Edu 15 is an nline learning prtal that gives access t lessns, tutrials and talks; tgether these prvide in-depth infrmatin abut SAR data, prcessing, and data analysis fr a range f applicatins. The material is at an advanced level, aimed at scientists and future EO prfessinals. 4.2 Capacity building initiatives Develping human capacity t access, prcess and analyse EO data requires training at many different levels. Here we review sme f the initiatives supprted by internatinal rganizatins, EU funded prjects and ther internatinal cllabratins. 4.2.1 On-ging internatinal prgrammes (in alphabetical rder) The COMET 16 Prgram was established in 1989 by UCAR and NOAA s NWS t prmte a better understanding f messcale meterlgy amng weather frecasters and t maximize the benefits f new weather technlgies. The COMET missin has expanded, and tday COMET uses innvative methds t disseminate and enhance scientific knwledge in the envirnmental sciences, particularly meterlgy, but als areas such as ceangraphy, hydrlgy, space weather and emergency management. COMET s innvative educatinal slutins include cuttingedge distance learning materials, n-site and virtual training events, and supprt fr the effrt f individuals t advance their skills and scientific knwledge. A free cllectin f learning resurces fr the gescience cmmunity has been created within MetEd. 11 The Eurpean Assciatin f Remte Sensing Labratries (EARSEL) rganises wrkshps fr secndary schl teachers. 17 These typically last 1-2 days, ften assciated with cnferences r exhibitins f interest, and are supprted by ESA. The Eurpean Gesciences Unin (EGU) Cmmittee n Educatin has rganised Gesciences Infrmatin fr Teachers (GIFT) Wrkshps since 2003. These 2.5-day teachertraining wrkshps are held in cnjunctin with EGU s annual General Assembly, and typically hst abut 80 teachers. Their main bjective is t spread first-hand scientific infrmatin t science teachers in primary and secndary schls, thereby shrtening the time between discvery and text-bk significantly. Teachers are prvided with material that can be used directly in the classrm, and lectures frm the GIFT wrkshps are freely available as vides n YuTube r 13 https://www.meted.ucar.edu/index.php 14 http://www.eursdr.net/educatin/current 15 https://saredu.dlr.de 16 http://www.cmet.ucar.edu/ 17 http://www.earsel.rg/?target=educ 10
EGU TV 18 ESA: Every summer ESA s Educatin Office welcmes arund 40 secndary schl teachers frm acrss Eurpe t ESA s Eurpean Space Research and Technlgy Centre (ESTEC) in the Netherlands fr the ESA Summer Wrkshp fr teachers 19. Over fur days teachers participate in a variety f activities that shw hw space can be used as a cntext fr teaching different schl subjects. Entitled Watching ver the Earth, the ESA Teacher s Pack includes a selectin f Remte Sensing/EO tpics and is targeted t lwer secndary level students (age 11-14). The pack is available in several languages (English, French, German, Spanish, Italian and Dutch) in hard cpy, and may als be dwnladed frm a dedicated ESA website. 20 ESA summer schls n Mnitring and Mdelling f the Earth System 21 prmtes the explitatin f EO data acrss disciplines, with a specific fcus n EO data assimilatin int Earth System mdels. The summer schls take place every ther year at ESA/ESRIN in Italy, and are attended by an average f abut 65 PhD students and early-career researchers. ESA s advanced thematic training curses in land, cean and atmspheric remte sensing fr the next generatin f Principal Investigatrs (PIs) 22 are typically attended by PhD students and early pst-dctral scientists, wh wrk n the scientific explitatin f ESA and Third Party Missin EO data. These curses are held annually and are hsted in Eurpean Universities and Research institutins, with the hst cuntry rtating amng the ESA Member States. The ESA TIGER initiative 23 was launched in 2002 t prmte the use f EO data fr imprved Integrated Water Resurces Management (IWRM) in Africa. Besides facilitating EO data access and supprting crsscutting activities f crdinatin and utreach, TIGER als fcuses n training and capacity building curses (3-5 days events), designed t supprt the effrts f its African partners (water authrities, technical centres, universities) t develp independent capacity t explit EO technlgy in the management f water resurces and adaptatin t climate change. The EUMETCAL 24 prgramme started in 2001 and will develp Eurpean training cperatin in the field f meterlgy until 2017. Tday it is the Eurpean Virtual Organisatin fr Meterlgical Training. Its bjectives are t: (i) serve as the Eurpean virtual training rganisatin, prviding a frum fr creatin and exchange f training resurces in meterlgy and related tpics; (ii) prvide a mechanism whereby Eurpean Natinal Meterlgical Services can cllabrate t enhance their training capabilities n a lng-term basis; and (iii) meet the training requirements f Eurpean NMSs in the lng term. Key achievements are its extensive virtual training library, its training wrkshps, interactive learning mdules and crdinatin f blended and n-line curses in meterlgy. EUMETCAL activities link trainers and prfessinals frm participating and partner cuntries, prmte the exchange f best practice, and encurage sharing f training material. GEO fr All 25 aims t make gespatial educatin and pprtunities accessible t all. By cmbining the ptential f free and pen GI sftware, pen data, pen standards, pen access t research publicatins, pen educatin resurces in Gespatial educatin and research will enable creatin f sustainable innvatin ecsystem t advance the discipline. Over 100 labs arund the wrld are part f the initiative. The Glbal Earth Observatin System f Systems (GEOSS) 26 prvides decisin-supprt tls t a wide variety f users. This system f systems will practively link tgether existing and planned bserving systems arund the wrld and supprt the develpment f new systems where 18 www.egu.eu/utreach/egu-tv 19 www.esa.int/educatin/teachers_crner/annual_esa_summer_teacher_wrkshp 20 www.esa.int/educatin/teacher_s_pack 21 https://earth.esa.int/web/e-summer-schl/hme 22 https://earth.esa.int/web/guest/e-educatin-and-trainingweb/eedu/pis-advanced-training 23 www.tiger.esa.int 24 http://www.eumetcal.rg/ 25 http://www.gefrall.rg 26 http://www.earthbservatins.rg/gess.php 11